int main(void)
{
float *h_A; // A matrix
float *h_B; // B matrix
float *h_C; // C = A*B matrix
int Mdim, Ndim, Pdim; // A[N][P], B[P][M], C[N][M]
int szA, szB, szC; // number of elements in each matrix
cl_mem d_a, d_b, d_c; // Matrices in device memory
double start_time; // Starting time
double run_time; // timing data
char * kernelsource; // kernel source string
cl_int err; // error code returned from OpenCL calls
cl_device_id device_id; // compute device id
cl_context context; // compute context
cl_command_queue commands; // compute command queue
cl_program program; // compute program
cl_kernel kernel; // compute kernel
Ndim = ORDER;
Pdim = ORDER;
Mdim = ORDER;
szA = Ndim * Pdim;
szB = Pdim * Mdim;
szC = Ndim * Mdim;
h_A = (float *)malloc(szA * sizeof(float));
h_B = (float *)malloc(szB * sizeof(float));
h_C = (float *)malloc(szC * sizeof(float));
initmat(Mdim, Ndim, Pdim, h_A, h_B, h_C);
printf("\n===== Sequential, matrix mult (dot prod), order %d on host CPU ======\n",ORDER);
for(int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
seq_mat_mul_sdot(Mdim, Ndim, Pdim, h_A, h_B, h_C);
run_time = wtime() - start_time;
results(Mdim, Ndim, Pdim, h_C, run_time);
}
//--------------------------------------------------------------------------------
// Create a context, queue and device.
//--------------------------------------------------------------------------------
// Set up OpenCL context. queue, kernel, etc.
cl_uint numPlatforms;
// Find number of platforms
err = clGetPlatformIDs(0, NULL, &numPlatforms);
if (err != CL_SUCCESS || numPlatforms <= 0)
{
printf("Error: Failed to find a platform!\n%s\n",err_code(err));
return EXIT_FAILURE;
}
// Get all platforms
cl_platform_id Platform[numPlatforms];
err = clGetPlatformIDs(numPlatforms, Platform, NULL);
if (err != CL_SUCCESS || numPlatforms <= 0)
{
printf("Error: Failed to get the platform!\n%s\n",err_code(err));
return EXIT_FAILURE;
}
// Secure a device
for (int i = 0; i < numPlatforms; i++)
{
err = clGetDeviceIDs(Platform[i], DEVICE, 1, &device_id, NULL);
if (err == CL_SUCCESS)
break;
}
if (device_id == NULL)
{
printf("Error: Failed to create a device group!\n%s\n",err_code(err));
return EXIT_FAILURE;
}
// Create a compute context
context = clCreateContext(0, 1, &device_id, NULL, NULL, &err);
if (!context)
{
printf("Error: Failed to create a compute context!\n%s\n",err_code(err));
return EXIT_FAILURE;
}
// Create a command queue
commands = clCreateCommandQueue(context, device_id, 0, &err);
if (!commands)
{
printf("Error: Failed to create a command commands!\n%s\n", err_code(err));
return EXIT_FAILURE;
}
//--------------------------------------------------------------------------------
// Setup the buffers, initialize matrices, and write them into global memory
//--------------------------------------------------------------------------------
// Reset A, B and C matrices (just to play it safe)
initmat(Mdim, Ndim, Pdim, h_A, h_B, h_C);
d_a = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(float) * szA, h_A, &err);
if (err != CL_SUCCESS)
{
printf("Error: failed to create buffer\n%s\n", err_code(err));
return EXIT_FAILURE;
}
d_b = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(float) * szB, h_B, &err);
if (err != CL_SUCCESS)
{
printf("Error: failed to create buffer\n%s\n", err_code(err));
return EXIT_FAILURE;
}
d_c = clCreateBuffer(context, CL_MEM_WRITE_ONLY,
sizeof(float) * szC, NULL, &err);
if (err != CL_SUCCESS)
{
printf("Error: failed to create buffer\n%s\n", err_code(err));
return EXIT_FAILURE;
}
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... Naive
//--------------------------------------------------------------------------------
kernelsource = getKernelSource("../C_elem.cl");
// Create the comput program from the source buffer
program = clCreateProgramWithSource(context, 1, (const char **) & kernelsource, NULL, &err);
if (err != CL_SUCCESS)
