Remove old version
This commit is contained in:
Tom Deakin
parent
e91c31b44a
commit
95f9efb7d9
27
Makefile
27
Makefile
@ -1,27 +0,0 @@
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LDLIBS = -l OpenCL
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CXXFLAGS = -std=c++11 -O3
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PLATFORM = $(shell uname -s)
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ifeq ($(PLATFORM), Darwin)
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LDLIBS = -framework OpenCL
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endif
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all: gpu-stream-ocl gpu-stream-cuda
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gpu-stream-ocl: ocl-stream.cpp common.o Makefile
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$(CXX) $(CXXFLAGS) -Wno-deprecated-declarations common.o $< -o $@ $(LDLIBS)
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common.o: common.cpp common.h Makefile
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gpu-stream-cuda: cuda-stream.cu common.o Makefile
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ifeq ($(shell which nvcc > /dev/null; echo $$?), 0)
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nvcc $(CXXFLAGS) common.o $< -o $@
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else
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$(error "Cannot find nvcc, please install CUDA toolkit")
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endif
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.PHONY: clean
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clean:
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rm -f gpu-stream-ocl gpu-stream-cuda *.o
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115
common.cpp
115
common.cpp
@ -1,115 +0,0 @@
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/*=============================================================================
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*------------------------------------------------------------------------------
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* Copyright 2015: Tom Deakin, Simon McIntosh-Smith, University of Bristol HPC
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* Based on John D. McCalpin’s original STREAM benchmark for CPUs
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*------------------------------------------------------------------------------
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* License:
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* 1. You are free to use this program and/or to redistribute
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* this program.
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* 2. You are free to modify this program for your own use,
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* including commercial use, subject to the publication
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* restrictions in item 3.
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* 3. You are free to publish results obtained from running this
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* program, or from works that you derive from this program,
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* with the following limitations:
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* 3a. In order to be referred to as "GPU-STREAM benchmark results",
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* published results must be in conformance to the GPU-STREAM
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* Run Rules published at
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* http://github.com/UoB-HPC/GPU-STREAM/wiki/Run-Rules
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* and incorporated herein by reference.
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* The copyright holders retain the
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* right to determine conformity with the Run Rules.
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* 3b. Results based on modified source code or on runs not in
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* accordance with the GPU-STREAM Run Rules must be clearly
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* labelled whenever they are published. Examples of
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* proper labelling include:
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* "tuned GPU-STREAM benchmark results"
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* "based on a variant of the GPU-STREAM benchmark code"
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* Other comparable, clear and reasonable labelling is
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* acceptable.
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* 3c. Submission of results to the GPU-STREAM benchmark web site
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* is encouraged, but not required.
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* 4. Use of this program or creation of derived works based on this
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* program constitutes acceptance of these licensing restrictions.
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* 5. Absolutely no warranty is expressed or implied.
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*———————————————————————————————————-----------------------------------------*/
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#include "common.h"
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// Default array size 50 * 2^20 (50*8 Mebibytes double precision)
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// Use binary powers of two so divides 1024
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unsigned int ARRAY_SIZE = 52428800;
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unsigned int NTIMES = 10;
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bool useFloat = false;
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unsigned int deviceIndex = 0;
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int parseUInt(const char *str, unsigned int *output)
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{
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char *next;
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*output = strtoul(str, &next, 10);
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return !strlen(next);
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}
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void parseArguments(int argc, char *argv[])
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{
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for (int i = 1; i < argc; i++)
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{
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if (!strcmp(argv[i], "--list"))
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{
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listDevices();
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exit(0);
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}
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else if (!strcmp(argv[i], "--device"))
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{
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if (++i >= argc || !parseUInt(argv[i], &deviceIndex))
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{
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std::cout << "Invalid device index" << std::endl;
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exit(1);
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}
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}
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else if (!strcmp(argv[i], "--arraysize") || !strcmp(argv[i], "-s"))
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{
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if (++i >= argc || !parseUInt(argv[i], &ARRAY_SIZE))
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{
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std::cout << "Invalid array size" << std::endl;
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exit(1);
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}
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}
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else if (!strcmp(argv[i], "--numtimes") || !strcmp(argv[i], "-n"))
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{
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if (++i >= argc || !parseUInt(argv[i], &NTIMES))
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{
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std::cout << "Invalid number of times" << std::endl;
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exit(1);
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}
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}
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else if (!strcmp(argv[i], "--float"))
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{
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useFloat = true;
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std::cout << "Warning: If number of iterations set >= 8, expect rounding errors with single precision" << std::endl;
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}
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else if (!strcmp(argv[i], "--help") || !strcmp(argv[i], "-h"))
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{
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std::cout << std::endl;
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std::cout << "Usage: ./gpu-stream-cuda [OPTIONS]" << std::endl << std::endl;
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std::cout << "Options:" << std::endl;
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std::cout << " -h --help Print the message" << std::endl;
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std::cout << " --list List available devices" << std::endl;
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std::cout << " --device INDEX Select device at INDEX" << std::endl;
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std::cout << " -s --arraysize SIZE Use SIZE elements in the array" << std::endl;
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std::cout << " -n --numtimes NUM Run the test NUM times (NUM >= 2)" << std::endl;
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std::cout << " --float Use floats (rather than doubles)" << std::endl;
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std::cout << std::endl;
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exit(0);
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}
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else
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{
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std::cout << "Unrecognized argument '" << argv[i] << "' (try '--help')"
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<< std::endl;
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exit(1);
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}
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}
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}
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112
common.h
112
common.h
@ -1,112 +0,0 @@
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/*=============================================================================
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*------------------------------------------------------------------------------
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* Copyright 2015: Tom Deakin, Simon McIntosh-Smith, University of Bristol HPC
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* Based on John D. McCalpin’s original STREAM benchmark for CPUs
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*------------------------------------------------------------------------------
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* License:
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* 1. You are free to use this program and/or to redistribute
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* this program.
