370 lines
8.8 KiB
C++
370 lines
8.8 KiB
C++
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// Copyright (c) 2015-16 Tom Deakin, Simon McIntosh-Smith,
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// University of Bristol HPC
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//
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// For full license terms please see the LICENSE file distributed with this
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// source code
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#include "OCLStream.h"
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// Cache list of devices
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bool cached = false;
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std::vector<cl::Device> devices;
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void getDeviceList(void);
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std::string kernels{R"CLC(
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constant TYPE scalar = startScalar;
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kernel void init(
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global TYPE * restrict a,
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global TYPE * restrict b,
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global TYPE * restrict c,
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TYPE initA, TYPE initB, TYPE initC)
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{
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const size_t i = get_global_id(0);
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a[i] = initA;
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b[i] = initB;
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c[i] = initC;
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}
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kernel void copy(
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global const TYPE * restrict a,
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global TYPE * restrict c)
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{
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const size_t i = get_global_id(0);
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c[i] = a[i];
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}
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kernel void mul(
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global TYPE * restrict b,
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global const TYPE * restrict c)
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{
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const size_t i = get_global_id(0);
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b[i] = scalar * c[i];
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}
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kernel void add(
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global const TYPE * restrict a,
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global const TYPE * restrict b,
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global TYPE * restrict c)
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{
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const size_t i = get_global_id(0);
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c[i] = a[i] + b[i];
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}
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kernel void triad(
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global TYPE * restrict a,
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global const TYPE * restrict b,
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global const TYPE * restrict c)
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{
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const size_t i = get_global_id(0);
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a[i] = b[i] + scalar * c[i];
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}
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kernel void nstream(
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global TYPE * restrict a,
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global const TYPE * restrict b,
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global const TYPE * restrict c)
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{
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const size_t i = get_global_id(0);
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a[i] += b[i] + scalar * c[i];
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}
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kernel void stream_dot(
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global const TYPE * restrict a,
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global const TYPE * restrict b,
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global TYPE * restrict sum,
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local TYPE * restrict wg_sum,
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int array_size)
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{
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size_t i = get_global_id(0);
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const size_t local_i = get_local_id(0);
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wg_sum[local_i] = 0.0;
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for (; i < array_size; i += get_global_size(0))
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wg_sum[local_i] += a[i] * b[i];
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for (int offset = get_local_size(0) / 2; offset > 0; offset /= 2)
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{
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barrier(CLK_LOCAL_MEM_FENCE);
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if (local_i < offset)
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{
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wg_sum[local_i] += wg_sum[local_i+offset];
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}
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}
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if (local_i == 0)
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sum[get_group_id(0)] = wg_sum[local_i];
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}
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)CLC"};
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template <class T>
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OCLStream<T>::OCLStream(const int ARRAY_SIZE, const int device_index)
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{
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if (!cached)
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getDeviceList();
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// Setup default OpenCL GPU
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if (device_index >= devices.size())
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throw std::runtime_error("Invalid device index");
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device = devices[device_index];
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// Determine sensible dot kernel NDRange configuration
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if (device.getInfo<CL_DEVICE_TYPE>() & CL_DEVICE_TYPE_CPU)
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{
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dot_num_groups = device.getInfo<CL_DEVICE_MAX_COMPUTE_UNITS>();
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dot_wgsize = device.getInfo<CL_DEVICE_NATIVE_VECTOR_WIDTH_DOUBLE>() * 2;
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}
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else
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{
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dot_num_groups = device.getInfo<CL_DEVICE_MAX_COMPUTE_UNITS>() * 4;
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dot_wgsize = device.getInfo<CL_DEVICE_MAX_WORK_GROUP_SIZE>();
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}
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// Print out device information
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std::cout << "Using OpenCL device " << getDeviceName(device_index) << std::endl;
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std::cout << "Driver: " << getDeviceDriver(device_index) << std::endl;
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std::cout << "Reduction kernel config: " << dot_num_groups << " groups of size " << dot_wgsize << std::endl;
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context = cl::Context(device);
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queue = cl::CommandQueue(context);
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// Create program
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cl::Program program(context, kernels);
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std::ostringstream args;
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args << "-DstartScalar=" << startScalar << " ";
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if (sizeof(T) == sizeof(double))
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{
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args << "-DTYPE=double";
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// Check device can do double
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if (!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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try
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{
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program.build(args.str().c_str());
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}
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catch (cl::Error& err)
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{
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if (err.err() == CL_BUILD_PROGRAM_FAILURE)
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{
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std::cout << program.getBuildInfo<CL_PROGRAM_BUILD_LOG>()[0].second << std::endl;
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throw err;
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}
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}
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}
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else if (sizeof(T) == sizeof(float))
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{
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args << "-DTYPE=float";
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program.build(args.str().c_str());
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}
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// Create kernels
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init_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer, cl::Buffer, T, T, T>(program, "init");
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copy_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer>(program, "copy");
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mul_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer>(program, "mul");
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add_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer, cl::Buffer>(program, "add");
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triad_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer, cl::Buffer>(program, "triad");
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nstream_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer, cl::Buffer>(program, "nstream");
