Browse Source

Added first signs of the CUDA Extension for Storm.

Former-commit-id: b02385cd82
tempestpy_adaptions
PBerger 11 years ago
parent
commit
d5828043de
  1. 334
      resources/cudaForStorm/CMakeLists.txt
  2. 124
      resources/cudaForStorm/src/cudaTests.h
  3. 62
      resources/cudaForStorm/src/main.cpp
  4. 4
      resources/cudaForStorm/srcCuda/allCudaKernels.h
  5. 0
      resources/cudaForStorm/srcCuda/bandWidth.cu
  6. 0
      resources/cudaForStorm/srcCuda/bandWidth.h
  7. 286
      resources/cudaForStorm/srcCuda/basicAdd.cu
  8. 9
      resources/cudaForStorm/srcCuda/basicAdd.h
  9. 39
      resources/cudaForStorm/srcCuda/kernelSwitchTest.cu
  10. 1
      resources/cudaForStorm/srcCuda/kernelSwitchTest.h
  11. 19
      resources/cudaForStorm/srcCuda/utility.cu
  12. 3
      resources/cudaForStorm/srcCuda/utility.h

334
resources/cudaForStorm/CMakeLists.txt

@ -0,0 +1,334 @@
cmake_minimum_required (VERSION 2.8.6)
# Set project name
project (cudaForStorm CXX C)
# Set the version number
set (STORM_CPP_VERSION_MAJOR 1)
set (STORM_CPP_VERSION_MINOR 0)
# Add base folder for better inclusion paths
include_directories("${PROJECT_SOURCE_DIR}")
include_directories("${PROJECT_SOURCE_DIR}/src")
message(STATUS "CUDA_PATH is ${CUDA_PATH} or $ENV{CUDA_PATH}")
#############################################################
##
## CMake options of StoRM
##
#############################################################
option(DEBUG "Sets whether the DEBUG mode is used" ON)
option(USE_POPCNT "Sets whether the popcnt instruction is going to be used." ON)
option(LINK_LIBCXXABI "Sets whether libc++abi should be linked." OFF)
option(USE_LIBCXX "Sets whether the standard library is libc++." OFF)
option(ENABLE_GLPK "Sets whether StoRM is built with support for glpk." OFF)
set(GUROBI_ROOT "" CACHE STRING "The root directory of Gurobi (if available).")
set(Z3_ROOT "" CACHE STRING "The root directory of Z3 (if available).")
set(ADDITIONAL_INCLUDE_DIRS "" CACHE STRING "Additional directories added to the include directories.")
set(ADDITIONAL_LINK_DIRS "" CACHE STRING "Additional directories added to the link directories.")
#############################################################
##
## Inclusion of required libraries
##
#############################################################
# Add the resources/cmake folder to Module Search Path for FindTBB.cmake
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${PROJECT_SOURCE_DIR}/../cmake/")
find_package(CUDA REQUIRED)
find_package(Doxygen REQUIRED)
find_package(Threads REQUIRED)
# If the DEBUG option was turned on, we will target a debug version and a release version otherwise
if (DEBUG)
set (CMAKE_BUILD_TYPE "DEBUG")
else()
set (CMAKE_BUILD_TYPE "RELEASE")
endif()
message(STATUS "StoRM - Building ${CMAKE_BUILD_TYPE} version.")
if ("${GUROBI_ROOT}" STREQUAL "")
set(ENABLE_GUROBI OFF)
else()
set(ENABLE_GUROBI ON)
endif()
if ("${Z3_ROOT}" STREQUAL "")
set(ENABLE_Z3 OFF)
else()
set(ENABLE_Z3 ON)
set(Z3_LIB_NAME "z3")
endif()
message(STATUS "StoRM - CMAKE_BUILD_TYPE: ${CMAKE_BUILD_TYPE}")
message(STATUS "StoRM - CMAKE_BUILD_TYPE (ENV): $ENV{CMAKE_BUILD_TYPE}")
#############################################################
##
## CUDA Options
##
#############################################################
SET (CUDA_VERBOSE_BUILD ON CACHE BOOL "nvcc verbose" FORCE)
set(CUDA_ATTACH_VS_BUILD_RULE_TO_CUDA_FILE ON)
set(BUILD_SHARED_LIBS OFF)
set(CUDA_SEPARABLE_COMPILATION ON)
#set(CUDA_NVCC_FLAGS "-arch=sm_30")
#############################################################
##
## Compiler specific settings and definitions
##
#############################################################
# Path to the no-strict-aliasing target
set(CONVERSIONHELPER_TARGET "${PROJECT_SOURCE_DIR}/src/utility/ConversionHelper.cpp")
if(CMAKE_COMPILER_IS_GNUCC)
message(STATUS "StoRM - Using Compiler Configuration: GCC")
# Set standard flags for GCC
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -funroll-loops")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -Wall -pedantic")
