diff --git a/src/Accelerators/NNPA/Conversion/ZHighToZLow/ZHighToZLow.cpp b/src/Accelerators/NNPA/Conversion/ZHighToZLow/ZHighToZLow.cpp
index c3fca41393..adff6073e9 100644
--- a/src/Accelerators/NNPA/Conversion/ZHighToZLow/ZHighToZLow.cpp
+++ b/src/Accelerators/NNPA/Conversion/ZHighToZLow/ZHighToZLow.cpp
@@ -190,47 +190,27 @@ Value insertAllocOrEmitZeroConstant(ArrayRef<IndexExpr> dims,
         affine::normalizeMemRefType(mlir::cast<MemRefType>(zMemRefType.value));
 
     // Create a ZHighStickifiedConstantOp.
-
-    // Keep previous implementation about generating stickified data at
-    // ZHighConstPropagationPass. To use this, comment in and set directive "
-    // NNPA_ZHIGH_STICKIFIEDCONST_GEN"
-    //
-    // #ifdef NNPA_ZHIGH_STICKIFIEDCONST_GEN
-    //     // Set zero in value attribute as DenseResourceElementsAttribute.
-    //     ZHighStickifiedConstantOp stickifiedConstant =
-    //         rewriter.create<ZHighStickifiedConstantOp>(loc, resType,
-    //             /*stickified=*/rewriter.getBoolAttr(true),
-    //             /*value=*/nullptr,
-    //             /*alignment=*/rewriter.getI64IntegerAttr(4096));
-    //
-    //     // Use an dense resource attribute to store stickified data.
-    //     // Attribute type: tensor<sizeInBytes x i8>
-    //     int64_t sizeInBytes =
-    //         affine::getIntOrFloatMemRefSizeInBytes(resType).value();
-    //     char *rawData = static_cast<char *>(malloc(sizeInBytes));
-    //     assert(rawData && "failed to allocate memory for stickified data");
-    //     memset(rawData, 0, sizeInBytes);
-    //     DenseResourceElementsAttr valueAttr =
-    //     DenseUI8ResourceElementsAttr::get(
-    //         RankedTensorType::get({sizeInBytes}, rewriter.getI8Type()),
-    //         stickifiedConstant.getOperation()
-    //             ->getDialect()
-    //             ->getNamespace(), // use the dialect as the blob "hint"
-    //         HeapAsmResourceBlob::allocateAndCopyWithAlign(
-    //             llvm::ArrayRef(rawData, sizeInBytes), alignof(char)));
-    //     stickifiedConstant.setValueAttr(valueAttr);
-    //     free(rawData);
-    // #else
-
-    // Set zero in value attribute as SplatElementsAttr.
-    FloatAttr floatZero = rewriter.getFloatAttr(resType.getElementType(), 0.0);
-    ZHighStickifiedConstantOp stickifiedConstant = rewriter.create<
-        ZHighStickifiedConstantOp>(loc, resType,
-        /*stickified=*/rewriter.getBoolAttr(true),
-        /*value=*/SplatElementsAttr::get(cast<ShapedType>(resType), floatZero),
-        /*alignment=*/rewriter.getI64IntegerAttr(4096));
-
-    // #endif // NNPA_ZHIGH_STICKIFIEDCONST_GEN
+    ZHighStickifiedConstantOp stickifiedConstant =
+        rewriter.create<ZHighStickifiedConstantOp>(loc, resType,
+            /*value=*/nullptr,
+            /*alignment=*/rewriter.getI64IntegerAttr(4096));
+
+    // Use an dense resource attribute to store stickified data.
+    // Attribute type: tensor<sizeInBytes x i8>
+    int64_t sizeInBytes =
+        affine::getIntOrFloatMemRefSizeInBytes(resType).value();
+    char *rawData = static_cast<char *>(malloc(sizeInBytes));
+    assert(rawData && "failed to allocate memory for stickified data");
+    memset(rawData, 0, sizeInBytes);
+    DenseResourceElementsAttr valueAttr = DenseUI8ResourceElementsAttr::get(
+        RankedTensorType::get({sizeInBytes}, rewriter.getI8Type()),
+        stickifiedConstant.getOperation()
+            ->getDialect()
+            ->getNamespace(), // use the dialect as the blob "hint"
+        HeapAsmResourceBlob::allocateAndCopyWithAlign(
+            llvm::ArrayRef(rawData, sizeInBytes), alignof(char)));
+    stickifiedConstant.setValueAttr(valueAttr);
+    free(rawData);
 
     res = stickifiedConstant.getResult();
   } else {
@@ -706,7 +686,7 @@ struct ZHighToZLowUnstickOpLowering : public ConversionPattern {
 };
 
 //===----------------------------------------------------------------------===//
-// Lower ZHigh Stickified Constant to ZLow Stickified Constant
+// Lower ZHigh Stickified Constant to KrnlGlobal
 //===----------------------------------------------------------------------===//
 
 struct ZHighToZLowStickifiedConstantOpLowering : public ConversionPattern {
@@ -719,7 +699,7 @@ struct ZHighToZLowStickifiedConstantOpLowering : public ConversionPattern {
   LogicalResult matchAndRewrite(Operation *op, ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const final {
     Location loc = op->getLoc();
-    ZHighStickifiedConstantOp zhighStickifiedConstOp =
+    ZHighStickifiedConstantOp stickifiedConstOp =
         llvm::dyn_cast<ZHighStickifiedConstantOp>(op);
 
     // Convert ZTensor type to MemRefType.
@@ -733,59 +713,36 @@ struct ZHighToZLowStickifiedConstantOpLowering : public ConversionPattern {
         affine::normalizeMemRefType(mlir::cast<MemRefType>(zMemRefType.value));
     ArrayRef<int64_t> normalizedShape = normalizedType.getShape();
 
-    // Create ZLowStickifiedConstantOp.
-    StringAttr layout =
-        getZTensorLayoutAttr(rewriter, *op->result_type_begin());
-
-    // Keep previous implementation about generating stickified data at
-    // ZHighConstPropagationPass. To use this, comment in and set directive "
-    // NNPA_ZHIGH_STICKIFIEDCONST_GEN"
-    //
-    // #ifdef NNPA_ZHIGH_STICKIFIEDCONST_GEN
-    //     // Lower to KrnlGlobalOp
-    //     // Get dense resource attribute.
-    //     auto blob = mlir::cast<DenseResourceElementsAttr>(
-    //         zhighStickifiedConstOp.getValue().value())
-    //                     .getRawHandle()
-    //                     .getBlob();
-    //     assert(blob && "Expecting dense resource with a valid blob");
-    //     ArrayRef<char> data = blob->getData();
-    //     // Validate the stickified tensor.
-    //     int64_t memRefSizeInBytes = getMemRefEltSizeInBytes(normalizedType);
-    //     memRefSizeInBytes *= normalizedType.getNumElements();
-    //     assert((data.size() == static_cast<uint64_t>(memRefSizeInBytes)) &&
-    //            "The stickified tensor's buffer size and MemRef's size
-    //            mismatched");
-    //     // Create a KrnlGlobalOp.
-    //     KrnlGlobalOp constantOp =
-    //         rewriter.create<KrnlGlobalOp>(loc, zMemRefType.value,
-    //             /*shape=*/
-    //             rewriter.getI64ArrayAttr(normalizedShape),
-    //             /*name=*/
-    //             rewriter.getStringAttr(
-    //                 "constant_stickify_" + std::to_string(constantID)),
-    //             /*value=*/zhighStickifiedConstOp.getValueAttr(),
-    //             /*offset=*/nullptr,
-    //             /*alignment=*/zhighStickifiedConstOp.getAlignmentAttr());
-    // #else
-    ZLowStickifiedConstantOp constantOp =
-        rewriter.create<ZLowStickifiedConstantOp>(loc,
-            mlir::cast<MemRefType>(zMemRefType.value),
+    // Get dense resource attribute.
+    auto blob = mlir::cast<DenseResourceElementsAttr>(
+        stickifiedConstOp.getValue().value())
+                    .getRawHandle()
+                    .getBlob();
+    assert(blob && "Expecting dense resource with a valid blob");
+    ArrayRef<char> data = blob->getData();
+
+    // Validate the stickified tensor.
+    int64_t memRefSizeInBytes = getMemRefEltSizeInBytes(normalizedType);
+    memRefSizeInBytes *= normalizedType.getNumElements();
+    assert((data.size() == static_cast<uint64_t>(memRefSizeInBytes)) &&
+           "The stickified tensor's buffer size and MemRef's size mismatched");
+
+    // Create a KrnlGlobalOp.
+    KrnlGlobalOp constantGlobal =
+        rewriter.create<KrnlGlobalOp>(loc, zMemRefType.value,
             /*shape=*/
             rewriter.getI64ArrayAttr(normalizedShape),
             /*name=*/
             rewriter.getStringAttr(
                 "constant_stickify_" + std::to_string(constantID)),
-            /*stickified=*/zhighStickifiedConstOp.getStickifiedAttr(),
-            /*value=*/zhighStickifiedConstOp.getValueAttr(),
-            /*layout=*/layout,
-            /*offset=*/rewriter.getI64IntegerAttr(0),
-            /*alignment=*/zhighStickifiedConstOp.getAlignmentAttr());
-    // #endif  // NNPA_ZHIGH_STICKIFIEDCONST_GEN
+            /*value=*/stickifiedConstOp.getValueAttr(),
+            /*offset=*/nullptr,
+            /*alignment=*/stickifiedConstOp.getAlignmentAttr());
+
     // Increment constant ID:
     constantID++;
 
-    rewriter.replaceOp(op, constantOp.getResult());
+    rewriter.replaceOp(op, constantGlobal.getResult());
     return success();
   }
 };
diff --git a/src/Accelerators/NNPA/Dialect/ZHigh/CMakeLists.txt b/src/Accelerators/NNPA/Dialect/ZHigh/CMakeLists.txt
index af5bab1779..915ed61717 100644
--- a/src/Accelerators/NNPA/Dialect/ZHigh/CMakeLists.txt
+++ b/src/Accelerators/NNPA/Dialect/ZHigh/CMakeLists.txt
@@ -47,7 +47,6 @@ add_onnx_mlir_library(OMZHighOps
   OMONNXOps # Use ONNXShapeHelper 
   OMLayoutHelper
   OMShapeHelperOpInterface
-  OMStickify
   OMNNPACompilerOptions
   MLIRIR
 
diff --git a/src/Accelerators/NNPA/Dialect/ZHigh/ZHigh.td b/src/Accelerators/NNPA/Dialect/ZHigh/ZHigh.td
index 8b17786bcd..d2624138c0 100644
--- a/src/Accelerators/NNPA/Dialect/ZHigh/ZHigh.td
+++ b/src/Accelerators/NNPA/Dialect/ZHigh/ZHigh.td
@@ -862,14 +862,11 @@ def ZHighStickifiedConstantOp:ZHigh_Op<"StickifiedConstant", [Pure]> {
   let summary = "ZHigh Stickified Constant operation";
   let description = [{
     This operator produces a constant tensor to store stickified data.
-    `value` attribute has original constant or stickified constant.
-    `stickified` attribute indicates the `value` is already stickified or not.
     Stickified data is opaque and must be 4K-aligned. One who produces
     the stickified data must make sure its size in bytes consistent with
     the output tensor's size.
   }];
-  let arguments = (ins BoolAttr:$stickified,
-                       OptionalAttr<AnyAttr>:$value,
+  let arguments = (ins OptionalAttr<AnyAttr>:$value,
                        DefaultValuedAttr<I64Attr, "4096">:$alignment);
   let results = (outs AnyZTensor:$output);
 }
diff --git a/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.cpp b/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.cpp
index 028b5ac528..f5b9ff910f 100644
--- a/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.cpp
+++ b/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.cpp
@@ -12,6 +12,7 @@
 
 #include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp"
 #include "src/Accelerators/NNPA/Compiler/NNPACompilerOptions.hpp"
+#include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps.hpp"
 #include "src/Accelerators/NNPA/Support/LayoutHelper.hpp"
 
 #include "src/Dialect/ONNX/DialectBuilder.hpp"
@@ -481,55 +482,5 @@ IntegerAttr getDefaultSaturation(PatternRewriter &rewriter) {
     return IntegerAttr();
 }
 