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* 2. You are free to modify this program for your own use,
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* including commercial use, subject to the publication
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* restrictions in item 3.
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* 3. You are free to publish results obtained from running this
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* program, or from works that you derive from this program,
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* with the following limitations:
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* 3a. In order to be referred to as "GPU-STREAM benchmark results",
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* published results must be in conformance to the GPU-STREAM
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* Run Rules published at
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* http://github.com/UoB-HPC/GPU-STREAM/wiki/Run-Rules
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* and incorporated herein by reference.
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* The copyright holders retain the
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* right to determine conformity with the Run Rules.
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* 3b. Results based on modified source code or on runs not in
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* accordance with the GPU-STREAM Run Rules must be clearly
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* labelled whenever they are published. Examples of
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* proper labelling include:
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* "tuned GPU-STREAM benchmark results"
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* "based on a variant of the GPU-STREAM benchmark code"
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* Other comparable, clear and reasonable labelling is
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* acceptable.
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* 3c. Submission of results to the GPU-STREAM benchmark web site
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* is encouraged, but not required.
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* 4. Use of this program or creation of derived works based on this
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* program constitutes acceptance of these licensing restrictions.
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* 5. Absolutely no warranty is expressed or implied.
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*———————————————————————————————————-----------------------------------------*/
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#include <iomanip>
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#include <iostream>
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#include <cstdlib>
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#include <cstring>
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#include <limits>
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#include <stdexcept>
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#define VERSION_STRING "1.0"
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extern void parseArguments(int argc, char *argv[]);
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extern void listDevices(void);
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extern unsigned int ARRAY_SIZE;
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extern unsigned int NTIMES;
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extern bool useFloat;
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extern unsigned int deviceIndex;
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template < typename T >
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void check_solution(void* a_in, void* b_in, void* c_in)
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{
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// Generate correct solution
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T golda = 1.0;
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T goldb = 2.0;
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T goldc = 0.0;
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T * a = static_cast<T*>(a_in);
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T * b = static_cast<T*>(b_in);
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T * c = static_cast<T*>(c_in);
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const T scalar = 3.0;
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for (unsigned int i = 0; i < NTIMES; i++)
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{
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// Double
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goldc = golda;
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goldb = scalar * goldc;
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goldc = golda + goldb;
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golda = goldb + scalar * goldc;
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}
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// Calculate average error
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double erra = 0.0;
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double errb = 0.0;
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double errc = 0.0;
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for (unsigned int i = 0; i < ARRAY_SIZE; i++)
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{
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erra += fabs(a[i] - golda);
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errb += fabs(b[i] - goldb);
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errc += fabs(c[i] - goldc);
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}
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erra /= ARRAY_SIZE;
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errb /= ARRAY_SIZE;
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errc /= ARRAY_SIZE;
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double epsi = std::numeric_limits<T>::epsilon() * 100;
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if (erra > epsi)
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std::cout
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<< "Validation failed on a[]. Average error " << erra
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<< std::endl;
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if (errb > epsi)
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std::cout
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<< "Validation failed on b[]. Average error " << errb
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<< std::endl;
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if (errc > epsi)
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std::cout
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<< "Validation failed on c[]. Average error " << errc
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<< std::endl;
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}
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397
cuda-stream.cu
397
cuda-stream.cu
@ -1,397 +0,0 @@
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/*=============================================================================
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*------------------------------------------------------------------------------
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* Copyright 2015: Tom Deakin, Simon McIntosh-Smith, University of Bristol HPC
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* Based on John D. McCalpin’s original STREAM benchmark for CPUs
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*------------------------------------------------------------------------------
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* License:
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* 1. You are free to use this program and/or to redistribute
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* this program.
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* 2. You are free to modify this program for your own use,
|
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* including commercial use, subject to the publication
|
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* restrictions in item 3.
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* 3. You are free to publish results obtained from running this
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* program, or from works that you derive from this program,
|
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* with the following limitations:
|
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* 3a. In order to be referred to as "GPU-STREAM benchmark results",
|
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* published results must be in conformance to the GPU-STREAM
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* Run Rules published at
|
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* http://github.com/UoB-HPC/GPU-STREAM/wiki/Run-Rules
|
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* and incorporated herein by reference.
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* The copyright holders retain the
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* right to determine conformity with the Run Rules.
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* 3b. Results based on modified source code or on runs not in
|
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* accordance with the GPU-STREAM Run Rules must be clearly
|
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* labelled whenever they are published. Examples of
|
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* proper labelling include:
|
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* "tuned GPU-STREAM benchmark results"
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* "based on a variant of the GPU-STREAM benchmark code"
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* Other comparable, clear and reasonable labelling is
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* acceptable.
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* 3c. Submission of results to the GPU-STREAM benchmark web site
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* is encouraged, but not required.
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* 4. Use of this program or creation of derived works based on this
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* program constitutes acceptance of these licensing restrictions.
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* 5. Absolutely no warranty is expressed or implied.
