e804f44497
Specifically: * make_kernel has been replaced by KernelFunctor. * Different define statements before including the header.
468 lines
15 KiB
C++
468 lines
15 KiB
C++
/*=============================================================================
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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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#define CL_HPP_ENABLE_EXCEPTIONS
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#define CL_HPP_MINIMUM_OPENCL_VERSION 110
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#define CL_HPP_TARGET_OPENCL_VERSION 110
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#include "CL/cl2.hpp"
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#include "common.h"
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std::string getDeviceName(const cl::Device& device);
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unsigned getDeviceList(std::vector<cl::Device>& devices);
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// Print error and exit
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void die(std::string msg, cl::Error& e)
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{
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std::cerr
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<< "Error: "
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<< msg
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<< ": " << e.what()
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<< "(" << e.err() << ")"
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<< std::endl;
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exit(e.err());
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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: OpenCL" << std::endl;
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std::string status;
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try
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{
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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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// Open the Kernel source
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std::string kernels;
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{
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std::ifstream in("ocl-stream-kernels.cl");
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if (!in.is_open())
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throw std::runtime_error("Cannot open kernel file");
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kernels = std::string (std::istreambuf_iterator<char>(in), (std::istreambuf_iterator<char>()));
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}
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// Setup OpenCL
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// Get list of devices
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std::vector<cl::Device> devices;
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getDeviceList(devices);
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// Check device index is in range
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if (deviceIndex >= devices.size())
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throw std::runtime_error("Chosen device index is invalid");
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cl::Device device = devices[deviceIndex];
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status = "Creating context";
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cl::Context context(device);
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status = "Creating queue";
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cl::CommandQueue queue(context);
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status = "Creating program";
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cl::Program program(context, kernels);
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// Print out device name
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std::string name = getDeviceName(device);
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std::cout << "Using OpenCL device " << name << std::endl;
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// Check device can do double precision if requested
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if (!useFloat && !device.getInfo<CL_DEVICE_DOUBLE_FP_CONFIG>())
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throw std::runtime_error("Device does not support double precision, please use --float");
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// Check buffers fit on the device
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status = "Getting device memory sizes";
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cl_ulong totalmem = device.getInfo<CL_DEVICE_GLOBAL_MEM_SIZE>();
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cl_ulong maxbuffer = device.getInfo<CL_DEVICE_MAX_MEM_ALLOC_SIZE>();
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if (maxbuffer < DATATYPE_SIZE*ARRAY_SIZE)
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throw std::runtime_error("Device cannot allocate a buffer big enough");
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if (totalmem < 3*DATATYPE_SIZE*ARRAY_SIZE)
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throw std::runtime_error("Device does not have enough memory for all 3 buffers");
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try
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{
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std::string options = "";
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if (useFloat)
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options = "-DFLOAT";
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program.build(options.c_str());
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}
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catch (cl::Error& e)
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{
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std::vector<cl::Device> devices = context.getInfo<CL_CONTEXT_DEVICES>();
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std::string buildlog = program.getBuildInfo<CL_PROGRAM_BUILD_LOG>(devices[0]);
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std::cerr
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<< "Build error:"
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<< buildlog
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<< std::endl;
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throw e;
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}
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status = "Making kernel copy";
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auto copy = cl::KernelFunctor<cl::Buffer&, cl::Buffer&>(program, "copy");
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status = "Making kernel mul";
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auto mul = cl::KernelFunctor<cl::Buffer&, cl::Buffer&>(program, "mul");
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status = "Making kernel add";
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auto add = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&>(program, "add");
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status = "Making kernel triad";
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auto triad = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&>(program, "triad");
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// 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++)
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{
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if (useFloat)
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{
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((float*)h_a)[i] = 1.0f;
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((float*)h_b)[i] = 2.0f;
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((float*)h_c)[i] = 0.0f;
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}
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else
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{
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((double*)h_a)[i] = 1.0;
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((double*)h_b)[i] = 2.0;
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((double*)h_c)[i] = 0.0;
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}
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}
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// Create device buffers
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status = "Creating buffers";
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cl::Buffer d_a(context, CL_MEM_READ_WRITE, DATATYPE_SIZE * ARRAY_SIZE);
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cl::Buffer d_b(context, CL_MEM_READ_WRITE, DATATYPE_SIZE * ARRAY_SIZE);
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cl::Buffer d_c(context, CL_MEM_READ_WRITE, DATATYPE_SIZE * ARRAY_SIZE);
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// Copy host memory to device
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status = "Copying buffers";
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queue.enqueueWriteBuffer(d_a, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_a);
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queue.enqueueWriteBuffer(d_b, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_b);
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queue.enqueueWriteBuffer(d_c, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_c);
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// Make sure the copies are finished
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queue.finish();
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// List of times
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std::vector< std::vector<double> > timings;
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// Declare timers
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std::chrono::high_resolution_clock::time_point t1, t2;
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// Main loop
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for (unsigned int k = 0; k < NTIMES; k++)
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{
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status = "Executing copy";
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std::vector<double> times;
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t1 = std::chrono::high_resolution_clock::now();
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copy(
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cl::EnqueueArgs(
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queue,
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cl::NDRange(ARRAY_SIZE)),
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d_a, d_c);
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queue.finish();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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status = "Executing mul";
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t1 = std::chrono::high_resolution_clock::now();
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mul(
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cl::EnqueueArgs(
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queue,
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cl::NDRange(ARRAY_SIZE)),
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d_b, d_c);
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queue.finish();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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status = "Executing add";
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t1 = std::chrono::high_resolution_clock::now();