-/// MLIR type to zDNN type.
-zdnn_data_types mlirTypeToZDNNType(Type elementType) {
-  if (mlir::isa<FloatType>(elementType)) {
-    FloatType floatTy = mlir::cast<FloatType>(elementType);
-    if (floatTy.getWidth() == 16) {
-      return FP16;
-    } else if (floatTy.getWidth() == 32) {
-      return FP32;
-    } else
-      llvm_unreachable("Unsupported data type.");
-  } else
-    llvm_unreachable("Unsupported data type.");
-}
-
-/// Get stickified data from denseElementAttribute
-ArrayRef<char> getStickifiedDataOfDenseElemAttr(
-    DenseElementsAttr denseAttr, StringAttr layout) {
-  ArrayRef<int64_t> shape = denseAttr.getType().getShape();
-  Type elementType = denseAttr.getType().getElementType();
-  int rank = shape.size();
-  // Read attributes's raw data.
-  std::vector<char> attrData;
-  getRawData(denseAttr, attrData);
-  // Call stickify.
-  zdnn_tensor_desc pre_tfrmd_desc, tfrmd_desc;
-  // pre-transformed desc.
-  zdnn_data_layouts zDNNLayout =
-      convertLayoutAttrToZDNNDataLayout(rank, layout);
-  // If zDNNLayout is NHWC, we stickify directly from NCHW.
-  if (zDNNLayout == ZDNN_NHWC)
-    zDNNLayout = ZDNN_NCHW;
-  zdnn_data_types zDNNType = onnx_mlir::zhigh::mlirTypeToZDNNType(elementType);
-  set_info_pre_transformed_desc(&pre_tfrmd_desc, zDNNLayout, zDNNType, shape);
-  // transformed desc.
-  zdnn_status status = generate_transformed_desc(&pre_tfrmd_desc, &tfrmd_desc);
-  assert(status == ZDNN_OK);
-  // Stick data using the software stickify.
-  zdnn_ztensor ztensor;
-  init_ztensor(&pre_tfrmd_desc, &tfrmd_desc, &ztensor);
-  status = allochelper_ztensor_alloc(&ztensor);
-  assert(status == ZDNN_OK);
-  status = stickify(&ztensor, attrData.data());
-  assert(status == ZDNN_OK);
-  int64_t sizeInBytes = ztensor.buffer_size;
-  char *rawData = (char *)malloc(sizeInBytes);
-  memcpy(rawData, ztensor.buffer, sizeInBytes);
-  allochelper_ztensor_free(&ztensor);
-  return llvm::ArrayRef(rawData, sizeInBytes);
-}
-
 } // namespace zhigh
 } // namespace onnx_mlir
diff --git a/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp b/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp
index 4d353950a6..def0813d7b 100644
--- a/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp
+++ b/src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp
@@ -16,7 +16,6 @@
 #include "mlir/IR/Builders.h"
 #include "mlir/IR/BuiltinAttributes.h"
 #include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps.hpp"
-#include "src/Accelerators/NNPA/Support/Stickify/Stickify.hpp"
 
 namespace onnx_mlir {
 namespace zhigh {
@@ -89,13 +88,6 @@ bool hasNNPAUse(mlir::Value v);
 /// Get saturation settings.
 mlir::IntegerAttr getDefaultSaturation(mlir::PatternRewriter &rewriter);
 
-/// MLIR type to zDNN type.
-zdnn_data_types mlirTypeToZDNNType(mlir::Type elementType);
-
-/// Get stickified data from denseElementAttribute
-mlir::ArrayRef<char> getStickifiedDataOfDenseElemAttr(
-    mlir::DenseElementsAttr denseAttr, mlir::StringAttr layout);
-
 } // namespace zhigh
 } // namespace onnx_mlir
 #endif
diff --git a/src/Accelerators/NNPA/Dialect/ZLow/CMakeLists.txt b/src/Accelerators/NNPA/Dialect/ZLow/CMakeLists.txt
index 99dd227c39..c259f721c3 100644
--- a/src/Accelerators/NNPA/Dialect/ZLow/CMakeLists.txt
+++ b/src/Accelerators/NNPA/Dialect/ZLow/CMakeLists.txt
@@ -11,13 +11,8 @@ add_onnx_mlir_library(OMZLowOps
   DEPENDS
   OMZLowIncGen
   OMONNXZLowCombineIncGen
-  OMKrnlGlobalOpInterface
 
   LINK_LIBS PUBLIC
   MLIRIR
   OMMlirDialects
-  OMZHighOps
-
-  ACCEL_INCLUDE_DIRS PRIVATE
-  ${NNPA_INCLUDE_PATH}
   )
diff --git a/src/Accelerators/NNPA/Dialect/ZLow/ZLow.td b/src/Accelerators/NNPA/Dialect/ZLow/ZLow.td
index 4376a3d90b..63fcb0704d 100644
--- a/src/Accelerators/NNPA/Dialect/ZLow/ZLow.td
+++ b/src/Accelerators/NNPA/Dialect/ZLow/ZLow.td
@@ -44,7 +44,6 @@ def ZMemRef : MemRefOf<[DLF16]>;
 //===----------------------------------------------------------------------===//
 
 include "mlir/Interfaces/SideEffectInterfaces.td"
-include "src/Interface/KrnlGlobalOpInterface.td"
 
 def ZLowAddOp:ZLow_Op<"add", [MemRefsNormalizable,
     DeclareOpInterfaceMethods<MemoryEffectsOpInterface>]> {
@@ -548,20 +547,4 @@ def ZLowConvertF32ToDLF16VectorOp:ZLow_Op<"vec_f32_to_dlf16", [Pure]> {
   ];
 }
 
-def ZLowStickifiedConstantOp:ZLow_Op<"stickifiedConstant", [MemRefsNormalizable,
-    DeclareOpInterfaceMethods<KrnlGlobalOpInterface>]> {
-  let summary = "ZLow Stickified Constant operation.";
-  let description = [{
-
-  }];
-  let arguments = (ins AnyAttr:$shape,
-                       StrAttr:$name,
-                       BoolAttr:$stickified,
-                       OptionalAttr<AnyAttr>:$value,
-                       OptionalAttr<StrAttr>:$layout,
-                       OptionalAttr<I64Attr>:$offset,
-                       DefaultValuedAttr<I64Attr, "4096">:$alignment);
-  let results = (outs ZMemRef:$output);
-}
-
 #endif // ZLOW_OPS
diff --git a/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.cpp b/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.cpp
index 4cf9d79b2b..7526933777 100644
--- a/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.cpp
+++ b/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.cpp
@@ -12,27 +12,19 @@
 //
 //===----------------------------------------------------------------------===//
 
-#include "mlir/Dialect/Affine/Analysis/Utils.h"
 #include "mlir/Dialect/Shape/IR/Shape.h"
 #include "mlir/Dialect/Traits.h"
 #include "mlir/IR/Block.h"
 #include "mlir/IR/Builders.h"
 #include "mlir/IR/BuiltinOps.h"
-#include "mlir/IR/DialectResourceBlobManager.h"
 #include "mlir/IR/IntegerSet.h"
 #include "mlir/IR/Matchers.h"
 #include "mlir/IR/OpImplementation.h"
 #include "mlir/IR/PatternMatch.h"
 #include "llvm/ADT/SetVector.h"
 #include "llvm/ADT/SmallBitVector.h"
-#include "llvm/ADT/TypeSwitch.h"
-#include "llvm/Support/Debug.h"
 
-#include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp"
 #include "src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.hpp"
-#include "src/Accelerators/NNPA/Support/LayoutHelper.hpp"
-#include "src/Accelerators/NNPA/Support/Stickify/Stickify.hpp"
-#include "src/Dialect/ONNX/ONNXOps/OpHelper.hpp"
 
 using namespace mlir;
 
@@ -366,75 +358,6 @@ void ZLowBatchNormOp::getEffects(
       SideEffects::DefaultResource::get());
 }
 
-/// Create a buffer for constant. Stickified data is
-/// created and set if `stickified` attribute is false.
-ArrayRef<char> ZLowStickifiedConstantOp::getBuffer() {
-  MLIRContext *context = getOperation()->getContext();
-  PatternRewriter rewriter(context);
-  ArrayRef<char> ret;
-  if (getValueAttr()) {
-    StringAttr layout = getLayoutAttr();
-    auto dataAttr = getValue().value();
-    if (!getStickified()) {
-      // The case which the data in value attribute is still not stickified.
-      // Get the buffer after stickification.
-      DenseElementsAttr denseAttr = mlir::cast<DenseElementsAttr>(dataAttr);
-      ret =
-          onnx_mlir::zhigh::getStickifiedDataOfDenseElemAttr(denseAttr, layout);
-    } else {
-      // Get the buffer from `value` attribute.
-      int64_t sizeInBytes = getBufferSize();
-      char *rawData = (char *)malloc(sizeInBytes);
-      std::vector<char> attrData;
-      getRawData(dataAttr, attrData);
-      memcpy(rawData, attrData.data(), sizeInBytes);
-      ret = llvm::ArrayRef(rawData, sizeInBytes);
-    }
-  }
-  return ret;
-}
-
-/// Get buffer size from result.
-uint64_t ZLowStickifiedConstantOp::getBufferSize() {
-  const Type type = getOperation()->getResults()[0].getType();
-  const MemRefType memRefTy = mlir::cast<mlir::MemRefType>(type);
-  auto sizeInBytes = affine::getIntOrFloatMemRefSizeInBytes(memRefTy);
-  return sizeInBytes.has_value() ? sizeInBytes.value() : 0;
-}
-
-/// Free buffer created by getBuffer().
-void ZLowStickifiedConstantOp::freeBuffer(ArrayRef<char> rawData) {
-  free(const_cast<char *>(rawData.data()));
-  return;
-}
-
-/// Get a buffer, set/copy it to value attribute, and free the buffer.
-void ZLowStickifiedConstantOp::updateValueAttr() {
-  MLIRContext *context = getOperation()->getContext();
-  PatternRewriter rewriter(context);
-  // Set buffer when the value attribute is still not stickified or is splat
-  // with dense element attribute.
-  if (getValueAttr()) {
-    bool isStickified = getStickified();
-    bool isSplat = false;
-    if (auto denseAttr = mlir::dyn_cast<DenseElementsAttr>(getValue().value()))
-      isSplat = denseAttr.isSplat();
-    if (!isStickified || isSplat) {
-      ArrayRef<char> rawData = getBuffer();
-      int64_t sizeInBytes = getBufferSize();
-      DenseResourceElementsAttr valueAttr = DenseUI8ResourceElementsAttr::get(
-          RankedTensorType::get({sizeInBytes}, rewriter.getI8Type()),
-          getOperation()
-              ->getDialect()
-              ->getNamespace(), // use the dialect as the blob "hint"
-          HeapAsmResourceBlob::allocateAndCopyWithAlign(
-              rawData, alignof(char)));
-      setValueAttr(valueAttr);
-      freeBuffer(rawData);
-    }
-  }
-}
-
 } // namespace zlow
 } // namespace onnx_mlir
 
diff --git a/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.hpp b/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.hpp
index 9ebeb64447..2050779dcb 100644
--- a/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.hpp
+++ b/src/Accelerators/NNPA/Dialect/ZLow/ZLowOps.hpp
@@ -24,8 +24,6 @@
 #include "mlir/IR/Dialect.h"
 #include "mlir/IR/OpDefinition.h"
 
-#include "src/Interface/KrnlGlobalOpInterface.hpp"
-
 /// Include the auto-generated header files containing the declarations of the
 /// ZLow dialect and operations.
 #include "src/Accelerators/NNPA/Dialect/ZLow/ZLowDialect.hpp.inc"
diff --git a/src/Accelerators/NNPA/Transform/ZHigh/CMakeLists.txt b/src/Accelerators/NNPA/Transform/ZHigh/CMakeLists.txt
index dfc7e7f5b0..7f9bfe05ec 100644
--- a/src/Accelerators/NNPA/Transform/ZHigh/CMakeLists.txt
+++ b/src/Accelerators/NNPA/Transform/ZHigh/CMakeLists.txt
@@ -12,6 +12,7 @@ add_onnx_mlir_library(OMZHighConstPropagation
   MLIRRewrite
   MLIRTransformUtils
   OMLayoutHelper
+  OMStickify
   OMZHighOps
   OMONNXOps
 
@@ -46,9 +47,6 @@ add_onnx_mlir_library(OMZHighClipToDLFloat
   MLIRTransformUtils
   OMZHighOps
   OMONNXOps
-
-  ACCEL_INCLUDE_DIRS PRIVATE
-  ${NNPA_INCLUDE_PATH}
   )
 
 add_onnx_mlir_rewriter(ZHighDecomposeStickUnstick)
diff --git a/src/Accelerators/NNPA/Transform/ZHigh/ZHighConstPropagation.cpp b/src/Accelerators/NNPA/Transform/ZHigh/ZHighConstPropagation.cpp
index 62724c1c73..a32bacb4c4 100644
--- a/src/Accelerators/NNPA/Transform/ZHigh/ZHighConstPropagation.cpp
+++ b/src/Accelerators/NNPA/Transform/ZHigh/ZHighConstPropagation.cpp
@@ -21,11 +21,9 @@
 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
 
 #include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps.hpp"
-#include "src/Accelerators/NNPA/Dialect/ZHigh/ZHighOps/OpHelper.hpp"
 #include "src/Accelerators/NNPA/Pass/NNPAPasses.hpp"
 #include "src/Accelerators/NNPA/Support/LayoutHelper.hpp"
 #include "src/Accelerators/NNPA/Support/Stickify/Stickify.hpp"
-#include "src/Compiler/CompilerOptions.hpp"
 #include "src/Dialect/ONNX/ONNXOps.hpp"
 #include "src/Dialect/ONNX/ONNXOps/OpHelper.hpp"
 
@@ -36,6 +34,33 @@ using namespace onnx_mlir::zhigh;
 namespace onnx_mlir {
 namespace zhigh {
 