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*———————————————————————————————————-----------------------------------------*/
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#include <iostream>
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#include <fstream>
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#include <vector>
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#include <chrono>
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#include <cfloat>
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#include <cmath>
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#include <cuda.h>
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#include "common.h"
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std::string getDeviceName(int device);
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int getDriver(void);
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// Code to check CUDA errors
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void check_cuda_error(void)
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{
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cudaError_t err = cudaGetLastError();
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if (err != cudaSuccess)
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{
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std::cerr
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<< "Error: "
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<< cudaGetErrorString(err)
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<< std::endl;
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exit(err);
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}
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}
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template <typename T>
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__global__ void copy(const T * a, T * c)
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{
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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c[i] = a[i];
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}
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template <typename T>
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__global__ void mul(T * b, const T * c)
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{
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const T scalar = 3.0;
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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b[i] = scalar * c[i];
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}
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template <typename T>
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__global__ void add(const T * a, const T * b, T * c)
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{
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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c[i] = a[i] + b[i];
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}
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template <typename T>
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__global__ void triad(T * a, const T * b, const T * c)
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{
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const T scalar = 3.0;
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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a[i] = b[i] + scalar * c[i];
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}
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int main(int argc, char *argv[])
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{
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// Print out run information
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std::cout
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<< "GPU-STREAM" << std::endl
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<< "Version: " << VERSION_STRING << std::endl
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<< "Implementation: CUDA" << std::endl;
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parseArguments(argc, argv);
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if (NTIMES < 2)
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throw std::runtime_error("Chosen number of times is invalid, must be >= 2");
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std::cout << "Precision: ";
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if (useFloat) std::cout << "float";
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else std::cout << "double";
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std::cout << std::endl << std::endl;
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std::cout << "Running kernels " << NTIMES << " times" << std::endl;
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if (ARRAY_SIZE % 1024 != 0)
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{
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unsigned int OLD_ARRAY_SIZE = ARRAY_SIZE;
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ARRAY_SIZE -= ARRAY_SIZE % 1024;
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std::cout
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<< "Warning: array size must divide 1024" << std::endl
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<< "Resizing array from " << OLD_ARRAY_SIZE
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<< " to " << ARRAY_SIZE << std::endl;
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if (ARRAY_SIZE == 0)
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throw std::runtime_error("Array size must be >= 1024");
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}
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// Get precision (used to reset later)
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std::streamsize ss = std::cout.precision();
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size_t DATATYPE_SIZE;
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if (useFloat)
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{
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DATATYPE_SIZE = sizeof(float);
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}
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else
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{
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DATATYPE_SIZE = sizeof(double);
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}
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// Display number of bytes in array
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std::cout << std::setprecision(1) << std::fixed
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<< "Array size: " << ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0 << " MB"
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<< " (=" << ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0/1024.0 << " GB)"
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<< std::endl;
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std::cout << "Total size: " << 3.0*ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0 << " MB"
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<< " (=" << 3.0*ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0/1024.0 << " GB)"
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<< std::endl;
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// Reset precision
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std::cout.precision(ss);
|
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// Check device index is in range
|
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int count;
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cudaGetDeviceCount(&count);
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check_cuda_error();
|
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if (deviceIndex >= count)
|
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throw std::runtime_error("Chosen device index is invalid");
|
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cudaSetDevice(deviceIndex);
|
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check_cuda_error();
|
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|
||||