{
printf("Error: could not create program\n%s\n", err_code(err));
return EXIT_FAILURE;
}
free(kernelsource);
// Build the program
err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
if (err != CL_SUCCESS)
{
size_t len;
char buffer[2048];
printf("Error: Failed to build program executable!\n%s\n", err_code(err));
clGetProgramBuildInfo(program, device_id, CL_PROGRAM_BUILD_LOG, sizeof(buffer), buffer, &len);
printf("%s\n", buffer);
return EXIT_FAILURE;
}
// Create the compute kernel from the program
kernel = clCreateKernel(program, "mmul", &err);
if (!kernel || err != CL_SUCCESS)
{
printf("Error: Failed to create compute kernel!\n%s\n", err_code(err));
return EXIT_FAILURE;
}
printf("\n===== OpenCL, matrix mult, C(i,j) per work item, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
err = clSetKernelArg(kernel, 0, sizeof(int), &Mdim);
err |= clSetKernelArg(kernel, 1, sizeof(int), &Ndim);
err |= clSetKernelArg(kernel, 2, sizeof(int), &Pdim);
err |= clSetKernelArg(kernel, 3, sizeof(cl_mem), &d_a);
err |= clSetKernelArg(kernel, 4, sizeof(cl_mem), &d_b);
err |= clSetKernelArg(kernel, 5, sizeof(cl_mem), &d_c);
if (err != CL_SUCCESS)
{
printf("Error: Could not set kernel arguments\n");
return EXIT_FAILURE;
}
start_time = wtime();
// Execute the kernel over the entire range of C matrix elements ... computing
// a dot product for each element of the product matrix. The local work
// group size is set to NULL ... so I'm telling the OpenCL runtime to
// figure out a local work group size for me.
const size_t global[2] = {Ndim, Mdim};
err = clEnqueueNDRangeKernel(
commands,
kernel,
2, NULL,
global, NULL,
0, NULL, NULL);
if (err != CL_SUCCESS)
{
printf("Error: Failed to execute kernel\n%s\n", err_code(err));
return EXIT_FAILURE;
}
err = clFinish(commands);
if (err != CL_SUCCESS)
{
printf("Error: waiting for queue to finish failed\n%s\n", err_code(err));
return EXIT_FAILURE;
}
run_time = wtime() - start_time;
err = clEnqueueReadBuffer(
commands, d_c, CL_TRUE, 0,
sizeof(float) * szC, h_C,
0, NULL, NULL);
if (err != CL_SUCCESS)
{
printf("Error: Failed to read buffer\n%s\n", err_code(err));
return EXIT_FAILURE;
}
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item
//--------------------------------------------------------------------------------
kernelsource = getKernelSource("../C_row.cl");
// Create the comput program from the source buffer
program = clCreateProgramWithSource(context, 1, (const char **) & kernelsource, NULL, &err);
if (err != CL_SUCCESS)
{
printf("Error: could not create program\n%s\n", err_code(err));
return EXIT_FAILURE;
}
free(kernelsource);
// Build the program
err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
if (err != CL_SUCCESS)
{
size_t len;
char buffer[2048];
printf("Error: Failed to build program executable!\n%s\n", err_code(err));
clGetProgramBuildInfo(program, device_id, CL_PROGRAM_BUILD_LOG, sizeof(buffer), buffer, &len);
printf("%s\n", buffer);
return EXIT_FAILURE;
}
// Create the compute kernel from the program
kernel = clCreateKernel(program, "mmul", &err);
if (!kernel || err != CL_SUCCESS)
{
printf("Error: Failed to create compute kernel!\n%s\n", err_code(err));
return EXIT_FAILURE;
}
printf("\n===== OpenCL, matrix mult, C row per work item, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
err = clSetKernelArg(kernel, 0, sizeof(int), &Mdim);
err |= clSetKernelArg(kernel, 1, sizeof(int), &Ndim);
err |= clSetKernelArg(kernel, 2, sizeof(int), &Pdim);
err |= clSetKernelArg(kernel, 3, sizeof(cl_mem), &d_a);
err |= clSetKernelArg(kernel, 4, sizeof(cl_mem), &d_b);
err |= clSetKernelArg(kernel, 5, sizeof(cl_mem), &d_c);
if (err != CL_SUCCESS)
{
printf("Error: Could not set kernel arguments\n");
return EXIT_FAILURE;
}
start_time = wtime();
// Execute the kernel over the rows of the C matrix ... computing
// a dot product for each element of the product matrix.