+/// Get raw data from a dense attribute.
+static void getRawData(DenseElementsAttr denseAttr, std::vector<char> &data) {
+  if (!denseAttr.isSplat()) {
+    data = denseAttr.getRawData();
+  } else {
+    ShapedType denseShapeType = mlir::cast<ShapedType>(denseAttr.getType());
+    std::vector<char> rawData = denseAttr.getRawData();
+    int64_t numElements = denseShapeType.getNumElements();
+    for (int i = 0; i < numElements; i++)
+      data.insert(data.end(), rawData.begin(), rawData.end());
+  }
+}
+
+/// MLIR type to zDNN type.
+zdnn_data_types mlirTypeToZDNNType(Type elementType) {
+  if (mlir::isa<FloatType>(elementType)) {
+    FloatType floatTy = mlir::cast<FloatType>(elementType);
+    if (floatTy.getWidth() == 16) {
+      return FP16;
+    } else if (floatTy.getWidth() == 32) {
+      return FP32;
+    } else
+      llvm_unreachable("Unsupported data type.");
+  } else
+    llvm_unreachable("Unsupported data type.");
+}
+
 /// Emit a ZHighStikifiedConstant using information from a stickified ztensor.
 ZHighStickifiedConstantOp emitZHighStickifiedConstant(PatternRewriter &rewriter,
     Location loc, zdnn_ztensor *ztensor, Type outputType) {
@@ -43,7 +68,6 @@ ZHighStickifiedConstantOp emitZHighStickifiedConstant(PatternRewriter &rewriter,
   // Create a ZHighStickifiedConstantOp.
   ZHighStickifiedConstantOp stickifiedConstant =
       rewriter.create<ZHighStickifiedConstantOp>(loc, outputType,
-          /*stickified=*/rewriter.getBoolAttr(true),
           /*value=*/nullptr,
           /*alignment=*/rewriter.getI64IntegerAttr(4096));
 
@@ -67,44 +91,44 @@ ZHighStickifiedConstantOp createConstantForStick(PatternRewriter &rewriter,
     Value replacingValue, Value input, StringAttr layout) {
   Location loc = replacingValue.getLoc();
   Operation *op = input.getDefiningOp();
+  ArrayRef<int64_t> shape = mlir::cast<ShapedType>(input.getType()).getShape();
+  Type elementType = mlir::cast<ShapedType>(input.getType()).getElementType();
+  int rank = shape.size();
+
   // Read dense attributes.
   DenseElementsAttr dataAttr = mlir::dyn_cast_or_null<mlir::DenseElementsAttr>(
       op->getAttrOfType<::mlir::Attribute>("value"));
   assert(dataAttr && "Attribute is null");
-  // Keep previous implementation about generating stickified data at
-  // ZHighConstPropagationPass. To use this, comment in and set directive "
-  // NNPA_ZHIGH_STICKIFIEDCONST_GEN"
-  //
-  // #ifdef NNPA_ZHIGH_STICKIFIEDCONST_GEN
-  //   // Set stickified data.
-  //   ArrayRef<char> stickifiedData =
-  //       getStickifiedDataOfDenseElemAttr(dataAttr, layout);
-  //   // Create a ZHighStickifiedConstantOp.
-  //   ZHighStickifiedConstantOp constantOp =
-  //       rewriter.create<ZHighStickifiedConstantOp>(loc,
-  //       replacingValue.getType(),
-  //           /*stickified=*/rewriter.getBoolAttr(true),
-  //           /*value=*/nullptr,
-  //           /*alignment=*/rewriter.getI64IntegerAttr(4096));
-  //
-  //   // Use an dense resource attribute to store stickified data.
-  //   // Attribute type: tensor<sizeInBytes x i8>
-  //   DenseResourceElementsAttr valueAttr = DenseUI8ResourceElementsAttr::get(
-  //       RankedTensorType::get({stickifiedData.size()}, rewriter.getI8Type()),
-  //       constantOp.getOperation()
-  //           ->getDialect()
-  //           ->getNamespace(), // use the dialect as the blob "hint"
-  //       HeapAsmResourceBlob::allocateAndCopyWithAlign(
-  //           stickifiedData, alignof(char)));
-  //
-  //   constantOp.setValueAttr(valueAttr);
-  // #else
-  ZHighStickifiedConstantOp constantOp =
-      rewriter.create<ZHighStickifiedConstantOp>(loc, replacingValue.getType(),
-          /*stickified=*/rewriter.getBoolAttr(false),
-          /*value=*/dataAttr,
-          /*alignment=*/rewriter.getI64IntegerAttr(4096));
-  // #endif //  NNPA_ZHIGH_STICKIFIEDCONST_GEN
+  // Read attributes's raw data.
+  std::vector<char> rawData;
+  getRawData(dataAttr, rawData);
+  // assert((rawData.size() == (uint64_t)getMemRefSizeInBytes(input)) &&
+  //        "Data size mismatched");
+
+  // Call stickify.
+  zdnn_tensor_desc pre_tfrmd_desc, tfrmd_desc;
+  // pre-transformed desc.
+  zdnn_data_layouts zDNNLayout =
+      convertLayoutAttrToZDNNDataLayout(rank, layout);
+  // If zDNNLayout is NHWC, we stickify directly from NCHW.
+  if (zDNNLayout == ZDNN_NHWC)
+    zDNNLayout = ZDNN_NCHW;
+  zdnn_data_types zDNNType = mlirTypeToZDNNType(elementType);
+  set_info_pre_transformed_desc(&pre_tfrmd_desc, zDNNLayout, zDNNType, shape);
+  // transformed desc.
+  zdnn_status status = generate_transformed_desc(&pre_tfrmd_desc, &tfrmd_desc);
+  assert(status == ZDNN_OK);
+  // Stick data using the software stickify.
+  zdnn_ztensor ztensor;
+  init_ztensor(&pre_tfrmd_desc, &tfrmd_desc, &ztensor);
+  status = allochelper_ztensor_alloc(&ztensor);
+  assert(status == ZDNN_OK);
+  status = stickify(&ztensor, rawData.data());
+  assert(status == ZDNN_OK);
+  // Emit a constant global in ZHigh dialect.
+  ZHighStickifiedConstantOp constantOp = emitZHighStickifiedConstant(
+      rewriter, loc, &ztensor, replacingValue.getType());
+
   return constantOp;
 }
 
diff --git a/src/Accelerators/NNPA/Transform/ZLow/ZLowDummyOpForMultiDerefPass.cpp b/src/Accelerators/NNPA/Transform/ZLow/ZLowDummyOpForMultiDerefPass.cpp
index c7e8ba9a65..b93a4f7688 100644
--- a/src/Accelerators/NNPA/Transform/ZLow/ZLowDummyOpForMultiDerefPass.cpp
+++ b/src/Accelerators/NNPA/Transform/ZLow/ZLowDummyOpForMultiDerefPass.cpp
@@ -58,7 +58,7 @@ class ZLowDummyOpForMultiDerefPass
               ZLowDialect::getDialectNamespace()) {
             ValueRange operands = op->getOperands();
             llvm::SmallSet<uint64_t, 4> processed;
-            for (int64_t i = 0; i < (int64_t)operands.size() - 1; ++i) {
+            for (uint64_t i = 0; i < operands.size() - 1; ++i) {
               if (processed.contains(i))
                 continue;
               for (uint64_t j = i + 1; j < operands.size(); ++j) {
diff --git a/src/Conversion/KrnlToLLVM/CMakeLists.txt b/src/Conversion/KrnlToLLVM/CMakeLists.txt
index 7a42037e08..92948137be 100644
--- a/src/Conversion/KrnlToLLVM/CMakeLists.txt
+++ b/src/Conversion/KrnlToLLVM/CMakeLists.txt
@@ -2,10 +2,10 @@
 
 add_onnx_mlir_library(OMKrnlToLLVM
   ConvertKrnlToLLVM.cpp
-  KrnlGlobalOpInterface.cpp
   KrnlFindIndex.cpp
   KrnlCall.cpp
   KrnlEntryPoint.cpp
+  KrnlGlobal.cpp
   KrnlInstrument.cpp
   KrnlMemcpy.cpp
   KrnlNone.cpp
@@ -22,7 +22,6 @@ add_onnx_mlir_library(OMKrnlToLLVM
 
   LINK_LIBS PUBLIC
   OMAccelerator
-  OMKrnlGlobalOpInterface
   OMSupport
   MLIRAffineToStandard
   MLIRArithTransforms
diff --git a/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.cpp b/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.cpp
index 709ede3c34..a8d631b2d1 100644
--- a/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.cpp
+++ b/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.cpp
@@ -211,17 +211,6 @@ void populateAffineAndKrnlToLLVMConversion(RewritePatternSet &patterns,
   // Use polynomial approximation for math.{tanh, sin, cos and exp} for better
   // performance.
   populateMathPolynomialApproximationPatterns(patterns);
-  // `arith.maxnumf/arith.minnumf` can be replaced with
-  // `llvm.intr.maxnum/llvm.intr.minnum` by
-  // populateArithToLLVMConversionPatterns, or with `arith.cmpf` and
-  // `arith.select` by populateArithExpandOpsPatterns. Which is applied for
-  // depends on the order in which the pattterns are  applied. Currently, it
-  // should be replaced with `llvm.intr.maxnum/llvm.intr.minnum` because
-  // `arith.cmpf` and `arith.select do not work in float16 on ppc64le and cannot
-  // use SIMD, but currently there is no way to specify the order. From testing,
-  // following two line generates expected replacement We need to consider to
-  // specify the order, but we use this workaround for now.
-  arith::populateArithToLLVMConversionPatterns(typeConverter, patterns);
   arith::populateArithExpandOpsPatterns(patterns);
   populateMathToLLVMConversionPatterns(typeConverter, patterns);
   populateFuncToLLVMConversionPatterns(typeConverter, patterns);
@@ -230,6 +219,7 @@ void populateAffineAndKrnlToLLVMConversion(RewritePatternSet &patterns,
   if (enableParallel) {
     populateOpenMPToLLVMConversionPatterns(typeConverter, patterns);
   }
+  arith::populateArithToLLVMConversionPatterns(typeConverter, patterns);
   cf::populateControlFlowToLLVMConversionPatterns(typeConverter, patterns);
 
   krnl::populateKrnlToLLVMConversion(typeConverter, patterns, ctx,
@@ -475,8 +465,8 @@ bool extractConstantsToFile(ModuleOp &module, std::string filepath,
   // Check constants with thresholds.
   // Do not count constants whose size is <= singleThreshold.
   uint64_t totalSize = 0;
-  SmallVector<KrnlGlobalOpInterface> globalOfInterest;
-  module.walk([&](KrnlGlobalOpInterface op) {
+  SmallVector<KrnlGlobalOp> globalOfInterest;
+  module.walk([&](KrnlGlobalOp op) {
     // Ignore constants that are return values.
     bool isReturnedValue = false;
     for (Operation *user : op.getResult().getUsers()) {
@@ -492,23 +482,22 @@ bool extractConstantsToFile(ModuleOp &module, std::string filepath,
     // For an unknown reason, enabling constants of bool caused segfault in the
     // IBM granite.20B model (The model with KV cache) at 1265 input tokens.
     // See issue https://github.com/onnx/onnx-mlir/issues/2713.
-    if (llvm::cast<MemRefType>(op.getResult().getType())
+    if (llvm::cast<MemRefType>(op->getResult(0).getType())
             .getElementType()
             .isInteger(1))
       return WalkResult::advance();
 
     // Get raw data from DenseElementsAttr or DenseResourceElementsAttr.
-    uint64_t bufferSize = op.getBufferSize();
-    if (bufferSize <= singleThreshold)
+    ArrayRef<char> rawData = getRawData(op);
+    if (rawData.empty())
+      return WalkResult::advance();
+
+    auto valueAttr = mlir::cast<ElementsAttr>(op.getValue().value());
+    if (valueAttr.isSplat() || rawData.size() <= singleThreshold)
       return WalkResult::advance();
 
-    if (op.getValueAttr()) {
-      auto valueAttr = mlir::cast<ElementsAttr>(op.getValue().value());
-      if (valueAttr.isSplat())
-        return WalkResult::advance();
-    }
     globalOfInterest.emplace_back(op);
-    totalSize += bufferSize;
+    totalSize += rawData.size();
     return WalkResult::advance();
   });
   // Do not use file if the total size of satisfied constants is <=
@@ -518,16 +507,15 @@ bool extractConstantsToFile(ModuleOp &module, std::string filepath,
 
   // Sort constants in the non-descending order of alignment values.
   // Non-alignment is the smallest value (-1), the others are positive.
-  llvm::sort(globalOfInterest,
-      [&](KrnlGlobalOpInterface left, KrnlGlobalOpInterface right) {
-        int64_t leftAlign = -1;
-        int64_t rightAlign = -1;
-        if (left.getAlignment().has_value())
-          leftAlign = left.getAlignment().value();
-        if (right.getAlignment().has_value())
-          rightAlign = right.getAlignment().value();
-        return (leftAlign < rightAlign);
-      });
+  llvm::sort(globalOfInterest, [&](KrnlGlobalOp left, KrnlGlobalOp right) {
+    int64_t leftAlign = -1;
+    int64_t rightAlign = -1;
+    if (left.getAlignment().has_value())
+      leftAlign = left.getAlignment().value();
+    if (right.getAlignment().has_value())
+      rightAlign = right.getAlignment().value();
+    return (leftAlign < rightAlign);
+  });
 
   // Store each constant into single file.
   // Constants with the highest alignment will be packed first in the file.
@@ -537,8 +525,8 @@ bool extractConstantsToFile(ModuleOp &module, std::string filepath,
   std::ofstream outfile(filepath, std::ios::app | std::ios::binary);
   uint64_t totalConstSize = 0;
   for (int64_t i = globalOfInterest.size() - 1; i >= 0; --i) {
-    KrnlGlobalOpInterface op = globalOfInterest[i];
-    ArrayRef<char> rawData = op.getBuffer();
+    KrnlGlobalOp op = globalOfInterest[i];
+    ArrayRef<char> rawData = getRawData(op);
 