// Print out device name
|
||||
std::cout << "Using CUDA device " << getDeviceName(deviceIndex) << std::endl;
|
||||
|
||||
// Print out device CUDA driver version
|
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std::cout << "Driver: " << getDriver() << std::endl;
|
||||
|
||||
// Check buffers fit on the device
|
||||
cudaDeviceProp props;
|
||||
cudaGetDeviceProperties(&props, deviceIndex);
|
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if (props.totalGlobalMem < 3*DATATYPE_SIZE*ARRAY_SIZE)
|
||||
throw std::runtime_error("Device does not have enough memory for all 3 buffers");
|
||||
|
||||
// Create host vectors
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void * h_a = malloc(ARRAY_SIZE*DATATYPE_SIZE);
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void * h_b = malloc(ARRAY_SIZE*DATATYPE_SIZE);
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void * h_c = malloc(ARRAY_SIZE*DATATYPE_SIZE);
|
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// Initilise arrays
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for (unsigned int i = 0; i < ARRAY_SIZE; i++)
|
||||
{
|
||||
if (useFloat)
|
||||
{
|
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((float*)h_a)[i] = 1.0f;
|
||||
((float*)h_b)[i] = 2.0f;
|
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((float*)h_c)[i] = 0.0f;
|
||||
}
|
||||
else
|
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{
|
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((double*)h_a)[i] = 1.0;
|
||||
((double*)h_b)[i] = 2.0;
|
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((double*)h_c)[i] = 0.0;
|
||||
}
|
||||
}
|
||||
|
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// Create device buffers
|
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void * d_a, * d_b, *d_c;
|
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cudaMalloc(&d_a, ARRAY_SIZE*DATATYPE_SIZE);
|
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check_cuda_error();
|
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cudaMalloc(&d_b, ARRAY_SIZE*DATATYPE_SIZE);
|
||||
check_cuda_error();
|
||||
cudaMalloc(&d_c, ARRAY_SIZE*DATATYPE_SIZE);
|
||||
check_cuda_error();
|
||||
|
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// Copy host memory to device
|
||||
cudaMemcpy(d_a, h_a, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyHostToDevice);
|
||||
check_cuda_error();
|
||||
cudaMemcpy(d_b, h_b, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyHostToDevice);
|
||||
check_cuda_error();
|
||||
cudaMemcpy(d_c, h_c, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyHostToDevice);
|
||||
check_cuda_error();
|
||||
|
||||
// Make sure the copies are finished
|
||||
cudaDeviceSynchronize();
|
||||
check_cuda_error();
|
||||
|
||||
// List of times
|
||||
std::vector< std::vector<double> > timings;
|
||||
|
||||
// Declare timers
|
||||
std::chrono::high_resolution_clock::time_point t1, t2;
|
||||
|
||||
// Main loop
|
||||
for (unsigned int k = 0; k < NTIMES; k++)
|
||||
{
|
||||
std::vector<double> times;
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
if (useFloat)
|
||||
copy<<<ARRAY_SIZE/1024, 1024>>>((float*)d_a, (float*)d_c);
|
||||
else
|
||||
copy<<<ARRAY_SIZE/1024, 1024>>>((double*)d_a, (double*)d_c);
|
||||
check_cuda_error();
|
||||
cudaDeviceSynchronize();
|
||||
check_cuda_error();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
if (useFloat)
|
||||
mul<<<ARRAY_SIZE/1024, 1024>>>((float*)d_b, (float*)d_c);
|
||||
else
|
||||
mul<<<ARRAY_SIZE/1024, 1024>>>((double*)d_b, (double*)d_c);
|
||||
check_cuda_error();
|
||||
cudaDeviceSynchronize();
|
||||
check_cuda_error();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
if (useFloat)
|
||||
add<<<ARRAY_SIZE/1024, 1024>>>((float*)d_a, (float*)d_b, (float*)d_c);
|
||||
else
|
||||
add<<<ARRAY_SIZE/1024, 1024>>>((double*)d_a, (double*)d_b, (double*)d_c);
|
||||
check_cuda_error();
|
||||
cudaDeviceSynchronize();
|
||||
check_cuda_error();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
if (useFloat)
|
||||
triad<<<ARRAY_SIZE/1024, 1024>>>((float*)d_a, (float*)d_b, (float*)d_c);
|
||||
else
|
||||
triad<<<ARRAY_SIZE/1024, 1024>>>((double*)d_a, (double*)d_b, (double*)d_c);
|
||||
check_cuda_error();
|
||||
cudaDeviceSynchronize();
|
||||
check_cuda_error();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
timings.push_back(times);
|
||||
|
||||
}
|
||||
|
||||
// Check solutions
|
||||
cudaMemcpy(h_a, d_a, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyDeviceToHost);
|
||||
check_cuda_error();
|
||||
cudaMemcpy(h_b, d_b, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyDeviceToHost);
|
||||
check_cuda_error();
|
||||
cudaMemcpy(h_c, d_c, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyDeviceToHost);
|
||||
check_cuda_error();
|
||||
|
||||
if (useFloat)
|
||||
{
|
||||
check_solution<float>(h_a, h_b, h_c);
|
||||
}
|
||||
else
|
||||
{
|
||||
check_solution<double>(h_a, h_b, h_c);
|
||||
}
|
||||
|
||||
// Crunch results
|
||||
size_t sizes[4] = {
|
||||
2 * DATATYPE_SIZE * ARRAY_SIZE,
|
||||
2 * DATATYPE_SIZE * ARRAY_SIZE,
|
||||
3 * DATATYPE_SIZE * ARRAY_SIZE,
|
||||
3 * DATATYPE_SIZE * ARRAY_SIZE
|
||||
};
|
||||
double min[4] = {DBL_MAX, DBL_MAX, DBL_MAX, DBL_MAX};
|
||||
double max[4] = {0.0, 0.0, 0.0, 0.0};
|
||||
double avg[4] = {0.0, 0.0, 0.0, 0.0};
|
||||
|
||||
// Ignore first result
|
||||
for (unsigned int i = 1; i < NTIMES; i++)
|
||||
{
|
||||
for (int j = 0; j < 4; j++)
|
||||
{
|
||||
avg[j] += timings[i][j];
|
||||
min[j] = std::min(min[j], timings[i][j]);
|
||||
max[j] = std::max(max[j], timings[i][j]);
|
||||
}
|
||||
}
|
||||
|
||||
for (int j = 0; j < 4; j++)
|
||||
avg[j] /= (double)(NTIMES-1);
|
||||
|
||||
// Display results
|
||||
std::string labels[] = {"Copy", "Mul", "Add", "Triad"};
|
||||
std::cout
|
||||
<< std::left << std::setw(12) << "Function"
|
||||
<< std::left << std::setw(12) << "MBytes/sec"
|
||||
<< std::left << std::setw(12) << "Min (sec)"
|
||||
<< std::left << std::setw(12) << "Max"
|
||||
<< std::left << std::setw(12) << "Average"
|
||||
<< std::endl;
|
||||
|
||||
for (int j = 0; j < 4; j++)
|
||||
{
|
||||
std::cout
|
||||
<< std::left << std::setw(12) << labels[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(3) << 1.0E-06 * sizes[j]/min[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(5) << min[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(5) << max[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(5) << avg[j]
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
// Free host vectors
|
||||
free(h_a);
|
||||
free(h_b);
|
||||
free(h_c);
|
||||
|
||||
// Free cuda buffers
|
||||
cudaFree(d_a);
|
||||
check_cuda_error();
|
||||
cudaFree(d_b);
|
||||
check_cuda_error();
|
||||
cudaFree(d_c);
|
||||
check_cuda_error();
|
||||
|
||||
}
|
||||
|
||||
std::string getDeviceName(int device)
|
||||
{
|
||||
struct cudaDeviceProp prop;
|
||||
cudaGetDeviceProperties(&prop, device);
|
||||
check_cuda_error();
|
||||
return std::string(prop.name);
|
||||
}
|
||||
|
||||
int getDriver(void)
|
||||
{
|
||||
int driver;
|
||||
cudaDriverGetVersion(&driver);
|
||||
check_cuda_error();
|
||||
return driver;
|
||||
}
|
||||
|
||||
void listDevices(void)
|
||||
{
|
||||
// Get number of devices
|
||||
int count;
|
||||
cudaGetDeviceCount(&count);
|
||||
check_cuda_error();
|
||||
|
||||
// Print device names
|
||||
if (count == 0)
|
||||
{
|
||||
std::cout << "No devices found." << std::endl;
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << std::endl;
|
||||
std::cout << "Devices:" << std::endl;
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
std::cout << i << ": " << getDeviceName(i) << std::endl;
|
||||
check_cuda_error();
|
||||
}
|
||||
std::cout << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,70 +0,0 @@
|
||||
/*=============================================================================
|
||||
*------------------------------------------------------------------------------
|
||||
* Copyright 2015: Tom Deakin, Simon McIntosh-Smith, University of Bristol HPC
|
||||
* Based on John D. McCalpin’s original STREAM benchmark for CPUs
|
||||
*------------------------------------------------------------------------------
|
||||
* License:
|
||||
* 1. You are free to use this program and/or to redistribute
|
||||
* this program.