const size_t global = Ndim;
err = clEnqueueNDRangeKernel(
commands,
kernel,
1, NULL,
&global, NULL,
0, NULL, NULL);
if (err != CL_SUCCESS)
{
printf("Error: Failed to execute kernel\n%s\n", err_code(err));
return EXIT_FAILURE;
}
err = clFinish(commands);
if (err != CL_SUCCESS)
{
printf("Error: waiting for queue to finish failed\n%s\n", err_code(err));
return EXIT_FAILURE;
}
run_time = wtime() - start_time;
err = clEnqueueReadBuffer(
commands, d_c, CL_TRUE, 0,
sizeof(float) * szC, h_C,
0, NULL, NULL);
if (err != CL_SUCCESS)
{
printf("Error: Failed to read buffer\n%s\n", err_code(err));
return EXIT_FAILURE;
}
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item, A row in pivate memory
//--------------------------------------------------------------------------------
kernelsource = getKernelSource("../C_row_priv.cl");
// Create the comput program from the source buffer
program = clCreateProgramWithSource(context, 1, (const char **) & kernelsource, NULL, &err);
if (err != CL_SUCCESS)
{
printf("Error: could not create program\n%s\n", err_code(err));
return EXIT_FAILURE;
}
free(kernelsource);
// Build the program
err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
if (err != CL_SUCCESS)
{
size_t len;
char buffer[2048];
printf("Error: Failed to build program executable!\n%s\n", err_code(err));
clGetProgramBuildInfo(program, device_id, CL_PROGRAM_BUILD_LOG, sizeof(buffer), buffer, &len);
printf("%s\n", buffer);
return EXIT_FAILURE;
}
// Create the compute kernel from the program
kernel = clCreateKernel(program, "mmul", &err);
if (!kernel || err != CL_SUCCESS)
{
printf("Error: Failed to create compute kernel!\n%s\n", err_code(err));
return EXIT_FAILURE;
}
printf("\n===== OpenCL, matrix mult, C row, A row in priv mem, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
err = clSetKernelArg(kernel, 0, sizeof(int), &Mdim);
err |= clSetKernelArg(kernel, 1, sizeof(int), &Ndim);
err |= clSetKernelArg(kernel, 2, sizeof(int), &Pdim);
err |= clSetKernelArg(kernel, 3, sizeof(cl_mem), &d_a);
err |= clSetKernelArg(kernel, 4, sizeof(cl_mem), &d_b);
err |= clSetKernelArg(kernel, 5, sizeof(cl_mem), &d_c);
if (err != CL_SUCCESS)
{
printf("Error: Could not set kernel arguments\n");
return EXIT_FAILURE;
}
start_time = wtime();
// Execute the kernel over the rows of the C matrix ... computing
// a dot product for each element of the product matrix.
const size_t global = Ndim;
const size_t local = ORDER / 16;
err = clEnqueueNDRangeKernel(
commands,
kernel,
1, NULL,
&global, &local,
0, NULL, NULL);
if (err != CL_SUCCESS)
{
printf("Error: Failed to execute kernel\n%s\n", err_code(err));
return EXIT_FAILURE;
}
err = clFinish(commands);
if (err != CL_SUCCESS)
{
printf("Error: waiting for queue to finish failed\n%s\n", err_code(err));
return EXIT_FAILURE;
}
run_time = wtime() - start_time;
err = clEnqueueReadBuffer(
commands, d_c, CL_TRUE, 0,
sizeof(float) * szC, h_C,
0, NULL, NULL);
if (err != CL_SUCCESS)
{
printf("Error: Failed to read buffer\n%s\n", err_code(err));
return EXIT_FAILURE;
}
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// Clean up!