     // Get alignment.
     int64_t alignment = -1;
@@ -556,11 +544,11 @@ bool extractConstantsToFile(ModuleOp &module, std::string filepath,
     }
 
     op.setOffsetAttr(b.getI64IntegerAttr(totalConstSize));
+    op.removeValueAttr();
     outfile.write(rawData.data(), rawData.size());
     totalConstSize += rawData.size();
-    op.removeValueAttr();
-    op.freeBuffer(rawData);
   }
+
   // No constant statisfying thresholds, do not store constants to file.
   if (totalConstSize == 0)
     return false;
@@ -972,8 +960,7 @@ void populateKrnlToLLVMConversion(LLVMTypeConverter &typeConverter,
       verifyInputTensors);
   krnl::populateLoweringKrnlCallOpPattern(typeConverter, patterns, ctx);
   krnl::populateLoweringKrnlFindIndexOpPattern(typeConverter, patterns, ctx);
-  krnl::populateLoweringKrnlGlobalOpInterfacePattern(
-      typeConverter, patterns, ctx);
+  krnl::populateLoweringKrnlGlobalOpPattern(typeConverter, patterns, ctx);
   krnl::populateLoweringKrnlInstrumentOpPattern(typeConverter, patterns, ctx);
   krnl::populateLoweringKrnlMemcpyOpPattern(typeConverter, patterns, ctx);
   krnl::populateLoweringKrnlPrintOpPattern(typeConverter, patterns, ctx);
diff --git a/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.hpp b/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.hpp
index ed5258516e..2309871db4 100644
--- a/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.hpp
+++ b/src/Conversion/KrnlToLLVM/ConvertKrnlToLLVM.hpp
@@ -68,9 +68,8 @@ void populateLoweringKrnlFindIndexOpPattern(
     mlir::LLVMTypeConverter &typeConverter, mlir::RewritePatternSet &patterns,
     mlir::MLIRContext *ctx);
 
-void populateLoweringKrnlGlobalOpInterfacePattern(
-    mlir::LLVMTypeConverter &typeConverter, mlir::RewritePatternSet &patterns,
-    mlir::MLIRContext *ctx);
+void populateLoweringKrnlGlobalOpPattern(mlir::LLVMTypeConverter &typeConverter,
+    mlir::RewritePatternSet &patterns, mlir::MLIRContext *ctx);
 
 void populateLoweringKrnlInstrumentOpPattern(
     mlir::LLVMTypeConverter &typeConverter, mlir::RewritePatternSet &patterns,
diff --git a/src/Conversion/KrnlToLLVM/KrnlGlobalOpInterface.cpp b/src/Conversion/KrnlToLLVM/KrnlGlobal.cpp
similarity index 66%
rename from src/Conversion/KrnlToLLVM/KrnlGlobalOpInterface.cpp
rename to src/Conversion/KrnlToLLVM/KrnlGlobal.cpp
index 1e579f5595..1c13787ac0 100644
--- a/src/Conversion/KrnlToLLVM/KrnlGlobalOpInterface.cpp
+++ b/src/Conversion/KrnlToLLVM/KrnlGlobal.cpp
@@ -2,13 +2,13 @@
  * SPDX-License-Identifier: Apache-2.0
  */
 
-//===------ KrnlGlobalOpInterface.cpp - Lower KrnlGlobalOpInterface -------===//
+//===------ KrnlGlobal.cpp - Lower KrnlGlobalOp ---------------------------===//
 //
-// Copyright 2019-2024 The IBM Research Authors.
+// Copyright 2019-2022 The IBM Research Authors.
 //
 // =============================================================================
 //
-// This file lowers the KrnlGlobalOpInterface.
+// This file lowers the KrnlGlobalOp operator.
 //
 //===----------------------------------------------------------------------===//
 
@@ -35,39 +35,33 @@ namespace krnl {
 /// This variable is initizalied inside ConvertKrnlToLLVMPass.
 extern std::string EXTERNAL_CONSTANT_PREFIX;
 
-class KrnlGlobalOpInterfaceLowering
-    : public OpInterfaceConversionPattern<KrnlGlobalOpInterface> {
-
+class KrnlGlobalOpLowering : public ConvertToLLVMPattern {
 public:
-  using OpInterfaceConversionPattern<
-      KrnlGlobalOpInterface>::OpInterfaceConversionPattern;
-
-  explicit KrnlGlobalOpInterfaceLowering(
+  explicit KrnlGlobalOpLowering(
       LLVMTypeConverter &typeConverter, MLIRContext *context)
-      : OpInterfaceConversionPattern(typeConverter, context) {}
+      : ConvertToLLVMPattern(
+            KrnlGlobalOp::getOperationName(), context, typeConverter) {}
 
-  LogicalResult matchAndRewrite(KrnlGlobalOpInterface op,
-      ArrayRef<Value> operands,
+  LogicalResult matchAndRewrite(Operation *op, ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const override {
-    Location loc = op->getLoc();
-    MLIRContext *context = op->getContext();
+    auto krnlGlobalOp = llvm::dyn_cast<KrnlGlobalOp>(op);
+    Location loc = krnlGlobalOp.getLoc();
+    MLIRContext *context = krnlGlobalOp.getContext();
     MultiDialectBuilder<LLVMBuilder> create(rewriter, loc);
-    const LLVMTypeConverter *llvmTypeConverter =
-        static_cast<const LLVMTypeConverter *>(getTypeConverter());
 
     // Basic type.
     Type llvmI8Ty = IntegerType::get(context, 8);
     Type llvmI8PtrTy = getPointerType(context, llvmI8Ty);
 
     // The element type of the array.
-    const Type type = op.getResult().getType();
+    const Type type = op->getResult(0).getType();
     const MemRefType memRefTy = mlir::cast<mlir::MemRefType>(type);
     const Type constantElementType =
-        llvmTypeConverter->convertType(memRefTy.getElementType());
+        typeConverter->convertType(memRefTy.getElementType());
     Type globalType = constantElementType;
 
     // The llvm type of the global (example: [2 x [8 x float]]).
-    const auto shape = mlir::dyn_cast<ArrayAttr>(op.getShape());
+    const auto shape = mlir::dyn_cast<ArrayAttr>(krnlGlobalOp.getShape());
     if (shape.empty())
       globalType = LLVM::LLVMArrayType::get(mlir::cast<Type>(globalType), 1);
     else {
@@ -80,17 +74,16 @@ class KrnlGlobalOpInterfaceLowering
     LLVM::GlobalOp global;
     // Pointer to the raw data of the global.
     Value dataPtr;
-    // Update value attribute if needed.
-    op.updateValueAttr();
 
-    if (op.getValue().has_value()) {
-      auto value = op.getValue().value();
+    if (krnlGlobalOp.getValue().has_value()) {
+      auto value = krnlGlobalOp.getValue().value();
       TypeSwitch<Attribute>(value)
           .Case<DenseResourceElementsAttr>([&](DenseResourceElementsAttr attr) {
-            global = lowerDenseResourceConstant(op, globalType, rewriter);
+            global =
+                lowerDenseResourceConstant(krnlGlobalOp, globalType, rewriter);
           })
           .Case<DenseElementsAttr>([&](DenseElementsAttr attr) {
-            global = lowerDenseConstant(op, globalType, rewriter);
+            global = lowerDenseConstant(krnlGlobalOp, globalType, rewriter);
           })
           .Default([&](Attribute attr) {
             llvm_unreachable("Unsupported attribute type");
@@ -98,14 +91,15 @@ class KrnlGlobalOpInterfaceLowering
       dataPtr = create.llvm.addressOf(global);
     } else {
       // Data are stored on files.
-      global = lowerGlobalOpWithExternalFiles(op, rewriter);
+      global = lowerGlobalOpWithExternalFiles(krnlGlobalOp, rewriter);
       dataPtr = create.llvm.load(llvmI8PtrTy, create.llvm.addressOf(global));
     }
 
     // Set the global alignment based on the alignment attribute if it exists,
     // otherwise use the module datalayout info.
-    krnl::setAlignment(global, op.getAlignmentAttr(),
-        op->getParentOfType<ModuleOp>(), rewriter, *llvmTypeConverter);
+    krnl::setAlignment(global, krnlGlobalOp.getAlignmentAttr(),
+        krnlGlobalOp->getParentOfType<ModuleOp>(), rewriter,
+        *getTypeConverter());
 
     // Prepare data to be inserted into a MemRefDescriptor (a struct).
     MemRefDescriptor memRefDescr =
@@ -121,32 +115,31 @@ class KrnlGlobalOpInterfaceLowering
     return mlir::cast<IntegerAttr>(a.getValue()[i]).getInt();
   }
 
-  LLVM::GlobalOp lowerDenseResourceConstant(
-      KrnlGlobalOpInterface &globalOpInterface, Type globalType,
-      ConversionPatternRewriter &rewriter) const {
-    assert(globalOpInterface.getValue().has_value() &&
-           "Expecting KrnlGlobalOpInterface with a valid value");
-    assert(mlir::isa<DenseResourceElementsAttr>(
-               globalOpInterface.getValue().value()) &&
-           "Expecting a global with an dense resource elements attribute");
-
-    MLIRContext *context = globalOpInterface.getContext();
-    Location loc = globalOpInterface.getLoc();
-    ModuleOp module = globalOpInterface->getParentOfType<ModuleOp>();
+  LLVM::GlobalOp lowerDenseResourceConstant(KrnlGlobalOp &krnlGlobalOp,
+      Type globalType, ConversionPatternRewriter &rewriter) const {
+    assert(krnlGlobalOp.getValue().has_value() &&
+           "Expecting KrnlGlobalOp with a valid value");
+    assert(
+        mlir::isa<DenseResourceElementsAttr>(krnlGlobalOp.getValue().value()) &&
+        "Expecting a global with an dense resource elements attribute");
+
+    MLIRContext *context = krnlGlobalOp.getContext();
+    Location loc = krnlGlobalOp.getLoc();
+    ModuleOp module = krnlGlobalOp->getParentOfType<ModuleOp>();
     MultiDialectBuilder<LLVMBuilder> create(rewriter, loc);
 
     OpBuilder::InsertionGuard insertGuard(rewriter);
     rewriter.setInsertionPointToStart(module.getBody());
 
-    auto blob = mlir::cast<DenseResourceElementsAttr>(
-        globalOpInterface.getValue().value())
-                    .getRawHandle()
-                    .getBlob();
+    auto blob =
+        mlir::cast<DenseResourceElementsAttr>(krnlGlobalOp.getValue().value())
+            .getRawHandle()
+            .getBlob();
     assert(blob && "Expecting dense resource with a valid blob");
     ArrayRef<char> rawData = blob->getData();
 
     // Check data size.
-    uint64_t sizeInBytes = computeSizeInBytes(globalOpInterface);
+    uint64_t sizeInBytes = computeSizeInBytes(krnlGlobalOp);
     assert(((uint64_t)rawData.size() == sizeInBytes) && "Data size mismatch.");
 
     StringRef data(rawData.data(), rawData.size());
@@ -154,23 +147,23 @@ class KrnlGlobalOpInterfaceLowering
     auto llvmArrayI8Ty =
         LLVM::LLVMArrayType::get(IntegerType::get(context, 8), sizeInBytes);
     LLVM::GlobalOp global = create.llvm.globalOp(llvmArrayI8Ty,
-        /*isConstant=*/true, LLVM::Linkage::Internal,
-        globalOpInterface.getName(), llvmStringAttr);
+        /*isConstant=*/true, LLVM::Linkage::Internal, krnlGlobalOp.getName(),
+        llvmStringAttr);
 
     LLVM_DEBUG(llvm::dbgs() << "global: " << global << "\n";);
     return global;
   }
 
-  LLVM::GlobalOp lowerDenseConstant(KrnlGlobalOpInterface &globalOpInterface,
-      Type globalType, ConversionPatternRewriter &rewriter) const {
-    assert(globalOpInterface.getValue().has_value() &&
-           "Expecting KrnlGlobalOpInterface with a valid value");
-    assert(mlir::isa<DenseElementsAttr>(globalOpInterface.getValue().value()) &&
+  LLVM::GlobalOp lowerDenseConstant(KrnlGlobalOp &krnlGlobalOp, Type globalType,
+      ConversionPatternRewriter &rewriter) const {
+    assert(krnlGlobalOp.getValue().has_value() &&
+           "Expecting KrnlGlobalOp with a valid value");
+    assert(mlir::isa<DenseElementsAttr>(krnlGlobalOp.getValue().value()) &&
            "Expecting a global with an dense elements attribute");
 
-    Location loc = globalOpInterface.getLoc();
-    ModuleOp module = globalOpInterface->getParentOfType<ModuleOp>();
-    MLIRContext *context = globalOpInterface.getContext();
+    Location loc = krnlGlobalOp.getLoc();
+    ModuleOp module = krnlGlobalOp->getParentOfType<ModuleOp>();
+    MLIRContext *context = krnlGlobalOp.getContext();
     MultiDialectBuilder<LLVMBuilder> create(rewriter, loc);
 
     Type llvmI8Ty = IntegerType::get(context, 8);
@@ -179,9 +172,9 @@ class KrnlGlobalOpInterfaceLowering
     rewriter.setInsertionPointToStart(module.getBody());
 
     DenseElementsAttr denseAttr =
-        mlir::cast<DenseElementsAttr>(globalOpInterface.getValue().value());
+        mlir::cast<DenseElementsAttr>(krnlGlobalOp.getValue().value());
 