|
||||
* 2. You are free to modify this program for your own use,
|
||||
* including commercial use, subject to the publication
|
||||
* restrictions in item 3.
|
||||
* 3. You are free to publish results obtained from running this
|
||||
* program, or from works that you derive from this program,
|
||||
* with the following limitations:
|
||||
* 3a. In order to be referred to as "GPU-STREAM benchmark results",
|
||||
* published results must be in conformance to the GPU-STREAM
|
||||
* Run Rules published at
|
||||
* http://github.com/UoB-HPC/GPU-STREAM/wiki/Run-Rules
|
||||
* and incorporated herein by reference.
|
||||
* The copyright holders retain the
|
||||
* right to determine conformity with the Run Rules.
|
||||
* 3b. Results based on modified source code or on runs not in
|
||||
* accordance with the GPU-STREAM Run Rules must be clearly
|
||||
* labelled whenever they are published. Examples of
|
||||
* proper labelling include:
|
||||
* "tuned GPU-STREAM benchmark results"
|
||||
* "based on a variant of the GPU-STREAM benchmark code"
|
||||
* Other comparable, clear and reasonable labelling is
|
||||
* acceptable.
|
||||
* 3c. Submission of results to the GPU-STREAM benchmark web site
|
||||
* is encouraged, but not required.
|
||||
* 4. Use of this program or creation of derived works based on this
|
||||
* program constitutes acceptance of these licensing restrictions.
|
||||
* 5. Absolutely no warranty is expressed or implied.
|
||||
*———————————————————————————————————-----------------------------------------*/
|
||||
|
||||
|
||||
#ifdef FLOAT
|
||||
#define DATATYPE float
|
||||
constant DATATYPE scalar = 3.0f;
|
||||
#else
|
||||
#pragma OPENCL EXTENSION cl_khr_fp64 : enable
|
||||
#define DATATYPE double
|
||||
constant DATATYPE scalar = 3.0;
|
||||
#endif
|
||||
|
||||
|
||||
kernel void copy(global const DATATYPE * restrict a, global DATATYPE * restrict c)
|
||||
{
|
||||
const size_t i = get_global_id(0);
|
||||
c[i] = a[i];
|
||||
}
|
||||
|
||||
kernel void mul(global DATATYPE * restrict b, global const DATATYPE * restrict c)
|
||||
{
|
||||
const size_t i = get_global_id(0);
|
||||
b[i] = scalar * c[i];
|
||||
}
|
||||
|
||||
kernel void add(global const DATATYPE * restrict a, global const DATATYPE * restrict b, global DATATYPE * restrict c)
|
||||
{
|
||||
const size_t i = get_global_id(0);
|
||||
c[i] = a[i] + b[i];
|
||||
}
|
||||
|
||||
kernel void triad(global DATATYPE * restrict a, global const DATATYPE * restrict b, global const DATATYPE * restrict c)
|
||||
{
|
||||
const size_t i = get_global_id(0);
|
||||
a[i] = b[i] + scalar * c[i];
|
||||
}
|
||||
488
ocl-stream.cpp
488
ocl-stream.cpp
@ -1,488 +0,0 @@
|
||||
/*=============================================================================
|
||||
*------------------------------------------------------------------------------
|
||||
* Copyright 2015: Tom Deakin, Simon McIntosh-Smith, University of Bristol HPC
|
||||
* Based on John D. McCalpin’s original STREAM benchmark for CPUs
|
||||
*------------------------------------------------------------------------------
|
||||
* License:
|
||||
* 1. You are free to use this program and/or to redistribute
|
||||
* this program.
|
||||
* 2. You are free to modify this program for your own use,
|
||||
* including commercial use, subject to the publication
|
||||
* restrictions in item 3.
|
||||
* 3. You are free to publish results obtained from running this
|
||||
* program, or from works that you derive from this program,
|
||||
* with the following limitations:
|
||||
* 3a. In order to be referred to as "GPU-STREAM benchmark results",
|
||||
* published results must be in conformance to the GPU-STREAM
|
||||
* Run Rules published at
|
||||
* http://github.com/UoB-HPC/GPU-STREAM/wiki/Run-Rules
|
||||
* and incorporated herein by reference.
|
||||
* The copyright holders retain the
|
||||
* right to determine conformity with the Run Rules.
|
||||
* 3b. Results based on modified source code or on runs not in
|
||||
* accordance with the GPU-STREAM Run Rules must be clearly
|
||||
* labelled whenever they are published. Examples of
|
||||
* proper labelling include:
|
||||
* "tuned GPU-STREAM benchmark results"
|
||||
* "based on a variant of the GPU-STREAM benchmark code"
|
||||
* Other comparable, clear and reasonable labelling is
|
||||
* acceptable.
|
||||
* 3c. Submission of results to the GPU-STREAM benchmark web site
|
||||
* is encouraged, but not required.
|
||||
* 4. Use of this program or creation of derived works based on this
|
||||
* program constitutes acceptance of these licensing restrictions.
|
||||
* 5. Absolutely no warranty is expressed or implied.