# -Werror is atm removed as this gave some problems with existing code
# May be re-set later
# (Thomas Heinemann, 2012-12-21)
# Turn on popcnt instruction if desired (yes by default)
if (USE_POPCNT)
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mpopcnt")
endif(USE_POPCNT)
# Set the no-strict-aliasing target for GCC
set_source_files_properties(${CONVERSIONHELPER_TARGET} PROPERTIES COMPILE_FLAGS " -fno-strict-aliasing ")
elseif(MSVC)
message(STATUS "StoRM - Using Compiler Configuration: MSVC")
# required for GMM to compile, ugly error directive in their code
add_definitions(/D_SCL_SECURE_NO_DEPRECATE /D_CRT_SECURE_NO_WARNINGS)
# required as the PRCTL Parser bloats object files (COFF) beyond their maximum size (see http://msdn.microsoft.com/en-us/library/8578y171(v=vs.110).aspx)
add_definitions(/bigobj)
# required by GTest and PrismGrammar::createIntegerVariable
add_definitions(/D_VARIADIC_MAX=10)
# Windows.h breaks GMM in gmm_except.h because of its macro definition for min and max
add_definitions(/DNOMINMAX)
if(ENABLE_Z3)
set(Z3_LIB_NAME "libz3")
endif()
# MSVC does not do strict-aliasing, so no option needed
else(CLANG)
message(STATUS "StoRM - Using Compiler Configuration: Clang (LLVM)")
# As CLANG is not set as a variable, we need to set it in case we have not matched another compiler.
set (CLANG ON)
# Set standard flags for clang
set (CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -funroll-loops -O3")
if(UNIX AND NOT APPLE AND NOT USE_LIBCXX)
set(CLANG_STDLIB libstdc++)
message(STATUS "StoRM - Linking against libstdc++")
else()
set(CLANG_STDLIB libc++)
message(STATUS "StoRM - Linking against libc++")
# Disable Cotire
set(STORM_USE_COTIRE OFF)
# Set up some Xcode specific settings
set(CMAKE_XCODE_ATTRIBUTE_CLANG_CXX_LANGUAGE_STANDARD "c++11")
set(CMAKE_XCODE_ATTRIBUTE_CLANG_CXX_LIBRARY "libc++")
endif()
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -stdlib=${CLANG_STDLIB} -Wall -pedantic -Wno-unused-variable -DBOOST_RESULT_OF_USE_TR1 -DBOOST_NO_DECLTYPE -ftemplate-depth=1024")
set (CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -g")
# Turn on popcnt instruction if desired (yes by default)
if (USE_POPCNT)
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mpopcnt")
endif(USE_POPCNT)
# Set the no-strict-aliasing target for Clang
set_source_files_properties(${CONVERSIONHELPER_TARGET} PROPERTIES COMPILE_FLAGS " -fno-strict-aliasing ")
endif()
#############################################################
##
## CMake-generated Config File for StoRM
##
#############################################################
# Base path for test files
set(STORM_CPP_TESTS_BASE_PATH "${PROJECT_SOURCE_DIR}/test")
# Gurobi Defines
if (ENABLE_GUROBI)
set(STORM_CPP_GUROBI_DEF "define")
else()
set(STORM_CPP_GUROBI_DEF "undef")
endif()
# glpk defines
if (ENABLE_GLPK)
set(STORM_CPP_GLPK_DEF "define")
else()
set(STORM_CPP_GLPK_DEF "undef")
endif()
# Z3 Defines
if (ENABLE_Z3)
set(STORM_CPP_Z3_DEF "define")
else()
set(STORM_CPP_Z3_DEF "undef")
endif()
# Intel TBB Defines
if (TBB_FOUND AND ENABLE_INTELTBB)
set(STORM_CPP_INTELTBB_DEF "define")
else()
set(STORM_CPP_INTELTBB_DEF "undef")
endif()
# Configure a header file to pass some of the CMake settings to the source code
configure_file (
"${PROJECT_SOURCE_DIR}/../../storm-config.h.in"
"${PROJECT_BINARY_DIR}/include/storm-config.h"
)
# Add the binary dir include directory for storm-config.h
include_directories("${PROJECT_BINARY_DIR}/include")
# Add the main source directory for includes
include_directories("${PROJECT_SOURCE_DIR}/../../src")
#############################################################
##
## Source file aggregation and clustering
##
#############################################################
file(GLOB_RECURSE CUDAFORSTORM_HEADERS ${PROJECT_SOURCE_DIR}/src/*.h)
file(GLOB_RECURSE CUDAFORSTORM_SOURCES ${PROJECT_SOURCE_DIR}/src/*.cpp)
file(GLOB_RECURSE CUDAFORSTORM_CUDA_SOURCES "${PROJECT_SOURCE_DIR}/srcCuda/*.cu")
file(GLOB_RECURSE CUDAFORSTORM_CUDA_HEADERS "${PROJECT_SOURCE_DIR}/srcCuda/*.h")
# Additional include files like the storm-config.h
file(GLOB_RECURSE STORM_BUILD_HEADERS ${PROJECT_BINARY_DIR}/include/*.h)