-    uint64_t sizeInBytes = computeSizeInBytes(globalOpInterface);
+    uint64_t sizeInBytes = computeSizeInBytes(krnlGlobalOp);
     LLVM::GlobalOp global;
     if (!(mlir::isa<StringType>(denseAttr.getElementType())) &&
         !(denseAttr.getElementType().isInteger(1)) && (!denseAttr.isSplat()) &&
@@ -195,15 +188,15 @@ class KrnlGlobalOpInterfaceLowering
       StringRef data(rawData.data(), rawData.size());
       StringAttr llvmStringAttr = StringAttr::get(context, data);
       global = create.llvm.globalOp(llvmArrayI8Ty,
-          /*isConstant=*/true, LLVM::Linkage::Internal,
-          globalOpInterface.getName(), llvmStringAttr);
+          /*isConstant=*/true, LLVM::Linkage::Internal, krnlGlobalOp.getName(),
+          llvmStringAttr);
     } else {
       if (mlir::isa<StringType>(denseAttr.getElementType()))
-        global = lowerStringLiteral(globalOpInterface, globalType, rewriter);
+        global = lowerStringLiteral(krnlGlobalOp, globalType, rewriter);
       else
         global = create.llvm.globalOp(globalType,
             /*isConstant=*/true, LLVM::Linkage::Internal,
-            globalOpInterface.getName(), globalOpInterface.getValue().value());
+            krnlGlobalOp.getName(), krnlGlobalOp.getValue().value());
     }
 
     LLVM_DEBUG(llvm::dbgs() << "global: " << global << "\n";);
@@ -211,24 +204,21 @@ class KrnlGlobalOpInterfaceLowering
   }
 
   LLVM::GlobalOp lowerGlobalOpWithExternalFiles(
-      KrnlGlobalOpInterface &globalOpInterface,
-      ConversionPatternRewriter &rewriter) const {
-    Location loc = globalOpInterface.getLoc();
-    MLIRContext *context = globalOpInterface.getContext();
-    ModuleOp module =
-        globalOpInterface.getOperation()->getParentOfType<ModuleOp>();
+      KrnlGlobalOp &krnlGlobalOp, ConversionPatternRewriter &rewriter) const {
+    Location loc = krnlGlobalOp.getLoc();
+    MLIRContext *context = krnlGlobalOp.getContext();
+    ModuleOp module = krnlGlobalOp.getOperation()->getParentOfType<ModuleOp>();
     MultiDialectBuilder<LLVMBuilder> create(rewriter, loc);
 
     Type llvmI8Ty = IntegerType::get(context, 8);
     Type llvmI8PtrTy = getPointerType(context, llvmI8Ty);
     Type llvmI64Ty = IntegerType::get(context, 64);
 
-    auto offset = globalOpInterface.getOffset();
-    assert(
-        offset.has_value() && "Missing offset value in KrnlGlobalOpInterface");
+    auto offset = krnlGlobalOp.getOffset();
+    assert(offset.has_value() && "Missing offset value in KrnlGlobalOp");
 
     // Data is store in `constants.bin` at offset.
-    std::string constantName = globalOpInterface.getName().str();
+    std::string constantName = krnlGlobalOp.getName().str();
 
     // Emit globals at the begining of the module.
     OpBuilder::InsertionGuard insertGuard(rewriter);
@@ -256,14 +246,14 @@ class KrnlGlobalOpInterfaceLowering
     return global;
   }
 
-  uint64_t computeSizeInBytes(KrnlGlobalOpInterface &globalOpInterface) const {
+  uint64_t computeSizeInBytes(KrnlGlobalOp &krnlGlobalOp) const {
     // Compute total number of elements.
-    const auto shape = mlir::dyn_cast<ArrayAttr>(globalOpInterface.getShape());
+    const auto shape = mlir::dyn_cast<ArrayAttr>(krnlGlobalOp.getShape());
     uint64_t numElements = 1;
     for (unsigned int i = 0; i < shape.size(); ++i)
       numElements *= ArrayAttrIntVal(shape, i);
 
-    const auto type = globalOpInterface.getResult().getType();
+    const auto type = krnlGlobalOp.getResult().getType();
     const auto memRefTy = mlir::cast<mlir::MemRefType>(type);
 
     // Special handling for bool.
@@ -277,9 +267,8 @@ class KrnlGlobalOpInterfaceLowering
   MemRefDescriptor createMemRefDescriptor(Value address, MemRefType memRefType,
       Location loc, OpBuilder &builder) const {
     Type elementType = memRefType.getElementType();
-    const LLVMTypeConverter *llvmTypeConverter =
-        static_cast<const LLVMTypeConverter *>(getTypeConverter());
-    Type llvmElemType = llvmTypeConverter->convertType(elementType);
+    const LLVMTypeConverter &typeConverter = *getTypeConverter();
+    Type llvmElemType = typeConverter.convertType(elementType);
     MLIRContext *context = builder.getContext();
     MultiDialectBuilder<LLVMBuilder> create(builder, loc);
 
@@ -289,21 +278,21 @@ class KrnlGlobalOpInterfaceLowering
     Value bitCastOp = create.llvm.bitcast(ptrType, address);
     // Create llvm MemRef from original MemRef and fill the data pointers.
     return MemRefDescriptor::fromStaticShape(
-        builder, loc, *llvmTypeConverter, memRefType, bitCastOp);
+        builder, loc, typeConverter, memRefType, bitCastOp);
   }
 
-  // Generate a global string for each globalOpInterface string value, and store
+  // Generate a global string for each krnlGlobalOp string value, and store
   // the address of the global strings into an array. Return the array address.
-  LLVM::GlobalOp lowerStringLiteral(KrnlGlobalOpInterface &globalOpInterface,
-      Type globalType, OpBuilder &builder) const {
-    assert(mlir::isa<DenseElementsAttr>(globalOpInterface.getValue().value()) &&
+  LLVM::GlobalOp lowerStringLiteral(
+      KrnlGlobalOp &krnlGlobalOp, Type globalType, OpBuilder &builder) const {
+    assert(mlir::isa<DenseElementsAttr>(krnlGlobalOp.getValue().value()) &&
            "Expecting a dense value");
 
-    Location loc = globalOpInterface.getLoc();
+    Location loc = krnlGlobalOp.getLoc();
     MultiDialectBuilder<LLVMBuilder> create(builder, loc);
 
     DenseElementsAttr denseAttr =
-        mlir::cast<DenseElementsAttr>(globalOpInterface.getValue().value());
+        mlir::cast<DenseElementsAttr>(krnlGlobalOp.getValue().value());
 
     Type i8PtrType = getI8PointerType(builder.getContext());
 
@@ -333,14 +322,14 @@ class KrnlGlobalOpInterfaceLowering
     auto llvmArrayI8Ty = LLVM::LLVMArrayType::get(i8Type, totalSize);
     LLVM::GlobalOp globalStr = create.llvm.globalOp(llvmArrayI8Ty,
         /*isConstant=*/true, LLVM::Linkage::Internal,
-        "om.strArray." + globalOpInterface.getName().str(), llvmStringAttr);
+        "om.strArray." + krnlGlobalOp.getName().str(), llvmStringAttr);
 
     // Generate an LLVM GlobalOps with an initializer region containing one
     // block.
     auto arrayType = LLVM::LLVMArrayType::get(i8PtrType, offsets.size());
     auto global = create.llvm.globalOp(arrayType,
-        /*isConstant=*/true, LLVM::Linkage::Internal,
-        globalOpInterface.getName(), Attribute());
+        /*isConstant=*/true, LLVM::Linkage::Internal, krnlGlobalOp.getName(),
+        Attribute());
     Region &region = global.getInitializerRegion();
     Block *block = builder.createBlock(&region);
 
@@ -366,10 +355,9 @@ class KrnlGlobalOpInterfaceLowering
   }
 };
 
-void populateLoweringKrnlGlobalOpInterfacePattern(
-    LLVMTypeConverter &typeConverter, RewritePatternSet &patterns,
-    MLIRContext *ctx) {
-  patterns.insert<KrnlGlobalOpInterfaceLowering>(typeConverter, ctx);
+void populateLoweringKrnlGlobalOpPattern(LLVMTypeConverter &typeConverter,
+    RewritePatternSet &patterns, MLIRContext *ctx) {
+  patterns.insert<KrnlGlobalOpLowering>(typeConverter, ctx);
 }
 
 } // namespace krnl
diff --git a/src/Dialect/Krnl/CMakeLists.txt b/src/Dialect/Krnl/CMakeLists.txt
index c3c7bf8991..683e4500dc 100644
--- a/src/Dialect/Krnl/CMakeLists.txt
+++ b/src/Dialect/Krnl/CMakeLists.txt
@@ -18,7 +18,6 @@ add_onnx_mlir_library(OMKrnlOps
   DEPENDS
   OMKrnlIncGen
   OMSpecializedKernelOpInterface
-  OMKrnlGlobalOpInterface
 
   LINK_LIBS PUBLIC
   OMCompilerOptions
diff --git a/src/Dialect/Krnl/Krnl.td b/src/Dialect/Krnl/Krnl.td
index 1d5a015d29..c8220dfc53 100644
--- a/src/Dialect/Krnl/Krnl.td
+++ b/src/Dialect/Krnl/Krnl.td
@@ -27,7 +27,6 @@ include "mlir/Interfaces/SideEffectInterfaces.td"
 include "mlir/Interfaces/ViewLikeInterface.td"
 include "mlir/Dialect/Affine/IR/AffineMemoryOpInterfaces.td"
 include "src/Interface/SpecializedKernelOpInterface.td"
-include "src/Interface/KrnlGlobalOpInterface.td"
 
 def Krnl_Dialect : Dialect {
   let name = "krnl";
@@ -407,8 +406,7 @@ def KrnlMemcpyOp : Op<Krnl_Dialect, "memcpy", [MemRefsNormalizable,
                        Index:$dest_offset, Index:$src_offset);
 }
 
-def KrnlGlobalOp : Op<Krnl_Dialect, "global", [Pure,
-    DeclareOpInterfaceMethods<KrnlGlobalOpInterface>, MemRefsNormalizable]> {
+def KrnlGlobalOp : Op<Krnl_Dialect, "global", [Pure, MemRefsNormalizable]> {
   let summary = "Krnl global operation";
   let description = [{
     Operation for holding global data values. A global constant can have a
diff --git a/src/Dialect/Krnl/KrnlOps.cpp b/src/Dialect/Krnl/KrnlOps.cpp
index bdcf2bffba..cec7b2d94d 100644
--- a/src/Dialect/Krnl/KrnlOps.cpp
+++ b/src/Dialect/Krnl/KrnlOps.cpp
@@ -12,14 +12,12 @@
 //
 //===----------------------------------------------------------------------===//
 
-#include "mlir/Dialect/Affine/Analysis/Utils.h"
 #include "mlir/Dialect/Bufferization/IR/Bufferization.h"
 #include "mlir/Dialect/Linalg/IR/Linalg.h"
 #include "mlir/Dialect/Math/IR/Math.h"
 #include "mlir/Dialect/SCF/IR/SCF.h"
 #include "mlir/Dialect/Shape/IR/Shape.h"
 #include "mlir/IR/DialectImplementation.h"
-#include "mlir/IR/DialectResourceBlobManager.h"
 #include "llvm/ADT/TypeSwitch.h"
 
 #include "mlir/IR/Value.h"
@@ -814,34 +812,6 @@ MutableOperandRange KrnlSpecializedKernel::getLoopRefs() {
   return getLoopsMutable();
 }
 
-ArrayRef<char> KrnlGlobalOp::getBuffer() {
-  ArrayRef<char> ret;
-  std::vector<char> attrData;
-  if (getValueAttr()) {
-    int64_t sizeInBytes = getBufferSize();
-    char *rawData = (char *)malloc(sizeInBytes);
-    auto valueAttr = getValue().value();
-    getRawData(valueAttr, attrData);
-    memcpy(rawData, attrData.data(), sizeInBytes);
-    ret = llvm::ArrayRef(rawData, sizeInBytes);
-  }
-  return ret;
-}
-
-uint64_t KrnlGlobalOp::getBufferSize() {
-  const Type type = getOperation()->getResults()[0].getType();
-  const MemRefType memRefTy = mlir::cast<mlir::MemRefType>(type);
-  auto sizeInBytes = affine::getIntOrFloatMemRefSizeInBytes(memRefTy);
-  return sizeInBytes.has_value() ? sizeInBytes.value() : 0;
-}
-
-void KrnlGlobalOp::freeBuffer(ArrayRef<char> rawData) {
-  free(const_cast<char *>(rawData.data()));
-  return;
-}
-
-void KrnlGlobalOp::updateValueAttr() {}
-
 //===----------------------------------------------------------------------===//
 // KrnlMatMulOp
 //===----------------------------------------------------------------------===//
diff --git a/src/Dialect/Krnl/KrnlOps.hpp b/src/Dialect/Krnl/KrnlOps.hpp
index fcf48a395d..661fa7576d 100644
--- a/src/Dialect/Krnl/KrnlOps.hpp
+++ b/src/Dialect/Krnl/KrnlOps.hpp
@@ -21,7 +21,6 @@
 
 #include "src/Dialect/Krnl/KrnlHelper.hpp"
 #include "src/Dialect/Krnl/KrnlTypes.hpp"
-#include "src/Interface/KrnlGlobalOpInterface.hpp"
 #include "src/Interface/SpecializedKernelOpInterface.hpp"
 
 #include "src/Dialect/Krnl/KrnlDialect.hpp.inc"
diff --git a/src/Dialect/ONNX/ONNXOps/OpHelper.cpp b/src/Dialect/ONNX/ONNXOps/OpHelper.cpp
index 72479a53ab..520de56339 100644
--- a/src/Dialect/ONNX/ONNXOps/OpHelper.cpp
+++ b/src/Dialect/ONNX/ONNXOps/OpHelper.cpp
@@ -12,7 +12,6 @@
 //
 //===----------------------------------------------------------------------===//
 