|
||||
*———————————————————————————————————-----------------------------------------*/
|
||||
|
||||
|
||||
#include <iostream>
|
||||
#include <fstream>
|
||||
#include <vector>
|
||||
#include <chrono>
|
||||
#include <cfloat>
|
||||
#include <cmath>
|
||||
|
||||
#define CL_HPP_ENABLE_EXCEPTIONS
|
||||
#define CL_HPP_MINIMUM_OPENCL_VERSION 110
|
||||
#define CL_HPP_TARGET_OPENCL_VERSION 110
|
||||
#include "CL/cl2.hpp"
|
||||
#include "common.h"
|
||||
|
||||
std::string getDeviceName(const cl::Device& device);
|
||||
std::string getDeviceDriver(const cl::Device& device);
|
||||
unsigned getDeviceList(std::vector<cl::Device>& devices);
|
||||
|
||||
|
||||
// Print error and exit
|
||||
void die(std::string msg, cl::Error& e)
|
||||
{
|
||||
std::cerr
|
||||
<< "Error: "
|
||||
<< msg
|
||||
<< ": " << e.what()
|
||||
<< "(" << e.err() << ")"
|
||||
<< std::endl;
|
||||
exit(e.err());
|
||||
}
|
||||
|
||||
|
||||
int main(int argc, char *argv[])
|
||||
{
|
||||
|
||||
// Print out run information
|
||||
std::cout
|
||||
<< "GPU-STREAM" << std::endl
|
||||
<< "Version: " << VERSION_STRING << std::endl
|
||||
<< "Implementation: OpenCL" << std::endl;
|
||||
|
||||
std::string status;
|
||||
|
||||
try
|
||||
{
|
||||
parseArguments(argc, argv);
|
||||
if (NTIMES < 2)
|
||||
throw std::runtime_error("Chosen number of times is invalid, must be >= 2");
|
||||
|
||||
|
||||
std::cout << "Precision: ";
|
||||
if (useFloat) std::cout << "float";
|
||||
else std::cout << "double";
|
||||
std::cout << std::endl << std::endl;
|
||||
|
||||
std::cout << "Running kernels " << NTIMES << " times" << std::endl;
|
||||
|
||||
if (ARRAY_SIZE % 1024 != 0)
|
||||
{
|
||||
unsigned int OLD_ARRAY_SIZE = ARRAY_SIZE;
|
||||
ARRAY_SIZE -= ARRAY_SIZE % 1024;
|
||||
std::cout
|
||||
<< "Warning: array size must divide 1024" << std::endl
|
||||
<< "Resizing array from " << OLD_ARRAY_SIZE
|
||||
<< " to " << ARRAY_SIZE << std::endl;
|
||||
if (ARRAY_SIZE == 0)
|
||||
throw std::runtime_error("Array size must be >= 1024");
|
||||
}
|
||||
|
||||
// Get precision (used to reset later)
|
||||
std::streamsize ss = std::cout.precision();
|
||||
|
||||
size_t DATATYPE_SIZE;
|
||||
|
||||
if (useFloat)
|
||||
{
|
||||
DATATYPE_SIZE = sizeof(float);
|
||||
}
|
||||
else
|
||||
{
|
||||
DATATYPE_SIZE = sizeof(double);
|
||||
}
|
||||
|
||||
// Display number of bytes in array
|
||||
std::cout << std::setprecision(1) << std::fixed
|
||||
<< "Array size: " << ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0 << " MB"
|
||||
<< " (=" << ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0/1024.0 << " GB)"
|
||||
<< std::endl;
|
||||
std::cout << "Total size: " << 3.0*ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0 << " MB"
|
||||
<< " (=" << 3.0*ARRAY_SIZE*DATATYPE_SIZE/1024.0/1024.0/1024.0 << " GB)"
|
||||
<< std::endl;
|
||||
|
||||
// Reset precision
|
||||
std::cout.precision(ss);
|
||||
|
||||
// Open the Kernel source
|
||||
std::string kernels;
|
||||
{
|
||||
std::ifstream in("ocl-stream-kernels.cl");
|
||||
if (!in.is_open())
|
||||
throw std::runtime_error("Cannot open kernel file");
|
||||
kernels = std::string (std::istreambuf_iterator<char>(in), (std::istreambuf_iterator<char>()));
|
||||
}
|
||||
|
||||
|
||||
// Setup OpenCL
|
||||
|
||||
// Get list of devices
|
||||
std::vector<cl::Device> devices;
|
||||
getDeviceList(devices);
|
||||
|
||||
// Check device index is in range
|
||||
if (deviceIndex >= devices.size())
|
||||
throw std::runtime_error("Chosen device index is invalid");
|
||||
|
||||
cl::Device device = devices[deviceIndex];
|
||||
|
||||
status = "Creating context";
|
||||
cl::Context context(device);
|
||||
|
||||
status = "Creating queue";
|
||||
cl::CommandQueue queue(context);
|
||||
|
||||
status = "Creating program";
|
||||
cl::Program program(context, kernels);
|
||||
|
||||
// Print out device name
|
||||
std::string name = getDeviceName(device);
|
||||
std::cout << "Using OpenCL device " << name << std::endl;
|
||||
|
||||
// Print out OpenCL driver version for this device
|
||||
std::string driver = getDeviceDriver(device);
|
||||
std::cout << "Driver: " << driver << std::endl;
|
||||
|
||||
// Check device can do double precision if requested
|
||||
if (!useFloat && !device.getInfo<CL_DEVICE_DOUBLE_FP_CONFIG>())
|
||||
throw std::runtime_error("Device does not support double precision, please use --float");
|
||||
|
||||
// Check buffers fit on the device
|
||||