# Group the headers and sources
source_group(main FILES ${CUDAFORSTORM_HEADERS} ${CUDAFORSTORM_SOURCES})
source_group(cuda FILES ${CUDAFORSTORM_CUDA_SOURCES} ${CUDAFORSTORM_CUDA_HEADERS})
# Add custom additional include or link directories
if (ADDITIONAL_INCLUDE_DIRS)
message(STATUS "StoRM - Using additional include directories ${ADDITIONAL_INCLUDE_DIRS}")
include_directories(${ADDITIONAL_INCLUDE_DIRS})
endif(ADDITIONAL_INCLUDE_DIRS)
if (ADDITIONAL_LINK_DIRS)
message(STATUS "StoRM - Using additional link directories ${ADDITIONAL_LINK_DIRS}")
link_directories(${ADDITIONAL_LINK_DIRS})
endif(ADDITIONAL_LINK_DIRS)
#############################################################
##
## Pre executable-creation link_directories setup
##
#############################################################
if (ENABLE_GUROBI)
link_directories("${GUROBI_ROOT}/lib")
endif()
if (ENABLE_Z3)
link_directories("${Z3_ROOT}/bin")
endif()
if ((NOT Boost_LIBRARY_DIRS) OR ("${Boost_LIBRARY_DIRS}" STREQUAL ""))
set(Boost_LIBRARY_DIRS "${Boost_INCLUDE_DIRS}/stage/lib")
endif ()
link_directories(${Boost_LIBRARY_DIRS})
if (TBB_FOUND AND ENABLE_INTELTBB)
link_directories(${TBB_LIBRARY_DIRS})
endif()
###############################################################################
## #
## Executable Creation #
## #
## All link_directories() calls MUST be made before this point #
## #
###############################################################################
# Since this will be a library
include (GenerateExportHeader)
add_library(cudaForStorm STATIC ${CUDAFORSTORM_HEADERS} ${CUDAFORSTORM_SOURCES})
GENERATE_EXPORT_HEADER( cudaForStorm
BASE_NAME cudaForStorm
EXPORT_MACRO_NAME cudaForStorm_EXPORT
EXPORT_FILE_NAME cudaForStorm_Export.h
STATIC_DEFINE cudaForStorm_BUILT_AS_STATIC
)
#############################################################
##
## CUDA
##
#############################################################
#set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} --gpu-architecture sm_30)
cuda_add_library(cudaLibrary
${CUDAFORSTORM_CUDA_SOURCES} ${CUDAFORSTORM_CUDA_HEADERS}
OPTIONS -DSTUFF="" -arch=sm_30
RELEASE -DNDEBUG
DEBUG -g -DDEBUG
)
target_link_libraries(cudaLibrary ${CUDA_cusparse_LIBRARY})
ADD_DEPENDENCIES(cudaForStorm cudaLibrary)
target_link_libraries(cudaForStorm cudaLibrary)
message(STATUS "Found CUDA SDK in Version ${CUDA_VERSION_STRING}, sparse lib is ${CUDA_cusparse_LIBRARY}")
include_directories(${CUDA_INCLUDE_DIRS})
#############################################################
##
## Gurobi (optional)
##
#############################################################
if (ENABLE_GUROBI)
message (STATUS "StoRM - Linking with Gurobi")
include_directories("${GUROBI_ROOT}/include")
target_link_libraries(cudaForStorm "gurobi56")
endif(ENABLE_GUROBI)
#############################################################
##
## glpk (optional)
##
#############################################################
if (ENABLE_GLPK)
message (STATUS "StoRM - Linking with glpk")
target_link_libraries(cudaForStorm "glpk")
endif(ENABLE_GLPK)
#############################################################
##
## Z3 (optional)
##
#############################################################
if (ENABLE_Z3)
message (STATUS "StoRM - Linking with Z3")
include_directories("${Z3_ROOT}/include")
target_link_libraries(cudaForStorm ${Z3_LIB_NAME})
endif(ENABLE_Z3)
#############################################################
##
## Threads
##
#############################################################
include_directories(${THREADS_INCLUDE_DIRS})
target_link_libraries(cudaForStorm ${CMAKE_THREAD_LIBS_INIT})
if (MSVC)
# Add the DebugHelper DLL
set(CMAKE_CXX_STANDARD_LIBRARIES "${CMAKE_CXX_STANDARD_LIBRARIES} Dbghelp.lib")
target_link_libraries(cudaForStorm "Dbghelp.lib")
endif(MSVC)
# Link against libc++abi if requested. May be needed to build on Linux systems using clang.
if (LINK_LIBCXXABI)
message (STATUS "StoRM - Linking against libc++abi.")
target_link_libraries(storm "c++abi")
target_link_libraries(storm-functional-tests "c++abi")
target_link_libraries(storm-performance-tests "c++abi")
endif(LINK_LIBCXXABI)

