diff --git a/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/CMakeLists.txt b/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/CMakeLists.txt
index d33bfaf57a..64ed528359 100644
--- a/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/CMakeLists.txt
+++ b/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/CMakeLists.txt
@@ -1,6 +1,5 @@
 include_directories(common)
 
-add_example_with_mkl(dgemm_target_variant_dispatch_c)
 add_example_with_mkl(dgemm_dispatch_c)
 add_example_with_mkl(dgemm_example_01)
 add_example_with_mkl(dgemm_example_02)
diff --git a/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_dispatch_c.cpp b/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_dispatch_c.cpp
index 1e9ab2ea0f..d197c32fb8 100644
--- a/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_dispatch_c.cpp
+++ b/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_dispatch_c.cpp
@@ -63,7 +63,7 @@ int main()
 
     #pragma omp target data map(to: A[0:m*k], B[0:k*n]) map(tofrom: C[0:m*n])
     {
-       #pragma omp target variant dispatch use_device_ptr(A, B, C)
+       #pragma omp dispatch
        cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
                    m, n, k, alpha, A, k, B, n, beta, C, n);
     }
diff --git a/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_target_variant_dispatch_c.cpp b/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_target_variant_dispatch_c.cpp
deleted file mode 100644
index d803bd7ab9..0000000000
--- a/Publications/GPU-Opt-Guide/OpenMP/22_mkl_dispatch/dgemm_target_variant_dispatch_c.cpp
+++ /dev/null
@@ -1,123 +0,0 @@
-//==============================================================
-// Copyright © 2022 Intel Corporation
-//
-// SPDX-License-Identifier: MIT
-// =============================================================
-// clang-format off
-// Snippet begin
-#include <stdio.h>
-#include <stdlib.h>
-#include <math.h>
-#include <omp.h>
-#include "mkl.h"
-#include "mkl_omp_offload.h"
-
-#define min(x,y) (((x) < (y)) ? (x) : (y))
-#define EPSILON 0.0001
-
-int main()
-{
-    double *A, *B, *C, *C_fl;
-    int64_t m, n, k;
-    double alpha, beta;
-    double sum;
-    int64_t i, j, q;
-    int fail;
-
-    printf ("\n This example computes real matrix C=alpha*A*B+beta*C using \n"
-            " Intel oneMKL function dgemm, where A, B, and  C are matrices and \n"
-            " alpha and beta are double precision scalars\n\n");
-
-    m = 2000, k = 200, n = 1000;
-    printf (" Initializing data for matrix multiplication C=A*B for matrix \n"
-            " A(%li x %li) and matrix B(%li x %li)\n\n", m, k, k, n);
-    alpha = 1.0; beta = 0.0;
-
-    printf (" Allocating memory for matrices aligned on 64-byte boundary for better \n"
-            " performance \n\n");
-    A = (double *)mkl_malloc( m * k * sizeof( double ), 64 );
-    B = (double *)mkl_malloc( k * n * sizeof( double ), 64 );
-    C = (double *)mkl_malloc( m * n * sizeof( double ), 64 );
-    C_fl = (double *)mkl_malloc( m*n*sizeof( double ), 64 );
-
-    if (A == NULL || B == NULL || C == NULL || C_fl == NULL) {
-      printf( "\n ERROR: Cannot allocate memory for matrices. Exiting... \n\n");
-      return 1;
-    }
-
-    printf (" Intializing matrices \n\n");
-    for (i = 0; i < (m*k); i++) {
-        A[i] = (double)(i+1);
-    }
-
-    for (i = 0; i < (k*n); i++) {
-        B[i] = (double)(-i-1);
-    }
-
-    for (i = 0; i < (m*n); i++) {
-        C[i] = 0.0;
-        C_fl[i] = 0.0;
-    }
-
-    printf (" Computing matrix product using Intel oneMKL dgemm function via CBLAS interface \n\n");
-
-    #pragma omp target data map(to: A[0:m*k], B[0:k*n]) map(tofrom: C[0:m*n])
-    {
-       #pragma omp target variant dispatch use_device_ptr(A, B, C)
-       {
-          cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
-                      m, n, k, alpha, A, k, B, n, beta, C, n);
-       }
-    }
-
-    printf ("\n Top left corner of matrix C: \n");
-    for (i=0; i<min(m,6); i++) {
-        for (j=0; j<min(n,6); j++) {
-            printf ("%12.5G", C[j+i*n]);
-        }
-        printf ("\n");
-    }
-
-    printf (" Computing matrix product using for-loops \n");
-
-    for (i = 0; i < m; i++) {
-        for (j = 0; j < n; j++) {
-            sum = 0.0;
-            for (q = 0; q < k; q++) {
-                sum += A[k*i+q] * B[n*q+j];
-            }
-            C_fl[n*i+j] = alpha * sum + beta * C_fl[n*i+j];
-        }
-    }
-
-    printf ("\n Top left corner of matrix C_fl: \n");
-    for (i=0; i<min(m,6); i++) {
-        for (j=0; j<min(n,6); j++) {
-            printf ("%12.5G", C_fl[j+i*n]);
-        }
-        printf ("\n");
-    }
-
-    printf (" Computations completed. Verifying... \n\n");
-
-    fail = 0;
-    for (i = 0; i < (m*n); i++) {
-        if (fabs(C[i] - C_fl[i]) > EPSILON) {
-            fail = 1;
-            break;
-	}
-    }
-
-    if (fail)
-        printf ("\n **** FAIL **** \n");
-    else
-        printf ("\n **** PASS **** \n");
-
-    printf ("\n Deallocating memory \n\n");
-    mkl_free(A);
-    mkl_free(B);
-    mkl_free(C);
-
-    return fail;
-}
-// Snippet end