//--------------------------------------------------------------------------------
free(h_A);
free(h_B);
free(h_C);
clReleaseMemObject(d_a);
clReleaseMemObject(d_b);
clReleaseMemObject(d_c);
clReleaseProgram(program);
clReleaseKernel(kernel);
clReleaseCommandQueue(commands);
clReleaseContext(context);
return EXIT_SUCCESS;
}
int main(void)
{
int Mdim, Ndim, Pdim; // A[N][P], B[P][M], C[N][M]
int szA, szB, szC; // number of elements in each matrix
double start_time; // Starting time
double run_time; // timing data
Ndim = ORDER;
Pdim = ORDER;
Mdim = ORDER;
szA = Ndim * Pdim;
szB = Pdim * Mdim;
szC = Ndim * Mdim;
std::vector<float> h_A(szA); // Host memory for Matrix A
std::vector<float> h_B(szB); // Host memory for Matrix B
std::vector<float> h_C(szC); // Host memory for Matrix C
cl::Buffer d_a, d_b, d_c; // Matrices in device memory
initmat(Mdim, Ndim, Pdim, h_A, h_B, h_C);
printf("\n===== Sequential, matrix mult (dot prod), order %d on host CPU ======\n",ORDER);
for(int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
seq_mat_mul_sdot(Mdim, Ndim, Pdim, h_A, h_B, h_C);
run_time = wtime() - start_time;
results(Mdim, Ndim, Pdim, h_C, run_time);
}
try
{
//--------------------------------------------------------------------------------
// Create a context and queue for DEVICE
//--------------------------------------------------------------------------------
cl::Context context(DEVICE);
cl::CommandQueue queue(context);
//--------------------------------------------------------------------------------
// Setup the buffers, initialize matrices, and write them into global memory
//--------------------------------------------------------------------------------
// Reset A, B and C matrices (just to play it safe)
initmat(Mdim, Ndim, Pdim, h_A, h_B, h_C);
d_a = cl::Buffer(context, begin(h_A), end(h_A), true);
d_b = cl::Buffer(context, begin(h_B), end(h_B), true);
d_c = cl::Buffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * szC);
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... Naive
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
cl::Program program(context, util::loadProgram("../C_elem.cl"), true);
// Create the compute kernel from the program
auto naive_mmul = cl::make_kernel<int, int, int, cl::Buffer, cl::Buffer, cl::Buffer>(program, "mmul");
printf("\n===== OpenCL, matrix mult, C(i,j) per work item, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
// Execute the kernel over the entire range of C matrix elements ... computing
// a dot product for each element of the product matrix. The local work
// group size is set to NULL ... so I'm telling the OpenCL runtime to
// figure out a local work group size for me.