124
resources/cudaForStorm/src/cudaTests.h

@ -0,0 +1,124 @@
#include <cuda.h>
#include "srcCuda/allCudaKernels.h"
#include <iostream>
#include <chrono>
#include <random>
void cudaShowDevices() {
// Todo
}
void cudaSimpleAddTest(int a, int b) {
std::cout << "Running cudaSimpleAddTest:" << std::endl;
std::cout << "a = " << a << ", b = " << b << "" << std::endl;
int c = cuda_basicAdd(a, b);
std::cout << "Result: " << c << "" << std::endl;
}
void cudaArrayFmaTest(int N) {
std::cout << "Running cudaArrayFmaTest:" << std::endl;
std::cout << "N is " << N << ", resulting in " << (5 * sizeof(int) * N) << " Bytes of Data." << std::endl;
std::cout << "Generating random input arrays." << std::endl;
std::default_random_engine generator;
std::uniform_int_distribution<int> distribution(0, INT32_MAX);
int dice_roll = distribution(generator);
auto start_time = std::chrono::high_resolution_clock::now();
int* arrayA = new int[N];
int* arrayB = new int[N];
int* arrayC = new int[N];
int* arrayD = new int[N];
int* arrayD_CPU = new int[N];
for (int i = 0; i < N; ++i) {
//arrayA[i] = distribution(generator);
//arrayB[i] = distribution(generator);
//arrayC[i] = distribution(generator);
arrayA[i] = i * 1000 + 137;
arrayB[i] = i * 7000 + 1537;
arrayC[i] = i * 15000 + 97;
arrayD[i] = 0;
arrayD_CPU[i] = 0;
}
auto end_time = std::chrono::high_resolution_clock::now();
std::cout << "Array generation took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
std::cout << "Running FMA test on CPU." << std::endl;
start_time = std::chrono::high_resolution_clock::now();
cuda_arrayFmaHelper(arrayA, arrayB, arrayC, arrayD_CPU, N);
end_time = std::chrono::high_resolution_clock::now();
std::cout << "FMA on CPU took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
start_time = std::chrono::high_resolution_clock::now();
cuda_arrayFma(arrayA, arrayB, arrayC, arrayD, N);
end_time = std::chrono::high_resolution_clock::now();
std::cout << "FMA on GPU took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
int errors = 0;
for (int i = 0; i < N; ++i) {
if (arrayD[i] != arrayD_CPU[i]) {
std::cout << "Error in Entry " << i << ": GPU has " << arrayD[i] << " but CPU has " << arrayD_CPU[i] << "!" << std::endl;
++errors;
}
}
std::cout << "Checked Arrays for Errors: " << errors << " Errors occured." << std::endl;
}
void cudaArrayFmaOptimizedTest(int N, int M) {
std::cout << "Running cudaArrayFmaTest:" << std::endl;
std::cout << "N is " << N << ", resulting in " << (4 * sizeof(int) * N) << " Bytes of Data." << std::endl;
size_t freeCudaMemory = getFreeCudaMemory();
size_t totalCudaMemory = getTotalCudaMemory();
int freeProzent = static_cast<int>(((double)freeCudaMemory)/((double)totalCudaMemory) * 100);
std::cout << "CUDA Device has " << freeCudaMemory << " Bytes of " << totalCudaMemory << " Bytes free (" << (freeProzent) << "%)." << std::endl;
std::cout << "Generating random input arrays." << std::endl;
std::default_random_engine generator;
std::uniform_int_distribution<int> distribution(0, INT32_MAX);
auto start_time = std::chrono::high_resolution_clock::now();
int* arrayA = new int[4 * N];
int* arrayA_CPU = new int[4 * N];
for (int i = 0; i < 4*N; ++i) {
arrayA[i] = i * 1000 + i + (357854878 % (i+1));
arrayA_CPU[i] = arrayA[i];
}
auto end_time = std::chrono::high_resolution_clock::now();
std::cout << "Array generation took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
start_time = std::chrono::high_resolution_clock::now();
cuda_arrayFmaOptimizedHelper(arrayA_CPU, N);
end_time = std::chrono::high_resolution_clock::now();
std::cout << "FMA on CPU took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
start_time = std::chrono::high_resolution_clock::now();
cuda_arrayFmaOptimized(arrayA, N, M);
end_time = std::chrono::high_resolution_clock::now();
std::cout << "FMA on GPU took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
int errors = 0;
for (int i = 0; i < N; i+=4) {
if (arrayA[i+3] != arrayA_CPU[i+3]) {
//std::cout << "Error in Entry " << i << ": GPU has " << arrayA[i+3] << " but CPU has " << arrayA_CPU[i+3] << "!" << std::endl;
++errors;
}
}
std::cout << "Checked Arrays for Errors: " << errors << " Errors occured." << std::endl;
delete[] arrayA;
delete[] arrayA_CPU;
}

