使用std::vector的OpenCL矩阵乘法

我正试图使用OpenCl来预处理向量乘法，而代码本身似乎可以工作——返回的结果要么是垃圾，要么是零。据我所知，内核似乎没有接收到正确的值，或者我在这里缺少了一些不明显的东西，是什么？我以为这是我分配缓冲区的方式，但我不确定。

#define CL_USE_DEPRECATED_OPENCL_2_0_APIS
#include <iostream>
#include <fstream>
#include <sstream>
#include "./cl.hpp"
void populate_vector(std::vector<float> &vect, std::stringstream &readStream) {
std::string x;
std::string fStripped;
float readFloat;
while(std::getline(readStream, x, ',')){
std::stringstream elementStream;
elementStream << x;
std::getline(elementStream, fStripped, 'f');
elementStream << fStripped;
elementStream >> readFloat;
vect.push_back(readFloat);
}
}
int main()
{
std::vector<cl::Platform> platforms;
cl::Platform::get(&platforms);
if(platforms.empty()){
throw std::runtime_error("No Platforms found, check OpenCL installation.");
}
cl::Platform platform = platforms[0];
std::cout << "Using Platform: " << platform.getInfo<CL_PLATFORM_NAME>() << std::endl;
std::vector<cl::Device> devices;
platform.getDevices(CL_DEVICE_TYPE_GPU, &devices);
if(devices.empty()){
throw std::runtime_error ("No Devices Found, check installation.");
}
cl::Device device = devices[0];
// Create an execusion context
cl::Context context(device);
cl::CommandQueue queue(context,device);

// Load the kernel sources, use global memory
std::ifstream fs("mCrossProd.cl");
if(!fs.is_open()){
throw  std::runtime_error("Cannot open kernel source file.");
}
// Extract kernel code
std::stringstream ss;
ss << fs.rdbuf();
auto code = ss.str();
cl::Program::Sources sources;
sources.push_back({code.c_str(), code.length()});
fs.close();
// Build the kernel
cl::Program program(context, sources);
if(program.build({device})!= CL_SUCCESS){
std::cout << " Error building: " << program.getBuildInfo<CL_PROGRAM_BUILD_LOG>(device) << "n";
exit(1);
}
// Output matrix dimensions
int M = 4, N = 3, K = 6;
int A_dims = M * K;
int B_dims = N * K;
int C_dims = M * N;
// Create buffers for device
cl::Buffer buffer_A(context,CL_MEM_READ_WRITE,sizeof(float)*A_dims);
cl::Buffer buffer_B(context,CL_MEM_READ_WRITE,sizeof(float)*B_dims);
cl::Buffer buffer_C(context,CL_MEM_READ_WRITE,sizeof(float)*C_dims);
std::string s;
std::vector<float> A;
std::vector<float> B;
std::vector<float> C;
std::ifstream infile("matrices.txt");
std::cout << "Opened file to read" << 'n';

std::getline(infile,s);
//std::cout << s;
std::stringstream mss(s);
populate_vector(A, mss);   
std::copy(A.begin(), A.end(), std::ostream_iterator<float>(std::cout, ", "));
std::cout << 'n';
mss.str("");
mss.clear();
std::getline(infile,s);
mss << s;
populate_vector(B, mss);  
std::copy(B.begin(), B.end(), std::ostream_iterator<float>(std::cout, ", "));
std::cout << 'n';
mss.str("");
mss.clear();
std::getline(infile,s);
mss << s;
populate_vector(C, mss);
std::copy(C.begin(), C.end(), std::ostream_iterator<float>(std::cout, ", "));
std::cout << 'n';


//write arrays A and B to the device
queue.enqueueWriteBuffer(buffer_A,CL_TRUE,0,A.size()*sizeof(float),&A);
queue.enqueueWriteBuffer(buffer_B,CL_TRUE,0,B.size()*sizeof(float),&B);
std::cout << A.size() * sizeof(float) << 'n';
std::cout << B.size() * sizeof(float) << 'n';
std::cout << C.size() * sizeof(float) << 'n';
// Select kernel, pass arguments
cl::Kernel kernel = cl::Kernel(program, "mCrossProd");
kernel.setArg(0, M);
kernel.setArg(1, N);
kernel.setArg(2, K);
kernel.setArg(3, buffer_A);
kernel.setArg(4, buffer_B);
kernel.setArg(5, buffer_C);
// Execute kernel
if( queue.enqueueNDRangeKernel(kernel,cl::NullRange,cl::NDRange(M,N),cl::NDRange(1,1)) != CL_SUCCESS )
{
std::cout << "Failed to launch kernel" << std::endl;
exit(1);
}
queue.finish();
// read result C from the device to array C
queue.enqueueReadBuffer(buffer_C,CL_TRUE,0,C.size(),&C[0]);
std::cout << C.size() << std::endl;
std::cout << C_dims << std::endl;
std::cout << M << " " << N << std::endl;
std::cout << "nThe solution is" << std::endl;
std::copy(C.begin(), C.end(), std::ostream_iterator<float>(std::cout, ", "));
std::cout << 'n';
for(int i = 0; i < M; i++) {
for(int j = 0; j < N; j++) {
std::cout << "C[" + std::to_string(i*N+j) + "] = ";
std::cout << C[i*N+j] << " ";
}
std::cout << std::endl;
}
}

测试内核

__kernel void mCrossProd(const int M, const int N, const int K, __global float* A, __global float* B, __global float* C) {
int const i = get_global_id(0);
int const j = get_global_id(1);
int const debug_elem_id = 3; // purely for debug purposes.
for(int k = 0; k < K; k++){
C[i*N+j] += A[i*K+k] * B[N*k+j];
if((i*N+j)==debug_elem_id)
{   
//printf("PROD, i = %d, j = %d, k = %d, N = %dn", i,j,k,N);
printf("PROD, %.2fn", A[i*K+k] * B[N*k+j]);
printf("SUM: %.2fn", C[i*N+j]);
}
}
}

matrix.txt 的内容

1.5f, 1.0f, 2.0f, 2.0f, 4.0f, 1.0f, 4.0f, 2.0f, 1.0f, 1.0f, 0.0f, 0.0f, 3.0f, 2.0f, 5.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 2.0f, 1.0f, 1.0f
1.5f, 2.0f, 4.0f, 1.0f, 1.0f, 2.0f, 4.0f, 2.0f, 1.0f, 0.0f, 0.0f, 1.0f, 9.0f, 2.0f, 1.0f, 2.0f, 1.0f, 0.0f
0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f