-#include "mlir/IR/DialectResourceBlobManager.h"
 #include "mlir/IR/TypeUtilities.h"
 #include "llvm/ADT/TypeSwitch.h"
 #include "llvm/Support/Path.h"
@@ -753,29 +752,6 @@ bool hasIntegerPowerExponent(ONNXPowOp *op, int64_t &exponentValue) {
   return false;
 }
 
-/// Get raw data from a dense attribute.
-void getRawData(Attribute dataAttr, std::vector<char> &data) {
-  TypeSwitch<Attribute>(dataAttr)
-      .Case<DenseElementsAttr>([&](DenseElementsAttr denseAttr) {
-        if (!denseAttr.isSplat()) {
-          data = denseAttr.getRawData();
-        } else {
-          ShapedType denseShapeType =
-              mlir::cast<ShapedType>(denseAttr.getType());
-          std::vector<char> rawData = denseAttr.getRawData();
-          int64_t numElements = denseShapeType.getNumElements();
-          for (int i = 0; i < numElements; i++)
-            data.insert(data.end(), rawData.begin(), rawData.end());
-        }
-      })
-      .Case<DenseResourceElementsAttr>(
-          [&](DenseResourceElementsAttr denseResourceAttr) {
-            data = denseResourceAttr.getRawHandle().getBlob()->getData();
-          })
-      .Default(
-          [&](Attribute attr) { llvm_unreachable("Unsupported data type."); });
-}
-
 //===----------------------------------------------------------------------===//
 // Support for ReshapeOp.
 //===----------------------------------------------------------------------===//
diff --git a/src/Dialect/ONNX/ONNXOps/OpHelper.hpp b/src/Dialect/ONNX/ONNXOps/OpHelper.hpp
index 278a454313..b084ad5cd6 100644
--- a/src/Dialect/ONNX/ONNXOps/OpHelper.hpp
+++ b/src/Dialect/ONNX/ONNXOps/OpHelper.hpp
@@ -261,9 +261,6 @@ bool isScalarTensor(mlir::Value v);
 
 bool hasIntegerPowerExponent(mlir::ONNXPowOp *op, int64_t &exponentValue);
 
-/// Get raw data from a dense attribute.
-void getRawData(mlir::Attribute dataAttr, std::vector<char> &data);
-
 //===----------------------------------------------------------------------===//
 // Support for dim operations.
 //===----------------------------------------------------------------------===//
diff --git a/src/Interface/CMakeLists.txt b/src/Interface/CMakeLists.txt
index 21b76d0f31..07a1eb6873 100644
--- a/src/Interface/CMakeLists.txt
+++ b/src/Interface/CMakeLists.txt
@@ -5,7 +5,6 @@ add_onnx_mlir_interface(ShapeHelperOpInterface)
 add_onnx_mlir_interface(ResultTypeInferenceOpInterface)
 add_onnx_mlir_interface(HasOnnxSubgraphOpInterface)
 add_onnx_mlir_interface(SpecializedKernelOpInterface)
-add_onnx_mlir_interface(KrnlGlobalOpInterface)
 
