Merge pull request #2174 from gangliao/define_cmake
Define cc_xxx and nv_xxx to simplify cmakerefactor_docs
Yi Wang
8 years ago
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GitHub
commit
0a4b540a6a
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# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# To simplify the build process of PaddlePaddle, we defined couple of
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# fundamental abstractions, e.g., how to build library, binary and
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# test in C++, CUDA and Go.
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#
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# -------------------------------------------
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# C++ CUDA C++ Go
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# -------------------------------------------
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# cc_library nv_library go_library
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# cc_binary nv_binary go_binary
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# cc_test nv_test go_test
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# -------------------------------------------
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#
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# cmake_parse_arguments can help us to achieve this goal.
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# https://cmake.org/cmake/help/v3.0/module/CMakeParseArguments.html
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# cc_library parses tensor.cc and figures out that target also depend on tensor.h.
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# cc_library(tensor
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# SRCS
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# tensor.cc
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# DEPS
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# variant)
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function(cc_library TARGET_NAME)
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set(options OPTIONAL)
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set(oneValueArgs "")
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set(multiValueArgs SRCS DEPS)
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cmake_parse_arguments(cc_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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if (${cc_library_OPTIONAL} STREQUAL "SHARED")
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add_library(${TARGET_NAME} SHARED ${cc_library_SRCS})
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else()
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add_library(${TARGET_NAME} STATIC ${cc_library_SRCS})
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endif()
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add_dependencies(${TARGET_NAME} ${cc_library_DEPS} ${external_project_dependencies})
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endfunction(cc_library)
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# cc_binary parses tensor.cc and figures out that target also depend on tensor.h.
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# cc_binary(tensor
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# SRCS
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# tensor.cc)
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function(cc_binary TARGET_NAME)
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set(options OPTIONAL)
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set(oneValueArgs "")
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set(multiValueArgs SRCS DEPS)
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cmake_parse_arguments(cc_binary "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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add_executable(${TARGET_NAME} ${cc_binary_SRCS})
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add_dependencies(${TARGET_NAME} ${cc_binary_DEPS} ${external_project_dependencies})
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target_link_libraries(${TARGET_NAME} ${cc_binary_DEPS})
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endfunction(cc_binary)
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# The dependency to target tensor implies that if any of
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# tensor{.h,.cc,_test.cc} is changed, tensor_test need to be re-built.
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# cc_test(tensor_test
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# SRCS
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# tensor_test.cc
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# DEPS
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# tensor)
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function(cc_test TARGET_NAME)
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set(options "")
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set(oneValueArgs "")
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set(multiValueArgs SRCS DEPS)
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cmake_parse_arguments(cc_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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add_executable(${TARGET_NAME} ${cc_test_SRCS})
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add_dependencies(${TARGET_NAME} ${cc_test_DEPS} ${external_project_dependencies})
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target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} ${GTEST_MAIN_LIBRARIES} ${GTEST_LIBRARIES})
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add_test(${TARGET_NAME} ${TARGET_NAME})
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endfunction(cc_test)
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# Suppose that ops.cu includes global functions that take Tensor as
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# their parameters, so ops depend on tensor. This implies that if
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# any of tensor.{h.cc}, ops.{h,cu} is changed, ops need to be re-built.
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# nv_library(ops
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# SRCS
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# ops.cu
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# DEPS
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# tensor)
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function(nv_library TARGET_NAME)
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set(options OPTIONAL)
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set(oneValueArgs "")
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set(multiValueArgs SRCS DEPS)
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cmake_parse_arguments(nv_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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if (${nv_library_OPTIONAL} STREQUAL "SHARED")
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cuda_add_library(${TARGET_NAME} SHARED ${nv_library_SRCS})
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else()
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cuda_add_library(${TARGET_NAME} STATIC ${nv_library_SRCS})
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endif()
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add_dependencies(${TARGET_NAME} ${nv_library_DEPS} ${external_project_dependencies})
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endfunction(nv_library)
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function(nv_binary TARGET_NAME)
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set(options "")
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set(oneValueArgs "")
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set(multiValueArgs SRCS DEPS)
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cmake_parse_arguments(nv_binary "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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cuda_add_executable(${TARGET_NAME} ${nv_binary_SRCS})
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add_dependencies(${TARGET_NAME} ${nv_binary_DEPS} ${external_project_dependencies})
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target_link_libraries(${TARGET_NAME} ${nv_binary_DEPS})
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endfunction(nv_binary)
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# The dependency to target tensor implies that if any of
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# ops{.h,.cu,_test.cu} is changed, ops_test need to be re-built.