status = "Getting device memory sizes";
|
||||
cl_ulong totalmem = device.getInfo<CL_DEVICE_GLOBAL_MEM_SIZE>();
|
||||
cl_ulong maxbuffer = device.getInfo<CL_DEVICE_MAX_MEM_ALLOC_SIZE>();
|
||||
if (maxbuffer < DATATYPE_SIZE*ARRAY_SIZE)
|
||||
throw std::runtime_error("Device cannot allocate a buffer big enough");
|
||||
if (totalmem < 3*DATATYPE_SIZE*ARRAY_SIZE)
|
||||
throw std::runtime_error("Device does not have enough memory for all 3 buffers");
|
||||
|
||||
try
|
||||
{
|
||||
std::string options = "";
|
||||
if (useFloat)
|
||||
options = "-DFLOAT";
|
||||
program.build(options.c_str());
|
||||
}
|
||||
catch (cl::Error& e)
|
||||
{
|
||||
std::vector<cl::Device> devices = context.getInfo<CL_CONTEXT_DEVICES>();
|
||||
std::string buildlog = program.getBuildInfo<CL_PROGRAM_BUILD_LOG>(devices[0]);
|
||||
std::cerr
|
||||
<< "Build error:"
|
||||
<< buildlog
|
||||
<< std::endl;
|
||||
throw e;
|
||||
}
|
||||
|
||||
status = "Making kernel copy";
|
||||
auto copy = cl::KernelFunctor<cl::Buffer&, cl::Buffer&>(program, "copy");
|
||||
status = "Making kernel mul";
|
||||
auto mul = cl::KernelFunctor<cl::Buffer&, cl::Buffer&>(program, "mul");
|
||||
status = "Making kernel add";
|
||||
auto add = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&>(program, "add");
|
||||
status = "Making kernel triad";
|
||||
auto triad = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&>(program, "triad");
|
||||
|
||||
// Create host vectors
|
||||
void *h_a = malloc(ARRAY_SIZE * DATATYPE_SIZE);
|
||||
void *h_b = malloc(ARRAY_SIZE * DATATYPE_SIZE);
|
||||
void *h_c = malloc(ARRAY_SIZE * DATATYPE_SIZE);
|
||||
|
||||
// Initilise arrays
|
||||
for (unsigned int i = 0; i < ARRAY_SIZE; i++)
|
||||
{
|
||||
if (useFloat)
|
||||
{
|
||||
((float*)h_a)[i] = 1.0f;
|
||||
((float*)h_b)[i] = 2.0f;
|
||||
((float*)h_c)[i] = 0.0f;
|
||||
}
|
||||
else
|
||||
{
|
||||
((double*)h_a)[i] = 1.0;
|
||||
((double*)h_b)[i] = 2.0;
|
||||
((double*)h_c)[i] = 0.0;
|
||||
}
|
||||
}
|
||||
|
||||
// Create device buffers
|
||||
status = "Creating buffers";
|
||||
cl::Buffer d_a(context, CL_MEM_READ_WRITE, DATATYPE_SIZE * ARRAY_SIZE);
|
||||
cl::Buffer d_b(context, CL_MEM_READ_WRITE, DATATYPE_SIZE * ARRAY_SIZE);
|
||||
cl::Buffer d_c(context, CL_MEM_READ_WRITE, DATATYPE_SIZE * ARRAY_SIZE);
|
||||
|
||||
|
||||
// Copy host memory to device
|
||||
status = "Copying buffers";
|
||||
queue.enqueueWriteBuffer(d_a, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_a);
|
||||
queue.enqueueWriteBuffer(d_b, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_b);
|
||||
queue.enqueueWriteBuffer(d_c, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_c);
|
||||
|
||||
// Make sure the copies are finished
|
||||
queue.finish();
|
||||
|
||||
|
||||
// List of times
|
||||
std::vector< std::vector<double> > timings;
|
||||
|
||||
// Declare timers
|
||||
std::chrono::high_resolution_clock::time_point t1, t2;
|
||||
|
||||
// Main loop
|
||||
for (unsigned int k = 0; k < NTIMES; k++)
|
||||
{
|
||||
status = "Executing copy";
|
||||
std::vector<double> times;
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
copy(
|
||||
cl::EnqueueArgs(
|
||||
queue,
|
||||
cl::NDRange(ARRAY_SIZE)),
|
||||
d_a, d_c);
|
||||
queue.finish();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
|
||||
status = "Executing mul";
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
mul(
|
||||
cl::EnqueueArgs(
|
||||
queue,
|
||||
cl::NDRange(ARRAY_SIZE)),
|
||||
d_b, d_c);
|
||||
queue.finish();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
|
||||
status = "Executing add";
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
add(
|
||||
cl::EnqueueArgs(
|
||||
queue,
|
||||
cl::NDRange(ARRAY_SIZE)),
|
||||
d_a, d_b, d_c);
|
||||
queue.finish();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
|
||||
status = "Executing triad";
|
||||
t1 = std::chrono::high_resolution_clock::now();
|
||||
triad(
|
||||
cl::EnqueueArgs(
|
||||
queue,
|
||||
cl::NDRange(ARRAY_SIZE)),
|
||||
d_a, d_b, d_c);
|
||||
queue.finish();
|
||||
t2 = std::chrono::high_resolution_clock::now();
|
||||
times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
|
||||
|
||||
timings.push_back(times);
|
||||
|
||||
}
|
||||
|
||||
// Check solutions
|
||||
status = "Copying back buffers";
|
||||
queue.enqueueReadBuffer(d_a, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_a);
|
||||
queue.enqueueReadBuffer(d_b, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_b);
