我在OpenCL中有一个项目。它是GPU上的矩阵分解。所有的工作正常,结果是好的。我看到的唯一情况是,当我连续多次执行程序(每秒大约一次)时,当我将初始缓冲区写入设备时,会遇到访问冲突。将缓冲区写入设备时出现OpenCL访问冲突
它总是在写入它被卡住的缓冲区。我对OpenCL非常陌生,我想知道如果我退出程序时是否必须清除GPU中的内存?有时它在第一次运行时崩溃,但在2或3次尝试后成功。然后再次,有时立即成功,以及随后的运行。这只是非常随机的。失败的实际缓冲区写入也会不时发生变化。有时第三个缓冲区写入失败,有时是第四个。
我运行此程序的参数是工作组大小为7和70 * 70元素的矩阵。起初我认为这可能是因为我的矩阵对于GPU来说太大(GT650M有2GB),但是有时候也会使用一个矩阵为O.000的元素来运行。
直到缓冲区写入的代码如下所示。
任何帮助,非常感谢。 Ps:为了清楚起见,PRECISION
是一个宏#define PRECISION float
。
int main(int argc, char *argv[])
{
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//// INITIALIZATION PART ///////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
try {
if (argc != 5) {
std::ostringstream oss;
oss << "Usage: " << argv[0] << " <kernel_file> <kernel_name> <workgroup_size> <array width>";
throw std::runtime_error(oss.str());
}
// Read in arguments.
std::string kernel_file(argv[1]);
std::string kernel_name(argv[2]);
unsigned int workgroup_size = atoi(argv[3]);
unsigned int array_dimension = atoi(argv[4]);
int total_matrix_length = array_dimension * array_dimension;
int total_workgroups = total_matrix_length/workgroup_size;
total_workgroups += total_matrix_length % workgroup_size == 0 ? 0 : 1;
// Print parameters
std::cout << "Workgroup size: " << workgroup_size << std::endl;
std::cout << "Total workgroups: " << total_workgroups << std::endl;
std::cout << "Array dimension: " << array_dimension << " x " << array_dimension << std::endl;
std::cout << "Total elements: " << total_matrix_length << std::endl;
// OpenCL initialization
std::vector<cl::Platform> platforms;
std::vector<cl::Device> devices;
cl::Platform::get(&platforms);
platforms[0].getDevices(CL_DEVICE_TYPE_GPU, &devices);
cl::Context context(devices);
cl::CommandQueue queue(context, devices[0], CL_QUEUE_PROFILING_ENABLE);
// Load the kernel source.
std::string file_text;
std::ifstream file_stream(kernel_file.c_str());
if (!file_stream) {
std::ostringstream oss;
oss << "There is no file called " << kernel_file;
throw std::runtime_error(oss.str());
}
file_text.assign(std::istreambuf_iterator<char>(file_stream), std::istreambuf_iterator<char>());
// Compile the kernel source.
std::string source_code = file_text;
std::pair<const char *, size_t> source(source_code.c_str(), source_code.size());
cl::Program::Sources sources;
sources.push_back(source);
cl::Program program(context, sources);
try {
program.build(devices);
}
catch (cl::Error& e) {
getchar();
std::string msg;
program.getBuildInfo<std::string>(devices[0], CL_PROGRAM_BUILD_LOG, &msg);
std::cerr << "Your kernel failed to compile" << std::endl;
std::cerr << "-----------------------------" << std::endl;
std::cerr << msg;
throw(e);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//// CREATE RANDOM INPUT DATA //////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Create matrix to work on.
// Create a random array.
int matrix_width = sqrt(total_matrix_length);
PRECISION* random_matrix = new PRECISION[total_matrix_length];
random_matrix = randommatrix(total_matrix_length);
PRECISION* A = new PRECISION[total_matrix_length];
for (int i = 0; i < total_matrix_length; i++)
A[i] = random_matrix[i];
PRECISION* L_SEQ = new PRECISION[total_matrix_length];
PRECISION* U_SEQ = new PRECISION[total_matrix_length];
PRECISION* P_SEQ = new PRECISION[total_matrix_length];
// Do the sequential algorithm.
decompose(A, L_SEQ, U_SEQ, P_SEQ, matrix_width);
float* PA = multiply(P_SEQ, A, total_matrix_length);
float* LU = multiply(L_SEQ, U_SEQ, total_matrix_length);
std::cout << "PA = LU?" << std::endl;
bool eq = equalMatrices(PA, LU, total_matrix_length);
std::cout << eq << std::endl;
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//// RUN AND SETUP KERNELS /////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Initialize arrays for GPU.