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# nv_test(ops_test
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# SRCS
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# ops_test.cu
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# DEPS
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# ops)
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function(nv_test TARGET_NAME)
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set(options "")
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set(oneValueArgs "")
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set(multiValueArgs SRCS DEPS)
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cmake_parse_arguments(nv_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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cuda_add_executable(${TARGET_NAME} ${nv_test_SRCS})
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add_dependencies(${TARGET_NAME} ${nv_test_DEPS} ${external_project_dependencies})
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target_link_libraries(${TARGET_NAME} ${nv_test_DEPS} ${GTEST_MAIN_LIBRARIES} ${GTEST_LIBRARIES})
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add_test(${TARGET_NAME} ${TARGET_NAME})
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endfunction(nv_test)
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@ -1,10 +1,7 @@
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file(GLOB_RECURSE ALL_TEST_FILES RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.cc")
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cc_test(place_test
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SRCS place_test.cc
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DEPS majel)
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add_executable(majel_tests ${ALL_TEST_FILES})
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if(WITH_GPU)
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add_dependencies(majel_tests majel)
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nv_test(cuda_test SRCS cuda_test.cu)
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target_link_libraries(majel_tests
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endif()
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${GTEST_LIBRARIES}
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${GTEST_MAIN_LIBRARIES}
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majel
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)
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add_test(majel_tests majel_tests)
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#include <cuda_runtime.h>
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#include <stdio.h>
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#include "gtest/gtest.h"
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#define CHECK_ERR(x) \
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if (x != cudaSuccess) { \
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fprintf(stderr, \
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"%s in %s at line %d\n", \
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cudaGetErrorString(err), \
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__FILE__, \
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__LINE__); \
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exit(-1); \
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}
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__global__ void vecAdd(float *d_A, float *d_B, float *d_C, int n) {
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int i = blockDim.x * blockIdx.x + threadIdx.x;
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if (i < n) {
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d_C[i] = d_A[i] + d_B[i];
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}
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}
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TEST(Cuda, Equality) {
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int n = 10;
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// Memory allocation for h_A, h_B and h_C (in the host)
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float h_A[10] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 0.0};
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float h_B[10] = {0.0, 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0};
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float h_C[10];
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float *d_A, *d_B, *d_C;
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cudaError_t err;
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// Memory allocation for d_A, d_B and d_C (in the device)
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err = cudaMalloc((void **)&d_A, sizeof(float) * n);
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CHECK_ERR(err);
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err = cudaMalloc((void **)&d_B, sizeof(float) * n);
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CHECK_ERR(err);
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err = cudaMalloc((void **)&d_C, sizeof(float) * n);
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CHECK_ERR(err);
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// Copying memory to device
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err = cudaMemcpy(d_A, h_A, sizeof(float) * n, cudaMemcpyHostToDevice);
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CHECK_ERR(err);
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err = cudaMemcpy(d_B, h_B, sizeof(float) * n, cudaMemcpyHostToDevice);
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CHECK_ERR(err);
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// Calling the kernel
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vecAdd<<<ceil(n / 256.0), 256>>>(d_A, d_B, d_C, n);
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// Copying results back to host
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err = cudaMemcpy(h_C, d_C, sizeof(float) * n, cudaMemcpyDeviceToHost);
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CHECK_ERR(err);
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EXPECT_EQ(h_C[0], 1.0);
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for (int i = 1; i < n - 1; ++i) {
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EXPECT_EQ(h_C[i], 11.0);
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}
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EXPECT_EQ(h_C[9], 1.0);
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}
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