|
||||
queue.enqueueReadBuffer(d_c, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_c);
|
||||
queue.finish();
|
||||
|
||||
|
||||
if (useFloat)
|
||||
{
|
||||
check_solution<float>(h_a, h_b, h_c);
|
||||
}
|
||||
else
|
||||
{
|
||||
check_solution<double>(h_a, h_b, h_c);
|
||||
}
|
||||
|
||||
// Crunch results
|
||||
size_t sizes[4] = {
|
||||
2 * DATATYPE_SIZE * ARRAY_SIZE,
|
||||
2 * DATATYPE_SIZE * ARRAY_SIZE,
|
||||
3 * DATATYPE_SIZE * ARRAY_SIZE,
|
||||
3 * DATATYPE_SIZE * ARRAY_SIZE
|
||||
};
|
||||
double min[4] = {DBL_MAX, DBL_MAX, DBL_MAX, DBL_MAX};
|
||||
double max[4] = {0.0, 0.0, 0.0, 0.0};
|
||||
double avg[4] = {0.0, 0.0, 0.0, 0.0};
|
||||
// Ignore first result
|
||||
for (unsigned int i = 1; i < NTIMES; i++)
|
||||
{
|
||||
for (int j = 0; j < 4; j++)
|
||||
{
|
||||
avg[j] += timings[i][j];
|
||||
min[j] = std::min(min[j], timings[i][j]);
|
||||
max[j] = std::max(max[j], timings[i][j]);
|
||||
}
|
||||
}
|
||||
for (int j = 0; j < 4; j++)
|
||||
avg[j] /= (double)(NTIMES-1);
|
||||
|
||||
// Display results
|
||||
std::string labels[] = {"Copy", "Mul", "Add", "Triad"};
|
||||
std::cout
|
||||
<< std::left << std::setw(12) << "Function"
|
||||
<< std::left << std::setw(12) << "MBytes/sec"
|
||||
<< std::left << std::setw(12) << "Min (sec)"
|
||||
<< std::left << std::setw(12) << "Max"
|
||||
<< std::left << std::setw(12) << "Average"
|
||||
<< std::endl;
|
||||
for (int j = 0; j < 4; j++)
|
||||
{
|
||||
std::cout
|
||||
<< std::left << std::setw(12) << labels[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(3) << 1.0E-06 * sizes[j]/min[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(5) << min[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(5) << max[j]
|
||||
<< std::left << std::setw(12) << std::setprecision(5) << avg[j]
|
||||
<< std::endl;
|
||||
}
|
||||
|
||||
// Free host vectors
|
||||
free(h_a);
|
||||
free(h_b);
|
||||
free(h_c);
|
||||
|
||||
}
|
||||
catch (cl::Error &e)
|
||||
{
|
||||
die(status, e);
|
||||
}
|
||||
catch (std::exception& e)
|
||||
{
|
||||
std::cerr
|
||||
<< "Error: "
|
||||
<< e.what()
|
||||
<< std::endl;
|
||||
exit(EXIT_FAILURE);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
unsigned getDeviceList(std::vector<cl::Device>& devices)
|
||||
{
|
||||
// Get list of platforms
|
||||
std::vector<cl::Platform> platforms;
|
||||
try
|
||||
{
|
||||
cl::Platform::get(&platforms);
|
||||
}
|
||||
catch (cl::Error &e)
|
||||
{
|
||||
die("Getting platforms", e);
|
||||
}
|
||||
|
||||
// Enumerate devices
|
||||
for (unsigned int i = 0; i < platforms.size(); i++)
|
||||
{
|
||||
std::vector<cl::Device> plat_devices;
|
||||
try
|
||||
{
|
||||
platforms[i].getDevices(CL_DEVICE_TYPE_ALL, &plat_devices);
|
||||
}
|
||||
catch (cl::Error &e)
|
||||
{
|
||||
die("Getting devices", e);
|
||||
}
|
||||
devices.insert(devices.end(), plat_devices.begin(), plat_devices.end());
|
||||
}
|
||||
|
||||
return devices.size();
|
||||
}
|
||||
|
||||
|
||||
std::string getDeviceName(const cl::Device& device)
|
||||
{
|
||||
std::string name;
|
||||
cl_device_info info = CL_DEVICE_NAME;
|
||||
|
||||
try
|
||||
{
|
||||
|
||||
// Special case for AMD
|
||||
#ifdef CL_DEVICE_BOARD_NAME_AMD
|
||||
device.getInfo(CL_DEVICE_VENDOR, &name);
|
||||
if (strstr(name.c_str(), "Advanced Micro Devices"))
|
||||
info = CL_DEVICE_BOARD_NAME_AMD;
|
||||
#endif
|
||||
|
||||
device.getInfo(info, &name);
|
||||
}
|
||||
catch (cl::Error &e)
|
||||
{
|
||||
die("Getting device name", e);
|
||||
}
|
||||
|
||||
return name;
|
||||
}
|
||||
|
||||
std::string getDeviceDriver(const cl::Device& device)
|
||||
{
|
||||
std::string driver;
|
||||
try
|
||||
{
|
||||
device.getInfo(CL_DRIVER_VERSION, &driver);
|
||||
}
|
||||
catch (cl::Error &e)
|
||||
{
|
||||
die("Getting device driver", e);
|
||||
}
|
||||
|
||||
return driver;
|
||||
}
|
||||
|
||||
|
||||
void listDevices(void)
|
||||
{
|
||||
// Get list of devices
|
||||
std::vector<cl::Device> devices;
|
||||
getDeviceList(devices);
|
||||
|
||||
// Print device names
|
||||
if (devices.size() == 0)
|
||||
{
|
||||
std::cout << "No devices found." << std::endl;
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << std::endl;
|
||||
std::cout << "Devices:" << std::endl;
|
||||
for (unsigned i = 0; i < devices.size(); i++)
|
||||
{
|
||||
std::cout << i << ": " << getDeviceName(devices[i]) << std::endl;
|
||||
}
|
||||
std::cout << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user