62
resources/cudaForStorm/src/main.cpp

@ -0,0 +1,62 @@
#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#include <chrono>
#include <random>
#include "cudaTests.h"
int main(int argc, char **argv){
resetCudaDevice();
int testNumber = 0;
int N = 10000;
int M = 402653184;
if (argc > 1) {
testNumber = atoi(argv[1]);
if (argc > 2) {
N = atoi(argv[2]);
if (argc > 3) {
M = atoi(argv[3]);
}
}
}
switch (testNumber) {
case 1:
cudaSimpleAddTest(N, M);
break;
case 2:
cudaArrayFmaTest(N);
break;
case 3:
cudaArrayFmaOptimizedTest(N, M);
break;
case 4:
cpp_cuda_bandwidthTest(M, N);
break;
case 5:
kernelSwitchTest(N);
break;
break;
// DEFAULT AND 0
case 0:
default:
std::cout << "Available functions are:" << std::endl;
std::cout << "0 - Show this overview" << std::endl;
std::cout << "1 - cuda simpleAddTest(N, M)" << std::endl;
std::cout << "2 - cuda arrayFmaTest(N)" << std::endl;
std::cout << "3 - cuda arrayFmaOptimizedTest(N, M)" << std::endl;
std::cout << "4 - cuda bandwidthTest(M, N)" << std::endl;
std::cout << "5 - cuda kernelSwitchTest(N)" << std::endl;
std::cout << std::endl;
std::cout << "Call: " << argv[0] << " Selection [N [M]]" << std::endl;
std::cout << "Defaults:" <<std::endl;
std::cout << "N: 10000" << std::endl;
std::cout << "M: 402653184" << std::endl;
break;
}
return 0;
}

4
resources/cudaForStorm/srcCuda/allCudaKernels.h

@ -0,0 +1,4 @@
#include "utility.h"
#include "bandWidth.h"
#include "basicAdd.h"
#include "kernelSwitchTest.h"