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dot_kernel = new cl::KernelFunctor<cl::Buffer, cl::Buffer, cl::Buffer, cl::LocalSpaceArg, cl_int>(program, "stream_dot");
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array_size = ARRAY_SIZE;
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// Check buffers fit on the device
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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 < sizeof(T)*ARRAY_SIZE)
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throw std::runtime_error("Device cannot allocate a buffer big enough");
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if (totalmem < 3*sizeof(T)*ARRAY_SIZE)
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throw std::runtime_error("Device does not have enough memory for all 3 buffers");
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// Create buffers
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d_a = cl::Buffer(context, CL_MEM_READ_WRITE, sizeof(T) * ARRAY_SIZE);
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d_b = cl::Buffer(context, CL_MEM_READ_WRITE, sizeof(T) * ARRAY_SIZE);
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d_c = cl::Buffer(context, CL_MEM_READ_WRITE, sizeof(T) * ARRAY_SIZE);
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d_sum = cl::Buffer(context, CL_MEM_WRITE_ONLY, sizeof(T) * dot_num_groups);
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sums = std::vector<T>(dot_num_groups);
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}
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template <class T>
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OCLStream<T>::~OCLStream()
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{
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delete init_kernel;
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delete copy_kernel;
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delete mul_kernel;
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delete add_kernel;
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delete triad_kernel;
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delete nstream_kernel;
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delete dot_kernel;
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devices.clear();
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}
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template <class T>
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void OCLStream<T>::copy()
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{
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(*copy_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(array_size)),
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d_a, d_c
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);
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queue.finish();
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}
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template <class T>
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void OCLStream<T>::mul()
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{
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(*mul_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(array_size)),
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d_b, d_c
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);
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queue.finish();
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}
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template <class T>
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void OCLStream<T>::add()
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{
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(*add_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(array_size)),
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d_a, d_b, d_c
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);
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queue.finish();
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}
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template <class T>
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void OCLStream<T>::triad()
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{
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(*triad_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(array_size)),
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d_a, d_b, d_c
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);
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queue.finish();
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}
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template <class T>
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void OCLStream<T>::nstream()
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{
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(*nstream_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(array_size)),
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d_a, d_b, d_c
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);
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queue.finish();
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}
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template <class T>
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T OCLStream<T>::dot()
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{
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(*dot_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(dot_num_groups*dot_wgsize), cl::NDRange(dot_wgsize)),
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d_a, d_b, d_sum, cl::Local(sizeof(T) * dot_wgsize), array_size
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);
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cl::copy(queue, d_sum, sums.begin(), sums.end());
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T sum = 0.0;
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for (T val : sums)
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sum += val;
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return sum;
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}
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template <class T>
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void OCLStream<T>::init_arrays(T initA, T initB, T initC)
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{
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(*init_kernel)(
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cl::EnqueueArgs(queue, cl::NDRange(array_size)),
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d_a, d_b, d_c, initA, initB, initC
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);
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queue.finish();
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}
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template <class T>
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void OCLStream<T>::read_arrays(std::vector<T>& a, std::vector<T>& b, std::vector<T>& c)
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{
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cl::copy(queue, d_a, a.begin(), a.end());
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cl::copy(queue, d_b, b.begin(), b.end());
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cl::copy(queue, d_c, c.begin(), c.end());
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}
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void getDeviceList(void)
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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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cl::Platform::get(&platforms);
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// Enumerate devices
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for (unsigned i = 0; i < platforms.size(); i++)
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{
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std::vector<cl::Device> plat_devices;
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platforms[i].getDevices(CL_DEVICE_TYPE_ALL, &plat_devices);
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devices.insert(devices.end(), plat_devices.begin(), plat_devices.end());
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}
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cached = true;
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}
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void listDevices(void)
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{
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getDeviceList();
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// Print device names
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if (devices.size() == 0)
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{
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std::cerr << "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 (int i = 0; i < devices.size(); i++)
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{
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std::cout << i << ": " << getDeviceName(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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std::string getDeviceName(const int device)
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{
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if (!cached)
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getDeviceList();
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std::string name;
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cl_device_info info = CL_DEVICE_NAME;
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if (device < devices.size())
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{
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devices[device].getInfo(info, &name);
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}
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else
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{
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throw std::runtime_error("Error asking for name for non-existant device");
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}
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return name;
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}
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std::string getDeviceDriver(const int device)
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{
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if (!cached)
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getDeviceList();
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std::string driver;
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if (device < devices.size())
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{
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devices[device].getInfo(CL_DRIVER_VERSION, &driver);
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}
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else
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{
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throw std::runtime_error("Error asking for driver for non-existant device");
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}
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return driver;
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}
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template class OCLStream<float>;
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template class OCLStream<double>;
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