 add_onnx_mlir_library(OMShapeInferenceOpInterface
   ShapeInferenceOpInterface.cpp
@@ -62,14 +61,3 @@ add_onnx_mlir_library(OMSpecializedKernelOpInterface
   MLIRIR
   LLVMSupport
   )
-
-add_onnx_mlir_library(OMKrnlGlobalOpInterface
-  KrnlGlobalOpInterface.cpp
-
-  DEPENDS
-  OMKrnlGlobalOpInterfaceIncGen
-
-  LINK_LIBS PUBLIC
-  MLIRIR
-  LLVMSupport
-  )
diff --git a/src/Interface/KrnlGlobalOpInterface.cpp b/src/Interface/KrnlGlobalOpInterface.cpp
deleted file mode 100644
index f54c6222c6..0000000000
--- a/src/Interface/KrnlGlobalOpInterface.cpp
+++ /dev/null
@@ -1,24 +0,0 @@
-/*
- * SPDX-License-Identifier: Apache-2.0
- */
-
-//===-------------------- KrnlGlobalOpInterface.cpp -----------------------===//
-//===---------------- KrnlGlobalOp Interface Definition -------------------===//
-//
-// Copyright 2024 The IBM Research Authors.
-//
-// =============================================================================
-//
-// This file contains the definition of the Constant Op Interface.
-//
-//===----------------------------------------------------------------------===//
-
-#include "KrnlGlobalOpInterface.hpp"
-
-using namespace mlir;
-
-//===----------------------------------------------------------------------===//
-// KrnlGlobal Op Interface
-//===----------------------------------------------------------------------===//
-
-#include "src/Interface/KrnlGlobalOpInterface.cpp.inc"
diff --git a/src/Interface/KrnlGlobalOpInterface.hpp b/src/Interface/KrnlGlobalOpInterface.hpp
deleted file mode 100644
index c9adafca14..0000000000
--- a/src/Interface/KrnlGlobalOpInterface.hpp
+++ /dev/null
@@ -1,27 +0,0 @@
-/*
- * SPDX-License-Identifier: Apache-2.0
- */
-
-//===-------------------- KrnlGlobalOpInterfaceo.hpp ----------------------===//
-//===---------------- KrnlGlobal Op Interface Definition ------------------===//
-//
-// Copyright 2024 The IBM Research Authors.
-//
-// =============================================================================
-//
-// This file contains the definition of the KrnlGlobal Op Interface.
-//
-//===----------------------------------------------------------------------===//
-
-#ifndef ONNX_MLIR_KRNLGLOBALOP_INTERFACE_H
-#define ONNX_MLIR_KRNLGLOBALOP_INTERFACE_H
-
-#include <map>
-#include <string>
-
-#include "mlir/IR/OpDefinition.h"
-
-/// Include the auto-generated declarations.
-#include "src/Interface/KrnlGlobalOpInterface.hpp.inc"
-
-#endif
diff --git a/src/Interface/KrnlGlobalOpInterface.td b/src/Interface/KrnlGlobalOpInterface.td
deleted file mode 100644
index 71e2c1a918..0000000000
--- a/src/Interface/KrnlGlobalOpInterface.td
+++ /dev/null
@@ -1,88 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-
-//===-------------------- KrnlGlobalOpInterface.hpp -----------------------===//
-//===---------------- KrnlGlobal Op Interface Definition ------------------===//
-//
-// Copyright 2024 The IBM Research Authors.
-//
-// =============================================================================
-//
-// This file contains the TableGen definition of the Constant Op
-// Interface Definition.
-//
-//===----------------------------------------------------------------------===//
-
-#ifdef KRNLGLOBAL_OP_INTERFACE
-#else
-#define KRNLGLOBAL_OP_INTERFACE
-
-include "mlir/IR/OpBase.td"
-
-def KrnlGlobalOpInterface : OpInterface<"KrnlGlobalOpInterface"> {
-  let description = [{
-    A KrnlGlobalOp-like operation is one that holds global constant value. It has
-    `name` attribute, `shape` attribute, `offset` attribute, and `alighnment`
-    attribute. Its content is stored in the `value` attribute, which can be
-    converted when retrieving.
-  }];
-
-  let methods = [
-      InterfaceMethod<"Get the buffer for the constant value from value attribute. "
-                      "If conversions are required to get the buffer. It should be "
-		      "done in this method. The constant value is stored in newly  "
-		      "allocated buffer. The buffer needs to be freed afte use by  "
-		      "using `freeBuffer()`.",
-          "::mlir::ArrayRef<char>", "getBuffer", (ins )
-      >,
-      InterfaceMethod<"Get the size of the buffer. ",
-          "uint64_t", "getBufferSize", (ins )
-      >,
-      InterfaceMethod<"Free the buffer for the constant value retrieved from value "
-                      "attribute.",
-          "void", "freeBuffer", (ins "::mlir::ArrayRef<char>": $buffer)
-      >,
-      InterfaceMethod<"Update the `value` attribute by converting existing `value` "
-                       "attribute. Assume to use getBuffer(), setValueAttr(), and  "
-		       "freeBuffer() in this function.",
-          "void", "updateValueAttr", (ins )
-      >,
-      InterfaceMethod<"Get the value from the attribute.",
-          "std::optional<Attribute>", "getValue", (ins )
-      >,
-      InterfaceMethod<"Get the `value` attribute.",
-          "Attribute", "getValueAttr", (ins )
-      >,
-      InterfaceMethod<"Remove value attribute.",
-          "Attribute", "removeValueAttr", (ins )
-      >,
-      InterfaceMethod<"Get the `alignment` attribute.",
-          "std::optional<uint64_t>", "getAlignment", (ins )
-      >,
-      InterfaceMethod<"Get the attribute for the alignment.",
-          "IntegerAttr", "getAlignmentAttr", (ins )
-      >,
-      InterfaceMethod<"Get the `shape` attribute.",
-          "::mlir::Attribute", "getShape", (ins )
-      >,
-      InterfaceMethod<"Get the `name` attribute.",
-          "::mlir::StringRef", "getName", (ins )
-      >,
-      InterfaceMethod<"Set the offset to the attribute.",
-          "void", "setOffsetAttr", (ins "::mlir::IntegerAttr": $attr)
-      >,
-      InterfaceMethod<"Get the `offset` attribute.",
-          "std::optional<uint64_t>", "getOffset", (ins )
-      >
-  ];
-
-  let extraClassDeclaration = [{
-    /// Return the single result of this op.
-    ::mlir::Value getResult() {
-      return getOperation()->getResult(0);
-    }
-  }];
-
-  let cppNamespace = "::mlir";
-}
-
-#endif // KRNLGLOBAL_OP_INTERFACE
diff --git a/test/mlir/accelerators/nnpa/conversion/device-placement/emit-zhighir.mlir b/test/mlir/accelerators/nnpa/conversion/device-placement/emit-zhighir.mlir
index a03c59b2f4..9b1bd2935d 100644
--- a/test/mlir/accelerators/nnpa/conversion/device-placement/emit-zhighir.mlir
+++ b/test/mlir/accelerators/nnpa/conversion/device-placement/emit-zhighir.mlir
@@ -39,13 +39,13 @@ module {
 // CHECK-DAG:       [[VAR_8_:%.+]] = "onnx.Transpose"([[VAR_2_]]) {perm = [2, 3, 1, 0]} : (tensor<8x1x5x5xf32>) -> tensor<5x5x1x8xf32>
 // CHECK-NOT: separator of consecutive DAGs
 // CHECK-DAG:       [[VAR_9_:%.+]] = "zhigh.Stick"([[VAR_8_]]) {layout = "HWCK"} : (tensor<5x5x1x8xf32>) -> tensor<5x5x1x8xf16, #zhigh.layout<{dataLayout = "HWCK"}>>
-// CHECK-DAG:       [[VAR_10_:%.+]] = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<[-0.161539719, -0.433835655, 0.091641359, -0.0168522168, -0.0650264397, -0.131737873, 0.0204175506, -0.121110231]> : tensor<8xf32>} : () -> tensor<8xf16, #zhigh.layout<{dataLayout = "1D"}>>
+// CHECK-DAG:       [[VAR_10_:%.+]] = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh_1> : tensor<4096xi8>} : () -> tensor<8xf16, #zhigh.layout<{dataLayout = "1D"}>>
 // CHECK:           [[VAR_11_:%.+]] = "zhigh.Conv2D"([[VAR_7_]], [[VAR_9_]], [[VAR_10_]]) {act_func = "ACT_RELU", kernel_shape = [5, 5], padding_type = "SAME_PADDING", strides = [1, 1]} : (tensor<1x28x28x1xf16, #zhigh.layout<{dataLayout = "NHWC"}>>, tensor<5x5x1x8xf16, #zhigh.layout<{dataLayout = "HWCK"}>>, tensor<8xf16, #zhigh.layout<{dataLayout = "1D"}>>) -> tensor<1x28x28x8xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
 // CHECK-DAG:       [[VAR_12_:%.+]] = "zhigh.MaxPool2D"([[VAR_11_]]) {kernel_shape = [2, 2], padding_type = "VALID_PADDING", strides = [2, 2]} : (tensor<1x28x28x8xf16, #zhigh.layout<{dataLayout = "NHWC"}>>) -> tensor<1x14x14x8xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
 // CHECK-DAG:       [[VAR_13_:%.+]] = "onnx.Transpose"([[VAR_1_]]) {perm = [2, 3, 1, 0]} : (tensor<16x8x5x5xf32>) -> tensor<5x5x8x16xf32>
 // CHECK-NOT: separator of consecutive DAGs
 // CHECK-DAG:       [[VAR_14_:%.+]] = "zhigh.Stick"([[VAR_13_]]) {layout = "HWCK"} : (tensor<5x5x8x16xf32>) -> tensor<5x5x8x16xf16, #zhigh.layout<{dataLayout = "HWCK"}>>
-// CHECK-DAG:       [[VAR_15_:%.+]] = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<[-0.0822488219, -0.108868778, -0.141039595, -0.204869166, -0.17913565, -0.215438381, -0.133805066, -0.195724562, -0.268250644, -0.258212209, -0.0761560649, 0.0132841459, -0.00444464432, -0.414740831, -0.17879115, -0.0386558883]> : tensor<16xf32>} : () -> tensor<16xf16, #zhigh.layout<{dataLayout = "1D"}>>
+// CHECK-DAG:       [[VAR_15_:%.+]] = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<16xf16, #zhigh.layout<{dataLayout = "1D"}>>
 // CHECK:           [[VAR_16_:%.+]] = "zhigh.Conv2D"([[VAR_12_]], [[VAR_14_]], [[VAR_15_]]) {act_func = "ACT_RELU", kernel_shape = [5, 5], padding_type = "SAME_PADDING", strides = [1, 1]} : (tensor<1x14x14x8xf16, #zhigh.layout<{dataLayout = "NHWC"}>>, tensor<5x5x8x16xf16, #zhigh.layout<{dataLayout = "HWCK"}>>, tensor<16xf16, #zhigh.layout<{dataLayout = "1D"}>>) -> tensor<1x14x14x16xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
 // CHECK:           [[VAR_17_:%.+]] = "zhigh.MaxPool2D"([[VAR_16_]]) {kernel_shape = [3, 3], padding_type = "VALID_PADDING", strides = [3, 3]} : (tensor<1x14x14x16xf16, #zhigh.layout<{dataLayout = "NHWC"}>>) -> tensor<1x4x4x16xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
 // CHECK:           [[VAR_18_:%.+]] = "zhigh.Unstick"([[VAR_17_]]) : (tensor<1x4x4x16xf16, #zhigh.layout<{dataLayout = "NHWC"}>>) -> tensor<1x16x4x4xf32>
diff --git a/test/mlir/accelerators/nnpa/conversion/lower-all-to-llvm.mlir b/test/mlir/accelerators/nnpa/conversion/lower-all-to-llvm.mlir
index 4100b41d9e..2307680415 100644
--- a/test/mlir/accelerators/nnpa/conversion/lower-all-to-llvm.mlir
+++ b/test/mlir/accelerators/nnpa/conversion/lower-all-to-llvm.mlir
@@ -478,4 +478,3 @@ func.func @test_call_zdnn_batchnorm() -> () {
   // CHECK-LABEL: test_call_zdnn_batchnorm
   // CHECK: {{.*}} = llvm.call @zdnn_batchnorm(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}) : (!llvm.ptr, !llvm.ptr, !llvm.ptr, !llvm.ptr) -> i32
 }
-
diff --git a/test/mlir/accelerators/nnpa/conversion/lower-to-llvm-be/lit.local.cfg b/test/mlir/accelerators/nnpa/conversion/lower-to-llvm-be/lit.local.cfg
deleted file mode 100644
index ac7f7ec3e6..0000000000
--- a/test/mlir/accelerators/nnpa/conversion/lower-to-llvm-be/lit.local.cfg
+++ /dev/null
@@ -1,6 +0,0 @@
-if sys.byteorder == "little":
-  config.unsupported = True
-else:
-  config.unsupported = False
-
-root = config.root
diff --git a/test/mlir/accelerators/nnpa/conversion/lower-to-llvm-be/lower-all-to-llvm_be.mlir b/test/mlir/accelerators/nnpa/conversion/lower-to-llvm-be/lower-all-to-llvm_be.mlir
deleted file mode 100644
index 0a5c78240a..0000000000
--- a/test/mlir/accelerators/nnpa/conversion/lower-to-llvm-be/lower-all-to-llvm_be.mlir
+++ /dev/null
@@ -1,21 +0,0 @@
-// RUN: onnx-mlir-opt --mcpu=z16 --maccel=NNPA --convert-krnl-to-llvm %s -split-input-file | FileCheck %s
-
-// -----
-
-func.func @test_stickifiedconstant() -> memref<1x1x1x1x32x64xf16> {
-  %0 = "zlow.stickifiedConstant"() {alignment = 4096 : i64, layout = "2D", name = "constant_stickify_0", offset = 0 : i64, shape = [1, 1, 1, 1, 32, 64], stickified = false, value = dense<[[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]]> : tensor<2x3xf32>} : () -> memref<1x1x1x1x32x64xf16>
-  return %0 : memref<1x1x1x1x32x64xf16>
-
-  // CHECK:         llvm.mlir.global internal constant 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{addr_space = 0 : i32, alignment = 4096 : i64}
-
-}
-
-// -----
-
-func.func @test_stickifiedconstant_allzero() -> memref<1x1x1x1x32x64xf16>  {
-  %0 = "zlow.stickifiedConstant"() {alignment = 4096 : i64, layout = "2D", name = "constant_stickify_0", offset = 0 : i64, shape = [1, 1, 1, 1, 32, 64], stickified = true, value = dense<0.000000e+00> : tensor<1x1x1x32x64xf16>} : () -> memref<1x1x1x1x32x64xf16>
-  return %0 : memref<1x1x1x1x32x64xf16>
-
-  // CHECK:         llvm.mlir.global internal constant 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{addr_space = 0 : i32, alignment = 4096 : i64}
-
-}
diff --git a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/conv.mlir b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/conv.mlir
index c409d1f9fd..2d2983ba07 100644
--- a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/conv.mlir
+++ b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/conv.mlir
@@ -189,7 +189,7 @@ func.func @conv_same_padding_no_bias_unknown_dims(%arg0: tensor<1x32x32x3xf16, #
 // CHECK:           krnl.store [[VAR_c1_i64_]], [[RES_1_]]{{.}}[[VAR_c4_]]{{.}} : memref<7xi64>
 // CHECK:           krnl.store [[VAR_c32_i64_]], [[RES_1_]]{{.}}[[VAR_c5_]]{{.}} : memref<7xi64>
 // CHECK:           krnl.store [[VAR_c32_i64_]], [[RES_1_]]{{.}}[[VAR_c6_]]{{.}} : memref<7xi64>
-// CHECK:           [[VAR_2_:%.+]] = "zlow.stickifiedConstant"() {alignment = 4096 : i64, name = "constant_stickify_0", offset = 0 : i64, shape = [1, 1, 1, 1, 32, 64], stickified = true, value = dense<0.000000e+00> : memref<1x1x1x1x32x64xf16>} : () -> memref<1x1x1x1x32x64xf16>
+// CHECK:           [[VAR_2_:%.+]] = "krnl.global"() {alignment = 4096 : i64, name = "constant_stickify_0", shape = [1, 1, 1, 1, 32, 64], value = dense_resource<zhigh> : tensor<4096xi8>} : () -> memref<1x1x1x1x32x64xf16>
 // CHECK:           "zlow.conv2d"([[PARAM_0_]], [[PARAM_1_]], [[VAR_2_]], [[RES_1_]], [[RES_]]) {act_func = "ACT_NONE", kernel_shape = [2, 2], padding_type = "SAME_PADDING", strides = [1, 1]} : (memref<1x32x32x3xf16, #map>, memref<2x2x3x1xf16, #map1>, memref<1x1x1x1x32x64xf16>, memref<7xi64>, memref<1x32x32x1xf16, #map>) -> ()
 // CHECK:           return [[RES_]] : memref<1x32x32x1xf16, #map>
 // CHECK:         }
diff --git a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/gru.mlir b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/gru.mlir
index c705168d4d..b828da2b80 100644
--- a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/gru.mlir
+++ b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/gru.mlir
@@ -220,8 +220,8 @@ func.func @gru_no_input_and_hidden_biases(%input : tensor<?x?x7xf16, #zhigh.layo
 // CHECK:           krnl.store [[VAR_1_]], [[RES_1_]]{{.}}[[VAR_c2_]]{{.}} : memref<5xi64>
 // CHECK:           krnl.store [[VAR_c7_i64_]], [[RES_1_]]{{.}}[[VAR_c3_]]{{.}} : memref<5xi64>
 // CHECK:           krnl.store [[VAR_c9_i64_]], [[RES_1_]]{{.}}[[VAR_c4_]]{{.}} : memref<5xi64>
-// CHECK-DAG:       [[VAR_2_:%.+]] = "zlow.stickifiedConstant"() {alignment = 4096 : i64, name = "constant_stickify_0", offset = 0 : i64, shape = [1, 3, 1, 1, 32, 64], stickified = true, value = dense<0.000000e+00> : memref<1x3x1x1x32x64xf16>} : () -> memref<1x3x1x1x32x64xf16>
-// CHECK-DAG:       [[VAR_3_:%.+]] = "zlow.stickifiedConstant"() {alignment = 4096 : i64, name = "constant_stickify_1", offset = 0 : i64, shape = [1, 3, 1, 1, 32, 64], stickified = true, value = dense<0.000000e+00> : memref<1x3x1x1x32x64xf16>} : () -> memref<1x3x1x1x32x64xf16>
+// CHECK-DAG:       [[VAR_2_:%.+]] = "krnl.global"() {alignment = 4096 : i64, name = "constant_stickify_0", shape = [1, 3, 1, 1, 32, 64], value = dense_resource<zhigh> : tensor<12288xi8>} : () -> memref<1x3x1x1x32x64xf16>
+// CHECK-DAG:       [[VAR_3_:%.+]] = "krnl.global"() {alignment = 4096 : i64, name = "constant_stickify_1", shape = [1, 3, 1, 1, 32, 64], value = dense_resource<zhigh_1> : tensor<12288xi8>} : () -> memref<1x3x1x1x32x64xf16>
 // CHECK-DAG:       [[VAR_dim_2_:%.+]] = memref.dim [[PARAM_0_]], [[VAR_c0_]] : memref<?x?x7xf16, [[MAP_0_]]>
 // CHECK-DAG:       [[VAR_dim_3_:%.+]] = memref.dim [[PARAM_0_]], [[VAR_c1_]] : memref<?x?x7xf16, [[MAP_0_]]>
 // CHECK-NOT: separator of consecutive DAGs
diff --git a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/lstm.mlir b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/lstm.mlir
index a31d70231e..e63d5cee97 100644
--- a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/lstm.mlir
+++ b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/lstm.mlir
@@ -357,8 +357,8 @@ func.func @lstm_no_input_and_hidden_biases(%input : tensor<?x?x7xf16, #zhigh.lay
 // CHECK:           krnl.store [[VAR_1_]], [[RES_2_]]{{.}}[[VAR_c2_]]{{.}} : memref<5xi64>
 // CHECK:           krnl.store [[VAR_c7_i64_]], [[RES_2_]]{{.}}[[VAR_c3_]]{{.}} : memref<5xi64>
 // CHECK:           krnl.store [[VAR_c9_i64_]], [[RES_2_]]{{.}}[[VAR_c4_]]{{.}} : memref<5xi64>
-// CHECK-DAG:       [[VAR_2_:%.+]] = "zlow.stickifiedConstant"() {alignment = 4096 : i64, name = "constant_stickify_0", offset = 0 : i64, shape = [1, 4, 1, 1, 32, 64], stickified = true, value = dense<0.000000e+00> : memref<1x4x1x1x32x64xf16>} : () -> memref<1x4x1x1x32x64xf16>
-// CHECK-DAG:       [[VAR_3_:%.+]] = "zlow.stickifiedConstant"() {alignment = 4096 : i64, name = "constant_stickify_1", offset = 0 : i64, shape = [1, 4, 1, 1, 32, 64], stickified = true, value = dense<0.000000e+00> : memref<1x4x1x1x32x64xf16>} : () -> memref<1x4x1x1x32x64xf16>
+// CHECK-DAG:       [[VAR_2_:%.+]] = "krnl.global"() {alignment = 4096 : i64, name = "constant_stickify_0", shape = [1, 4, 1, 1, 32, 64], value = dense_resource<zhigh> : tensor<16384xi8>} : () -> memref<1x4x1x1x32x64xf16>
+// CHECK-DAG:       [[VAR_3_:%.+]] = "krnl.global"() {alignment = 4096 : i64, name = "constant_stickify_1", shape = [1, 4, 1, 1, 32, 64], value = dense_resource<zhigh_1> : tensor<16384xi8>} : () -> memref<1x4x1x1x32x64xf16>
 // CHECK-DAG:       [[VAR_dim_3_:%.+]] = memref.dim [[PARAM_0_]], [[VAR_c0_]] : memref<?x?x7xf16, [[MAP_0_]]>
 // CHECK-DAG:       [[VAR_dim_4_:%.+]] = memref.dim [[PARAM_0_]], [[VAR_c1_]] : memref<?x?x7xf16, [[MAP_0_]]>
 // CHECK-NOT: separator of consecutive DAGs
diff --git a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/stickified-constant.mlir b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/stickified-constant.mlir
index b0188969d0..7bf9766d88 100644
--- a/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/stickified-constant.mlir
+++ b/test/mlir/accelerators/nnpa/conversion/zhigh-to-zlow/stickified-constant.mlir
@@ -2,17 +2,24 @@
 
 module  {
   func.func @remove_stick_2d() -> tensor<2x3xf32> {
-    %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<[[0., 1., 2.], [3., 4., 5.]]> : tensor<2x3xf32>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D"}>>
+    %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D"}>>
     %1 = "zhigh.Unstick"(%0) : (tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D"}>>) -> tensor<2x3xf32>
     return %1 : tensor<2x3xf32>
   }
 }
 
+{-#
+  dialect_resources: {
+    builtin: {
+      zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+    }
+  }
+#-}
 
 // CHECK-DAG: [[MAP_0_:#.+]] = affine_map<(d0, d1) -> (0, d1 floordiv 64, 0, d0 floordiv 32, d0 mod 32, d1 mod 64)>
-// CHECK-LABEL:  func.func @remove_stick_2d
+// CHECK-LABEL:  func @remove_stick_2d
 // CHECK-SAME:   () -> memref<2x3xf32> {
-// CHECK-DAG:       [[VAR_0_:%.+]] = "zlow.stickifiedConstant"() {alignment = 4096 : i64, layout = "2D", name = "constant_stickify_0", offset = 0 : i64, shape = [1, 1, 1, 1, 32, 64], stickified = false, value = dense<{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}> : tensor<2x3xf32>} : () -> memref<2x3xf16, #map>
+// CHECK-DAG:       [[VAR_0_:%.+]] = "krnl.global"() {alignment = 4096 : i64, name = "constant_stickify_0", shape = [1, 1, 1, 1, 32, 64], value = dense_resource<zhigh> : tensor<4096xi8>} : () -> memref<2x3xf16, [[MAP_0_]]>
 // CHECK-DAG:       [[VAR_c2_:%.+]] = arith.constant 2 : index
 // CHECK-DAG:       [[VAR_c3_:%.+]] = arith.constant 3 : index
 // CHECK-DAG:       [[RES_:%.+]] = memref.alloc() {{.*}}: memref<2x3xf32>
@@ -20,3 +27,8 @@ module  {
 // CHECK:           return [[RES_]] : memref<2x3xf32>
 // CHECK:         }
 
+// CHECK: dialect_resources: {
+// CHECK-NEXT:   builtin: {
+// CHECK-NEXT:     zhigh: "0x0100000000003E00400000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000004100420042800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"
+// CHECK-NEXT:   }
+// CHECK-NEXT: }
diff --git a/test/mlir/accelerators/nnpa/driver/ccfd.mlir b/test/mlir/accelerators/nnpa/driver/ccfd.mlir
index 690becf58b..3c66f67da7 100644
--- a/test/mlir/accelerators/nnpa/driver/ccfd.mlir
+++ b/test/mlir/accelerators/nnpa/driver/ccfd.mlir
@@ -5,14 +5,15 @@
 // COM: It is the necessary condition to get the best performance.
 