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add(
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cl::EnqueueArgs(
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queue,
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cl::NDRange(ARRAY_SIZE)),
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d_a, d_b, d_c);
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queue.finish();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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status = "Executing triad";
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t1 = std::chrono::high_resolution_clock::now();
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triad(
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cl::EnqueueArgs(
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queue,
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cl::NDRange(ARRAY_SIZE)),
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d_a, d_b, d_c);
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queue.finish();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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timings.push_back(times);
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}
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// Check solutions
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status = "Copying back buffers";
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queue.enqueueReadBuffer(d_a, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_a);
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queue.enqueueReadBuffer(d_b, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_b);
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queue.enqueueReadBuffer(d_c, CL_FALSE, 0, ARRAY_SIZE*DATATYPE_SIZE, h_c);
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queue.finish();
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if (useFloat)
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{
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check_solution<float>(h_a, h_b, h_c);
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}
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else
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{
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check_solution<double>(h_a, h_b, h_c);
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}
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// Crunch results
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size_t sizes[4] = {
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2 * DATATYPE_SIZE * ARRAY_SIZE,
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2 * DATATYPE_SIZE * ARRAY_SIZE,
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3 * DATATYPE_SIZE * ARRAY_SIZE,
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3 * DATATYPE_SIZE * ARRAY_SIZE
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};
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double min[4] = {DBL_MAX, DBL_MAX, DBL_MAX, DBL_MAX};
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double max[4] = {0.0, 0.0, 0.0, 0.0};
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double avg[4] = {0.0, 0.0, 0.0, 0.0};
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// Ignore first result
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for (unsigned int i = 1; i < NTIMES; i++)
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{
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for (int j = 0; j < 4; j++)
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{
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avg[j] += timings[i][j];
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min[j] = std::min(min[j], timings[i][j]);
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max[j] = std::max(max[j], timings[i][j]);
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}
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}
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for (int j = 0; j < 4; j++)
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avg[j] /= (double)(NTIMES-1);
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// Display results
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std::string labels[] = {"Copy", "Mul", "Add", "Triad"};
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std::cout
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<< std::left << std::setw(12) << "Function"
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<< std::left << std::setw(12) << "MBytes/sec"
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<< std::left << std::setw(12) << "Min (sec)"
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<< std::left << std::setw(12) << "Max"
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<< std::left << std::setw(12) << "Average"
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<< std::endl;
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for (int j = 0; j < 4; j++)
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{
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std::cout
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<< std::left << std::setw(12) << labels[j]
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<< std::left << std::setw(12) << std::setprecision(3) << 1.0E-06 * sizes[j]/min[j]
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<< std::left << std::setw(12) << std::setprecision(5) << min[j]
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<< std::left << std::setw(12) << std::setprecision(5) << max[j]
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<< std::left << std::setw(12) << std::setprecision(5) << avg[j]
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<< std::endl;
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}
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// Free host vectors
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free(h_a);
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free(h_b);
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free(h_c);
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}
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catch (cl::Error &e)
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{
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die(status, e);
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}
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catch (std::exception& e)
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{
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std::cerr
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<< "Error: "
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<< e.what()
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<< std::endl;
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exit(EXIT_FAILURE);
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}
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}
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unsigned getDeviceList(std::vector<cl::Device>& devices)
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{
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// Get list of platforms
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std::vector<cl::Platform> platforms;
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try
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{
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cl::Platform::get(&platforms);
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}
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catch (cl::Error &e)
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{
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die("Getting platforms", e);
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}
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// Enumerate devices
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for (unsigned int i = 0; i < platforms.size(); i++)
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{
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std::vector<cl::Device> plat_devices;
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try
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{
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platforms[i].getDevices(CL_DEVICE_TYPE_ALL, &plat_devices);
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}
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catch (cl::Error &e)
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{
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die("Getting devices", e);
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}
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devices.insert(devices.end(), plat_devices.begin(), plat_devices.end());
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}
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return devices.size();
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}
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std::string getDeviceName(const cl::Device& device)
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{
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std::string name;
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cl_device_info info = CL_DEVICE_NAME;
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try
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{
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// Special case for AMD
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#ifdef CL_DEVICE_BOARD_NAME_AMD
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device.getInfo(CL_DEVICE_VENDOR, &name);
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if (strstr(name.c_str(), "Advanced Micro Devices"))
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info = CL_DEVICE_BOARD_NAME_AMD;
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#endif
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device.getInfo(info, &name);
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}
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catch (cl::Error &e)
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{
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die("Getting device name", e);
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}
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return name;
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}
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void listDevices(void)
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{
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// Get list of devices
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std::vector<cl::Device> devices;
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getDeviceList(devices);
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// Print device names
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if (devices.size() == 0)
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{
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std::cout << "No devices found." << std::endl;
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}
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else
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{
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std::cout << std::endl;
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std::cout << "Devices:" << std::endl;
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for (unsigned i = 0; i < devices.size(); i++)
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{
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std::cout << i << ": " << getDeviceName(devices[i]) << std::endl;
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}
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std::cout << std::endl;
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}
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}
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