PRECISION* L_PAR = new PRECISION[total_matrix_length];
PRECISION* U_PAR = new PRECISION[total_matrix_length];
PRECISION* P_PAR = new PRECISION[total_matrix_length];
PRECISION* ROW_IDX = new PRECISION[matrix_width];
PRECISION* ROW_VAL = new PRECISION[matrix_width];
// Write A to U and initialize P.
for (int i = 0; i < total_matrix_length; i++)
U_PAR[i] = A[i];
// Initialize P_PAR.
for (int row = 0; row < matrix_width; row++)
{
for (int i = 0; i < matrix_width; i++)
IDX(P_PAR, row, i) = 0;
IDX(P_PAR, row, row) = 1;
}
// Allocate memory on the device
cl::Buffer P_BUFF(context, CL_MEM_READ_WRITE, total_matrix_length*sizeof(PRECISION));
cl::Buffer L_BUFF(context, CL_MEM_READ_WRITE, total_matrix_length*sizeof(PRECISION));
cl::Buffer U_BUFF(context, CL_MEM_READ_WRITE, total_matrix_length*sizeof(PRECISION));
// Buffer to determine maximum row value.
cl::Buffer MAX_ROW_IDX_BUFF(context, CL_MEM_READ_WRITE, total_workgroups*sizeof(PRECISION));
cl::Buffer MAX_ROW_VAL_BUFF(context, CL_MEM_READ_WRITE, total_workgroups*sizeof(PRECISION));
// Create the actual kernels.
cl::Kernel kernel(program, kernel_name.c_str());
std::string max_row_kernel_name = "max_row";
cl::Kernel max_row(program, max_row_kernel_name.c_str());
std::string swap_row_kernel_name = "swap_row";
cl::Kernel swap_row(program, swap_row_kernel_name.c_str());
// transfer source data from the host to the device
std::cout << "Writing buffers" << std::endl;
queue.enqueueWriteBuffer(P_BUFF, CL_TRUE, 0, total_matrix_length*sizeof(PRECISION), P_PAR);
queue.enqueueWriteBuffer(L_BUFF, CL_TRUE, 0, total_matrix_length*sizeof(PRECISION), L_PAR);
queue.enqueueWriteBuffer(U_BUFF, CL_TRUE, 0, total_matrix_length*sizeof(PRECISION), U_PAR);
queue.enqueueWriteBuffer(MAX_ROW_IDX_BUFF, CL_TRUE, 0, total_workgroups*sizeof(PRECISION), ROW_IDX);
queue.enqueueWriteBuffer(MAX_ROW_VAL_BUFF, CL_TRUE, 0, total_workgroups*sizeof(PRECISION), ROW_VAL);
完整的错误,当我与调试器钩子,我得到的是这样的:
Unhandled exception at 0x55903CC0 (nvopencl.dll) in Project.exe:
0xC0000005: Access violation reading location 0x0068F004.
If there is a handler for this exception, the program may be safely continued.
调试器显示我的下面,在命名空间cl
功能:
cl_int enqueueWriteBuffer(
const Buffer& buffer,
cl_bool blocking,
::size_t offset,
::size_t size,
const void* ptr,
const VECTOR_CLASS<Event>* events = NULL,
Event* event = NULL) const
{
return detail::errHandler(
::clEnqueueWriteBuffer(
object_, buffer(), blocking, offset, size,
ptr,
(events != NULL) ? (cl_uint) events->size() : 0,
(events != NULL && events->size() > 0) ? (cl_event*) &events->front() : NULL,
(cl_event*) event),
__ENQUEUE_WRITE_BUFFER_ERR);
编辑:完整源代码here。
这是导致错误的原因。谢谢! – 2014-11-01 11:11:07
非常感谢你,即使它是一个旧帖子,真的保存了我的培根! – 2016-07-05 20:36:12