 CHECK-LABEL: func.func @main_graph
-CHECK-DAG: zlow.stickifiedConstant
-CHECK-DAG: zlow.stickifiedConstant
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
 CHECK-DAG: memref.alloc
 CHECK-NEXT: zlow.stick
-CHECK-DAG: zlow.stickifiedConstant
 
-CHECK-DAG: zlow.stickifiedConstant
-CHECK-DAG: zlow.stickifiedConstant
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
 CHECK-DAG: memref.alloc
 CHECK-DAG: memref.alloc
 CHECK-DAG: krnl.global
@@ -23,10 +24,12 @@ CHECK-NEXT: zlow.lstm
 CHECK-NOT: zlow.stick
 CHECK-NOT: zlow.unstick
 
-CHECK-DAG: zlow.stickifiedConstant
-CHECK-DAG: zlow.stickifiedConstant
-CHECK-DAG: zlow.stickifiedConstant
-CHECK-DAG: zlow.stickifiedConstant
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
+CHECK-DAG: krnl.global
 CHECK-DAG: memref.alloc
 CHECK-DAG: memref.alloc
 CHECK-DAG: krnl.global
@@ -37,17 +40,17 @@ CHECK-NEXT: zlow.lstm
 CHECK-NOT: zlow.stick
 CHECK-NOT: zlow.unstick
 
-CHECK-DAG: zlow.stickifiedConstant
+CHECK-DAG: krnl.global
 CHECK-DAG: memref.alloc
 CHECK-DAG: krnl.global
-CHECK-DAG: zlow.stickifiedConstant
+CHECK-DAG: krnl.global
 CHECK-NEXT: zlow.matmul
 
 // No stick and unstick in between.
 CHECK-NOT: zlow.stick
 CHECK-NOT: zlow.unstick
 
-CHECK-DAG: zlow.stickifiedConstant
+CHECK-DAG: krnl.global
 CHECK-DAG: memref.alloc
 CHECK-DAG: krnl.global
 CHECK-NEXT: zlow.add
diff --git a/test/mlir/accelerators/nnpa/driver/dense-out-attention-layer.mlir b/test/mlir/accelerators/nnpa/driver/dense-out-attention-layer.mlir
index 11ccc619a0..863efd1ee4 100644
--- a/test/mlir/accelerators/nnpa/driver/dense-out-attention-layer.mlir
+++ b/test/mlir/accelerators/nnpa/driver/dense-out-attention-layer.mlir
@@ -14,6 +14,6 @@ func.func @test_matmul_add_add(%arg0: tensor<?x?x768xf32>, %arg1: tensor<768x768
 // CHECK-SAME:   ([[PARAM_0_:%.+]]: tensor<?x?x768xf32>, [[PARAM_1_:%.+]]: tensor<768x768xf32>) -> tensor<?x?x768xf32> {
 // CHECK-DAG:       [[VAR_0_:%.+]] = "zhigh.Stick"([[PARAM_0_]]) {layout = "3DS"} : (tensor<?x?x768xf32>) -> tensor<?x?x768xf16, #zhigh.layout<{dataLayout = "3DS"}>>
 // CHECK-DAG:       [[VAR_1_:%.+]] = "zhigh.Stick"([[PARAM_1_]]) {layout = "2D"} : (tensor<768x768xf32>) -> tensor<768x768xf16, #zhigh.layout<{dataLayout = "2D"}>>
-// CHECK-DAG:       [[VAR_2_:%.+]] = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<5.000000e+00> : tensor<768xf32>} : () -> tensor<768xf16, #zhigh.layout<{dataLayout = "1D"}>>
+// CHECK-DAG:       [[VAR_2_:%.+]] = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<49152xi8>} : () -> tensor<768xf16, #zhigh.layout<{dataLayout = "1D"}>>
 // CHECK:           [[VAR_3_:%.+]] = "zhigh.MatMul"([[VAR_0_]], [[VAR_1_]], [[VAR_2_]]) : (tensor<?x?x768xf16, #zhigh.layout<{dataLayout = "3DS"}>>, tensor<768x768xf16, #zhigh.layout<{dataLayout = "2D"}>>, tensor<768xf16, #zhigh.layout<{dataLayout = "1D"}>>) -> tensor<?x?x768xf16, #zhigh.layout<{dataLayout = "3DS"}>>
 }
diff --git a/test/mlir/accelerators/nnpa/transform/zhigh-constant-propagation-be/constprop.mlir b/test/mlir/accelerators/nnpa/transform/zhigh-constant-propagation-be/constprop.mlir
index 27c53c501b..609cab1aec 100644
--- a/test/mlir/accelerators/nnpa/transform/zhigh-constant-propagation-be/constprop.mlir
+++ b/test/mlir/accelerators/nnpa/transform/zhigh-constant-propagation-be/constprop.mlir
@@ -9,11 +9,16 @@ func.func @remove_stick_1d() -> tensor<6xf16, #zhigh.layout<{dataLayout = "1D"}>
   %res = "zhigh.Stick"(%inp) {layout = "1D"} : (tensor<6xf32>) -> tensor<6xf16, #zhigh.layout<{dataLayout = "1D"}>>
   return %res : tensor<6xf16, #zhigh.layout<{dataLayout = "1D"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<[0.000000e+00, 1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00]> : tensor<6xf32>} : () -> tensor<6xf16, #zhigh.layout<{dataLayout = "1D"}>>
+  // CHECK-NEXT: %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<6xf16, #zhigh.layout<{dataLayout = "1D"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
 
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E00400041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"
+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -26,10 +31,16 @@ func.func @remove_stick_2d() -> tensor<2x3xf32> {
   %res = "zhigh.Unstick"(%st) {layout = "2D"} : (tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D"}>>) -> tensor<2x3xf32>
   return %res : tensor<2x3xf32>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}> : tensor<2x3xf32>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -41,10 +52,16 @@ func.func @remove_stick_2ds() -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2D
   %res = "zhigh.Stick"(%inp) {layout = "2DS"} : (tensor<2x3xf32>) -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2DS"}>>
   return %res : tensor<2x3xf16, #zhigh.layout<{dataLayout = "2DS"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}> : tensor<2x3xf32>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2DS"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<8192xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "2DS"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -56,10 +73,16 @@ func.func @remove_stick_3d() -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3
   %res = "zhigh.Stick"(%inp) {layout = "3D"} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3D"}>>
   return %res : tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3D"}>>
 
- // CHECK-NEXT:  "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}{{.}}> : tensor<1x2x3xf32>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3D"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3D"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -71,10 +94,16 @@ func.func @remove_stick_3ds() -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "
   %res = "zhigh.Stick"(%inp) {layout = "3DS"} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3DS"}>>
   return %res : tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3DS"}>>
 
- // CHECK-NEXT:  "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}{{.}}> : tensor<1x2x3xf32>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3DS"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "3DS"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -86,10 +115,16 @@ func.func @remove_stick_4d() -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout =
   %res = "zhigh.Stick"(%inp) {layout = "4D"} : (tensor<1x1x2x3xf32>) -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "4D"}>>
   return %res : tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "4D"}>>
 
- // CHECK-NEXT:  "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}[{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}{{.}}]> : tensor<1x1x2x3xf32>} : () -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "4D"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "4D"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -101,10 +136,16 @@ func.func @remove_stick_nhwc() -> tensor<1x2x3x1xf16, #zhigh.layout<{dataLayout
   %res = "zhigh.Stick"(%inp) {layout = "NHWC"} : (tensor<1x1x2x3xf32>) -> tensor<1x2x3x1xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
   return %res : tensor<1x2x3x1xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}[{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}{{.}}]> : tensor<1x1x2x3xf32>} : () -> tensor<1x2x3x1xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<8192xi8>} : () -> tensor<1x2x3x1xf16, #zhigh.layout<{dataLayout = "NHWC"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000003E000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -116,10 +157,16 @@ func.func @remove_stick_nchw() -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout
   %res = "zhigh.Stick"(%inp) {layout = "NCHW"} : (tensor<1x1x2x3xf32>) -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "NCHW"}>>
   return %res : tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "NCHW"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}[{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}{{.}}]> : tensor<1x1x2x3xf32>} : () -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "NCHW"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<8192xi8>} : () -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "NCHW"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000003E000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -131,10 +178,16 @@ func.func @remove_stick_cnnk_hwck() -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLa
   %res = "zhigh.Stick"(%inp) {layout = "HWCK"} : (tensor<1x1x2x3xf32>) -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "HWCK"}>>
   return %res : tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "HWCK"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<{{.}}[{{.}}[0.000000e+00, 1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00, 5.000000e+00]{{.}}{{.}}]> : tensor<1x1x2x3xf32>} : () -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "HWCK"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<1x1x2x3xf16, #zhigh.layout<{dataLayout = "HWCK"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x0100000000003E004000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000041004200428000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -149,7 +202,7 @@ func.func @remove_stick_zrh_2d() -> tensor<2x3xf16, #zhigh.layout<{dataLayout =
   %res = "zhigh.StickForGRU"(%z, %r, %h) : (tensor<2x3xf32>, tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
   return %res : tensor<2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = true, value = dense_resource<zhigh> : tensor<24576xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<24576xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.StickForGRU"
@@ -173,7 +226,7 @@ func.func @remove_stick_zrh_3d() -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout
   %res = "zhigh.StickForGRU"(%z, %r, %h) : (tensor<1x2x3xf32>, tensor<1x2x3xf32>, tensor<1x2x3xf32>) -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
   return %res : tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = true, value = dense_resource<zhigh> : tensor<12288xi8>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<12288xi8>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "ZRH"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.StickForGRU"
@@ -198,7 +251,7 @@ func.func @remove_stick_fico_2d() -> tensor<2x3xf16, #zhigh.layout<{dataLayout =
   %res = "zhigh.StickForLSTM"(%f, %i, %c, %o) : (tensor<2x3xf32>, tensor<2x3xf32>, tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
   return %res : tensor<2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = true, value = dense_resource<zhigh> : tensor<32768xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<32768xi8>} : () -> tensor<2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.StickForLSTM"
@@ -223,7 +276,7 @@ func.func @remove_stick_fico_3d() -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout
   %res = "zhigh.StickForLSTM"(%f, %i, %c, %o) : (tensor<1x2x3xf32>, tensor<1x2x3xf32>, tensor<1x2x3xf32>, tensor<1x2x3xf32>) -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
   return %res : tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
 
-  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = true, value = dense_resource<zhigh> : tensor<16384xi8>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
+  // CHECK-NEXT: "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<16384xi8>} : () -> tensor<1x2x3xf16, #zhigh.layout<{dataLayout = "FICO"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.StickForLSTM"
@@ -244,10 +297,16 @@ func.func @out_of_range_minimum() -> tensor<1xf16, #zhigh.layout<{dataLayout = "
   %res = "zhigh.Stick"(%inp) {layout = "1D"} : (tensor<1xf32>) -> tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
   return %res : tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
 
-  // CHECK-NEXT: %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<-3.402820e+38> : tensor<1xf32>} : () -> tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
+  // CHECK-NEXT: %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
+
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x01000000FFFE00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }
 
 // -----
@@ -258,9 +317,14 @@ func.func @out_of_range_maximum() -> tensor<1xf16, #zhigh.layout<{dataLayout = "
   %res = "zhigh.Stick"(%inp) {layout = "1D"} : (tensor<1xf32>) -> tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
   return %res : tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
 
-  // CHECK-NEXT: %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, stickified = false, value = dense<3.402820e+38> : tensor<1xf32>} : () -> tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
+  // CHECK-NEXT: %0 = "zhigh.StickifiedConstant"() {alignment = 4096 : i64, value = dense_resource<zhigh> : tensor<4096xi8>} : () -> tensor<1xf16, #zhigh.layout<{dataLayout = "1D"}>>
 
   // CHECK-NOT: "onnx.Constant"
   // CHECK-NOT: "zhigh.Stick"
 
+  // CHECK: dialect_resources: {
+  // CHECK-NEXT:   builtin: {
+  // CHECK-NEXT:     zhigh: "0x010000007FFE00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000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+  // CHECK-NEXT:   }
+  // CHECK-NEXT: }
 }