0
resources/cudaForStorm/srcCuda/bandWidth.cu

0
resources/cudaForStorm/srcCuda/bandWidth.h

286
resources/cudaForStorm/srcCuda/basicAdd.cu

@ -0,0 +1,286 @@
#include <cuda.h>
#include <stdlib.h>
#include <stdio.h>
#include <chrono>
#include <iostream>
__global__ void cuda_kernel_basicAdd(int a, int b, int *c) {
*c = a + b;
}
__global__ void cuda_kernel_arrayFma(int const * const A, int const * const B, int const * const C, int * const D, int const N) {
// Fused Multiply Add:
// A * B + C => D
/*
*Die Variable i dient für den Zugriff auf das Array. Da jeder Thread die Funktion VecAdd
*ausführt, muss i für jeden Thread unterschiedlich sein. Ansonsten würden unterschiedliche
*Threads auf denselben Index im Array schreiben. blockDim.x ist die Anzahl der Threads der x-Komponente
*des Blocks, blockIdx.x ist die x-Koordinate des aktuellen Blocks und threadIdx.x ist die x-Koordinate des
*Threads, der die Funktion gerade ausführt.
*/
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < N) {
D[i] = A[i] * B[i] + C[i];
}
}
__global__ void cuda_kernel_arrayFmaOptimized(int * const A, int const N, int const M) {
// Fused Multiply Add:
// A * B + C => D
// Layout:
// A B C D A B C D A B C D
int i = blockDim.x * blockIdx.x + threadIdx.x;
if ((i*M) < N) {
for (int j = i*M; j < i*M + M; ++j) {
A[j*4 + 3] = A[j*4] * A[j*4 + 1] + A[j*4 + 2];
}
}
}
extern "C" int cuda_basicAdd(int a, int b) {
int c = 0;
int *dev_c;
cudaMalloc((void**)&dev_c, sizeof(int));
cuda_kernel_basicAdd<<<1, 1>>>(a, b, dev_c);
cudaMemcpy(&c, dev_c, sizeof(int), cudaMemcpyDeviceToHost);
//printf("%d + %d + 42 is %d\n", a, b, c);
cudaFree(dev_c);
return c;
}
void cpp_cuda_bandwidthTest(int entryCount, int N) {
// Size of the Arrays
size_t arraySize = entryCount * sizeof(int);
int* deviceIntArray;
int* hostIntArray = new int[arraySize];
// Allocate space on the device
auto start_time = std::chrono::high_resolution_clock::now();
for (int i = 0; i < N; ++i) {
if (cudaMalloc((void**)&deviceIntArray, arraySize) != cudaSuccess) {
std::cout << "Error in cudaMalloc while allocating " << arraySize << " Bytes!" << std::endl;
delete[] hostIntArray;
return;
}
// Free memory on device
if (cudaFree(deviceIntArray) != cudaSuccess) {
std::cout << "Error in cudaFree!" << std::endl;
delete[] hostIntArray;
return;
}
}
auto end_time = std::chrono::high_resolution_clock::now();
auto copyTime = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count();
double mBytesPerSecond = (((double)(N * arraySize)) / copyTime) * 0.95367431640625;
std::cout << "Allocating the Array " << N << " times took " << copyTime << " Microseconds." << std::endl;
std::cout << "Resulting in " << mBytesPerSecond << " MBytes per Second Allocationspeed." << std::endl;
if (cudaMalloc((void**)&deviceIntArray, arraySize) != cudaSuccess) {
std::cout << "Error in cudaMalloc while allocating " << arraySize << " Bytes for copyTest!" << std::endl;
delete[] hostIntArray;
return;
}
// Prepare data
for (int i = 0; i < N; ++i) {
hostIntArray[i] = i * 333 + 123;
}
// Copy data TO device
start_time = std::chrono::high_resolution_clock::now();
for (int i = 0; i < N; ++i) {
if (cudaMemcpy(deviceIntArray, hostIntArray, arraySize, cudaMemcpyHostToDevice) != cudaSuccess) {
std::cout << "Error in cudaMemcpy while copying " << arraySize << " Bytes to device!" << std::endl;
// Free memory on device
if (cudaFree(deviceIntArray) != cudaSuccess) {
std::cout << "Error in cudaFree!" << std::endl;
}
delete[] hostIntArray;
return;
}
}
end_time = std::chrono::high_resolution_clock::now();
copyTime = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count();
mBytesPerSecond = (((double)(N * arraySize)) / copyTime) * 0.95367431640625;
std::cout << "Copying the Array " << N << " times took " << copyTime << " Microseconds." << std::endl;
std::cout << "Resulting in " << mBytesPerSecond << " MBytes per Second TO device." << std::endl;
// Copy data FROM device
start_time = std::chrono::high_resolution_clock::now();
for (int i = 0; i < N; ++i) {
if (cudaMemcpy(hostIntArray, deviceIntArray, arraySize, cudaMemcpyDeviceToHost) != cudaSuccess) {
std::cout << "Error in cudaMemcpy while copying " << arraySize << " Bytes to host!" << std::endl;
// Free memory on device
if (cudaFree(deviceIntArray) != cudaSuccess) {
std::cout << "Error in cudaFree!" << std::endl;
}
delete[] hostIntArray;
return;
}
}
end_time = std::chrono::high_resolution_clock::now();
copyTime = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count();
mBytesPerSecond = (((double)(N * arraySize)) / copyTime) * 0.95367431640625;
std::cout << "Copying the Array " << N << " times took " << copyTime << " Microseconds." << std::endl;
std::cout << "Resulting in " << mBytesPerSecond << " MBytes per Second FROM device." << std::endl;
