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Fix cloning, compilation and linking errors for the non-docker version #9

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Currently the repository is impossible to clone or build in both docker and non-docker version.

Although not full, this is a list of changes that makes it work for the local non-docker version.

There's much more to be done, to make it universal, but this is the minimal set.

More changes will be added as the semester progresses.

steps to build, assuming conda rapids-23.04 environment has been installed (if not install from here)

git clone --recurse-submodules [...]
cd meta-json-parser
mkdir build
cd build
conda activate rapids-23.04
cmake ../ -GNinja
ninja

url = https://github.com/google/googletest.git
[submodule "third_parties/fmt"]
path = third_parties/fmt
url = https://github.com/fmtlib/fmt.git
[submodule "third_parties/mp11"]
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otherwise impossible to clone

[submodule "third_parties/googletest"]
path = third_parties/googletest
url = https://github.com/google/googletest.git
[submodule "third_parties/fmt"]
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otherwise impossible to link

@@ -3,29 +3,22 @@ set(CMAKE_VERBOSE_MAKEFILE ON)

project(meta-json-parser VERSION 0.1 LANGUAGES CXX CUDA)

find_package(CUDAToolkit 10.0 REQUIRED)
# As of now not using LIBCUDF throws
set(USE_LIBCUDF 1)
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if not set to 1, the project throws compilation errors (ifdefs are leaky)

IF(NOT LOCAL_LIB)
find_package(Boost 1.75) # version 1.75 is required to use boost::mp11::mp_pairwise_fold_q
ENDIF()
find_package(CUDAToolkit EXACT 11.8 REQUIRED)
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currently the newest is 12 (so the previous would find 12, as it only set minimum), but RAPIDS are currently limited to 11.X

include(GoogleTest)

#Add FMT library (as CUDA11.8 doesn't support gcc12)
add_subdirectory(third_parties/fmt)
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as above

@@ -113,6 +106,7 @@ target_link_libraries(meta-cudf-parser-1 PUBLIC lib-meta-json-parser)

target_include_directories(meta-cudf-parser-1 PUBLIC
"${PROJECT_SOURCE_DIR}/meta_cudf/opt1"
"$ENV{CONDA_PREFIX}/include"
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universal instead of hardfixed

@@ -182,7 +176,7 @@ add_subdirectory(third_parties/CLI11)
#add_executable(meta-json-parser-benchmark benchmark/checkpoint_results.cpp benchmark/checkpoint_results.h)
add_executable(meta-json-parser-benchmark)

target_link_libraries(meta-json-parser-benchmark PRIVATE lib-meta-json-parser CLI11)
target_link_libraries(meta-json-parser-benchmark PRIVATE lib-meta-json-parser fmt::fmt CLI11)
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otherwise throws linking errors

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During which part of build (I wonder which part requires fmt library)?

@@ -192,33 +186,34 @@ if (USE_LIBCUDF)
# instead of hardcoding paths to includes and to libraries, like below
target_include_directories(meta-cudf-parser-1 PUBLIC
/usr/local/include
/usr/local/include/libcudf/libcudacxx
$ENV{CONDA_PREFIX}/include
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universal instead of hardfixed

@@ -192,33 +186,34 @@ if (USE_LIBCUDF)
# instead of hardcoding paths to includes and to libraries, like below
target_include_directories(meta-cudf-parser-1 PUBLIC
/usr/local/include
/usr/local/include/libcudf/libcudacxx
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couldn't find libcudacxx in any folder related to current libraries and deleting this doesn't change anything

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I remember it was necessary for something, perhaps for running via docker image, but might be no longer needed.

)
target_include_directories(meta-cudf-parser-1 AFTER PUBLIC
/opt/conda/envs/rapids/include
$ENV{CONDA_PREFIX}/include
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universal instead of hardfixed

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also /opt/conda/envs/rapids doesn't exist in a default conda installation of rapids

)
target_link_libraries(meta-cudf-parser-1 PRIVATE
cudf
-L/usr/local/cuda/lib64 -L/usr/local/lib
-L/opt/conda/envs/rapids/lib
-L$ENV{CONDA_PREFIX}/lib
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universal instead of hardfixed

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also /opt/conda/envs/rapids doesn't exist in a default conda installation of rapids

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RAPIDS docker images used to have some of necessary includes and libs in /opt/conda/envs/rapids/ - while Dockerfile does not set CONDA_PREFIX environment variable. That's why it is here: for sudo docker build . to work.

Adding the $ENV{CONDA_PREFIX}/lib part is good, but I'd wait with removing /opt/conda/envs/rapids/ (see split commits).

)
target_compile_definitions(meta-cudf-parser-1 PRIVATE
HAVE_LIBCUDF=1
)

target_include_directories(meta-json-parser-benchmark PUBLIC
/usr/local/include
/usr/local/include/libcudf/libcudacxx
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as above

)
target_compile_definitions(meta-cudf-parser-1 PRIVATE
HAVE_LIBCUDF=1
)

target_include_directories(meta-json-parser-benchmark PUBLIC
/usr/local/include
/usr/local/include/libcudf/libcudacxx
$ENV{CONDA_PREFIX}/include
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as above

# NOTE: needs to be added as the last directory to be checked, because
# it can contain outdated Boost library (which in Ubuntu 20.04 is Boost 1.72)
target_include_directories(meta-json-parser-benchmark AFTER PUBLIC
/opt/conda/envs/rapids/include
$ENV{CONDA_PREFIX}/include
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as above

)
target_link_libraries(meta-json-parser-benchmark PRIVATE
cudf
-L/usr/local/cuda/lib64 -L/usr/local/lib
-L/opt/conda/envs/rapids/lib
-L$ENV{CONDA_PREFIX}/lib
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universal instead of hardfixed

as above with respect to existence of /envs/rapids

@@ -192,7 +192,7 @@ void describe_table(cudf::io::table_with_metadata& table_with_metadata, bool dum
printf("table (with metadata) has %d columns\n", n_cols);
for (int col_idx = 0; col_idx < n_cols; col_idx++) {
printf("column(%d) name is \"%s\":\n", col_idx,
table_with_metadata.metadata.column_names[col_idx].c_str());
table_with_metadata.metadata.schema_info[col_idx].name.c_str());
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cuDF in new (stable) RAPIDS released has changed its API and this is the new approach. schema info is a table of structs containing strings instead of table of strings

more info here

@@ -1,7 +1,6 @@
#pragma once
#include <cuda_runtime_api.h>
#include <thrust/host_vector.h>
#include <thrust/system/cuda/experimental/pinned_allocator.h>
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not used and CUDA 12 toolchain incompatible

@@ -257,7 +257,8 @@ cudf::io::table_with_metadata generate_example_metadata(const char* filename, in
return "Column " + to_string(i++);
});

cudf::io::table_metadata metadata{column_names};
cudf::io::table_metadata metadata;
std::for_each(begin(column_names), end(column_names), [&](auto& elem){metadata.schema_info.push_back({elem});});
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as above (cuDF API change)

@gprabowski
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a thing I noticed in development:
CONDA overwrites CUDA_HOME, it should be set manually back to 11.8 instead of 12.1 to which for some reason conda defaults to (although rapids-23.04 explicitly needs 11.8)

@jnareb
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jnareb commented May 23, 2023

Thanks.

I am currently working on incorporating this pull request, splitting it into even smaller pieces.
You can see current work in progress in branch 'pg/cmake_improvements', see
master...pg/cmake_improvements

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