// Free memory on device
if (cudaFree(deviceIntArray) != cudaSuccess) {
std::cout << "Error in cudaFree!" << std::endl;
}
delete[] hostIntArray;
}
extern "C" void cuda_arrayFma(int const * const A, int const * const B, int const * const C, int * const D, int const N) {
// Size of the Arrays
size_t arraySize = N * sizeof(int);
int* deviceIntArrayA;
int* deviceIntArrayB;
int* deviceIntArrayC;
int* deviceIntArrayD;
// Allocate space on the device
if (cudaMalloc((void**)&deviceIntArrayA, arraySize) != cudaSuccess) {
printf("Error in cudaMalloc1!\n");
return;
}
if (cudaMalloc((void**)&deviceIntArrayB, arraySize) != cudaSuccess) {
printf("Error in cudaMalloc2!\n");
cudaFree(deviceIntArrayA);
return;
}
if (cudaMalloc((void**)&deviceIntArrayC, arraySize) != cudaSuccess) {
printf("Error in cudaMalloc3!\n");
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
return;
}
if (cudaMalloc((void**)&deviceIntArrayD, arraySize) != cudaSuccess) {
printf("Error in cudaMalloc4!\n");
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
cudaFree(deviceIntArrayC);
return;
}
// Copy data TO device
if (cudaMemcpy(deviceIntArrayA, A, arraySize, cudaMemcpyHostToDevice) != cudaSuccess) {
printf("Error in cudaMemcpy!\n");
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
cudaFree(deviceIntArrayC);
cudaFree(deviceIntArrayD);
return;
}
if (cudaMemcpy(deviceIntArrayB, B, arraySize, cudaMemcpyHostToDevice) != cudaSuccess) {
printf("Error in cudaMemcpy!\n");
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
cudaFree(deviceIntArrayC);
cudaFree(deviceIntArrayD);
return;
}
if (cudaMemcpy(deviceIntArrayC, C, arraySize, cudaMemcpyHostToDevice) != cudaSuccess) {
printf("Error in cudaMemcpy!\n");
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
cudaFree(deviceIntArrayC);
cudaFree(deviceIntArrayD);
return;
}
// Festlegung der Threads pro Block
int threadsPerBlock = 512;
// Es werden soviele Blöcke benötigt, dass alle Elemente der Vektoren abgearbeitet werden können
int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
// Run kernel
cuda_kernel_arrayFma<<<blocksPerGrid, threadsPerBlock>>>(deviceIntArrayA, deviceIntArrayB, deviceIntArrayC, deviceIntArrayD, N);
// Copy data FROM device
if (cudaMemcpy(D, deviceIntArrayD, arraySize, cudaMemcpyDeviceToHost) != cudaSuccess) {
printf("Error in cudaMemcpy!\n");
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
cudaFree(deviceIntArrayC);
cudaFree(deviceIntArrayD);
return;
}
// Free memory on device
cudaFree(deviceIntArrayA);
cudaFree(deviceIntArrayB);
cudaFree(deviceIntArrayC);
cudaFree(deviceIntArrayD);
}
extern "C" void cuda_arrayFmaOptimized(int * const A, int const N, int const M) {
// Size of the Arrays
size_t arraySize = N * sizeof(int) * 4;
int* deviceIntArrayA;
// Allocate space on the device
if (cudaMalloc((void**)&deviceIntArrayA, arraySize) != cudaSuccess) {
printf("Error in cudaMalloc1!\n");
return;
}
#define ONFAILFREE0() do { } while(0)
#define ONFAILFREE1(a) do { cudaFree(a); } while(0)
#define ONFAILFREE2(a, b) do { cudaFree(a); cudaFree(b); } while(0)
#define ONFAILFREE3(a, b, c) do { cudaFree(a); cudaFree(b); cudaFree(c); } while(0)
#define ONFAILFREE4(a, b, c, d) do { cudaFree(a); cudaFree(b); cudaFree(c); cudaFree(d); } while(0)
#define CHECKED_CUDA_CALL(func__, freeArgs, ...) do { int retCode = cuda##func__ (__VA_ARGS__); if (retCode != cudaSuccess) { freeArgs; printf("Error in func__!\n"); return; } } while(0)
// Copy data TO device
CHECKED_CUDA_CALL(Memcpy, ONFAILFREE1(deviceIntArrayA), deviceIntArrayA, A, arraySize, cudaMemcpyHostToDevice);
/*if (cudaMemcpy(deviceIntArrayA, A, arraySize, cudaMemcpyHostToDevice) != cudaSuccess) {
printf("Error in cudaMemcpy!\n");
cudaFree(deviceIntArrayA);
return;
}*/
// Festlegung der Threads pro Block
int threadsPerBlock = 512;
// Es werden soviele Blöcke benötigt, dass alle Elemente der Vektoren abgearbeitet werden können
int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
// Run kernel
cuda_kernel_arrayFmaOptimized<<<blocksPerGrid, threadsPerBlock>>>(deviceIntArrayA, N, M);
// Copy data FROM device
if (cudaMemcpy(A, deviceIntArrayA, arraySize, cudaMemcpyDeviceToHost) != cudaSuccess) {
printf("Error in cudaMemcpy!\n");
cudaFree(deviceIntArrayA);
return;
}
// Free memory on device
if (cudaFree(deviceIntArrayA) != cudaSuccess) {
printf("Error in cudaFree!\n");
return;
}
}
extern "C" void cuda_arrayFmaHelper(int const * const A, int const * const B, int const * const C, int * const D, int const N) {
for (int i = 0; i < N; ++i) {
D[i] = A[i] * B[i] + C[i];
}
}
extern "C" void cuda_arrayFmaOptimizedHelper(int * const A, int const N) {
for (int i = 0; i < N; i += 4) {
A[i+3] = A[i] * A[i+1] + A[i+2];
}
}

9
resources/cudaForStorm/srcCuda/basicAdd.h

@ -0,0 +1,9 @@
extern "C" int cuda_basicAdd(int a, int b);
extern "C" void cuda_arrayFmaOptimized(int * const A, int const N, int const M);
extern "C" void cuda_arrayFmaOptimizedHelper(int * const A, int const N);
extern "C" void cuda_arrayFma(int const * const A, int const * const B, int const * const C, int * const D, int const N);
extern "C" void cuda_arrayFmaHelper(int const * const A, int const * const B, int const * const C, int * const D, int const N);
void cpp_cuda_bandwidthTest(int entryCount, int N);

39
resources/cudaForStorm/srcCuda/kernelSwitchTest.cu

@ -0,0 +1,39 @@
#include <iostream>
#include <chrono>
__global__ void cuda_kernel_kernelSwitchTest(int const * const A, int * const B) {
*B = *A;
}
void kernelSwitchTest(size_t N) {
int* deviceIntA;
int* deviceIntB;
if (cudaMalloc((void**)&deviceIntA, sizeof(int)) != cudaSuccess) {
std::cout << "Error in cudaMalloc while allocating " << sizeof(int) << " Bytes!" << std::endl;
return;
}
if (cudaMalloc((void**)&deviceIntB, sizeof(int)) != cudaSuccess) {
std::cout << "Error in cudaMalloc while allocating " << sizeof(int) << " Bytes!" << std::endl;
return;
}
// Allocate space on the device
auto start_time = std::chrono::high_resolution_clock::now();
for (int i = 0; i < N; ++i) {
cuda_kernel_kernelSwitchTest<<<1,1>>>(deviceIntA, deviceIntB);
}
auto end_time = std::chrono::high_resolution_clock::now();
std::cout << "Switching the Kernel " << N << " times took " << std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << "micros" << std::endl;
std::cout << "Resulting in " << (std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() / ((double)(N))) << "Microseconds per Kernel Switch" << std::endl;
// Free memory on device
if (cudaFree(deviceIntA) != cudaSuccess) {
std::cout << "Error in cudaFree!" << std::endl;
return;
}
if (cudaFree(deviceIntB) != cudaSuccess) {
std::cout << "Error in cudaFree!" << std::endl;
return;
}
}

1
resources/cudaForStorm/srcCuda/kernelSwitchTest.h

@ -0,0 +1 @@
void kernelSwitchTest(size_t N);

19
resources/cudaForStorm/srcCuda/utility.cu

@ -0,0 +1,19 @@
size_t getFreeCudaMemory() {
size_t freeMemory;
size_t totalMemory;
cudaMemGetInfo(&freeMemory, &totalMemory);
return freeMemory;
}
size_t getTotalCudaMemory() {
size_t freeMemory;
size_t totalMemory;
cudaMemGetInfo(&freeMemory, &totalMemory);
return totalMemory;
}
void resetCudaDevice() {
cudaDeviceReset();
}

3
resources/cudaForStorm/srcCuda/utility.h

@ -0,0 +1,3 @@
size_t getFreeCudaMemory();
size_t getTotalCudaMemory();
void resetCudaDevice();
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