cl::NDRange global(Ndim, Mdim);
naive_mmul(cl::EnqueueArgs(queue, global),
Mdim, Ndim, Pdim, d_a, d_b, d_c);
queue.finish();
run_time = wtime() - start_time;
cl::copy(queue, d_c, begin(h_C), end(h_C));
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
program = cl::Program(context, util::loadProgram("../C_row.cl"), true);
// Create the compute kernel from the program
auto crow_mmul = cl::make_kernel<int, int, int, cl::Buffer, cl::Buffer, cl::Buffer>(program, "mmul");
printf("\n===== OpenCL, matrix mult, C row per work item, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
cl::NDRange global(Ndim);
crow_mmul(cl::EnqueueArgs(queue, global),
Mdim, Ndim, Pdim, d_a, d_b, d_c);
queue.finish();
run_time = wtime() - start_time;
cl::copy(queue, d_c, begin(h_C), end(h_C));
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item, A row in pivate memory
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
program = cl::Program(context, util::loadProgram("../C_row_priv.cl"), true);
// Create the compute kernel from the program
auto arowpriv_mmul = cl::make_kernel<int, int, int, cl::Buffer, cl::Buffer, cl::Buffer>(program, "mmul");
printf("\n===== OpenCL, matrix mult, C row, A row in priv mem, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
cl::NDRange global(Ndim);
cl::NDRange local(ORDER / 16);
arowpriv_mmul(cl::EnqueueArgs(queue, global, local),
Mdim, Ndim, Pdim, d_a, d_b, d_c);
queue.finish();
run_time = wtime() - start_time;
cl::copy(queue, d_c, begin(h_C), end(h_C));
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item, A row pivate, B col local
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
program = cl::Program(context, util::loadProgram("../C_row_priv_bloc.cl"), true);
// Create the compute kernel from the program
auto browloc_mmul = cl::make_kernel<int, int, int, cl::Buffer, cl::Buffer, cl::Buffer, cl::LocalSpaceArg>(program, "mmul");
printf("\n===== OpenCL, mat mult, C row, priv A, B cols loc, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
cl::NDRange global(Ndim);
cl::NDRange local(ORDER / 16);
cl::LocalSpaceArg localmem = cl::Local(sizeof(float) * Pdim);
browloc_mmul(cl::EnqueueArgs(queue, global, local),
Mdim, Ndim, Pdim, d_a, d_b, d_c, localmem);
queue.finish();
run_time = wtime() - start_time;
cl::copy(queue, d_c, begin(h_C), end(h_C));
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... A and B in block form in local memory
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
program = cl::Program(context, util::loadProgram("../C_block_form.cl"), true);
// Create the compute kernel from the program
auto block_mmul = cl::make_kernel<int, int, int, cl::Buffer, cl::Buffer, cl::Buffer, cl::LocalSpaceArg, cl::LocalSpaceArg>(program, "mmul");
printf("\n===== OpenCL, A and B in block form in local memory, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = wtime();
int blocksize = 16;
cl::NDRange global(Ndim, Mdim);
cl::NDRange local(blocksize, blocksize);
cl::LocalSpaceArg localmem1 = cl::Local(sizeof(float) * blocksize * blocksize);
cl::LocalSpaceArg localmem2 = cl::Local(sizeof(float) * blocksize * blocksize);
block_mmul(cl::EnqueueArgs(queue, global, local),
Mdim, Ndim, Pdim, d_a, d_b, d_c, localmem1, localmem2);
queue.finish();
run_time = wtime() - start_time;
cl::copy(queue, d_c, begin(h_C), end(h_C));
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
} catch (cl::Error err)
{
std::cout << "Exception\n";
std::cerr << "ERROR: "
<< err.what()
<< "("
<< err_code(err.err())
<< ")"
<< std::endl;
}
return EXIT_SUCCESS;
}
int main(int argc, char *argv[])
{
int N; // A[N][N], B[N][N], C[N][N]
int size; // Number of elements in each matrix
double start_time; // Starting time
double run_time; // Timing
util::Timer timer; // Timing
N = ORDER;
size = N * N;
std::vector<float> h_A(size); // Host memory for Matrix A
std::vector<float> h_B(size); // Host memory for Matrix B
std::vector<float> h_C(size); // Host memory for Matrix C
cl::Buffer d_a, d_b, d_c; // Matrices in device memory
//--------------------------------------------------------------------------------
// Create a context and queue
//--------------------------------------------------------------------------------
try
{
cl_uint deviceIndex = 0;
parseArguments(argc, argv, &deviceIndex);
// Get list of devices
std::vector<cl::Device> devices;
unsigned numDevices = getDeviceList(devices);
// Check device index in range
if (deviceIndex >= numDevices)
{
std::cout << "Invalid device index (try '--list')\n";
return EXIT_FAILURE;
}
cl::Device device = devices[deviceIndex];
std::string name;
getDeviceName(device, name);
std::cout << "\nUsing OpenCL device: " << name << "\n";
std::vector<cl::Device> chosen_device;
chosen_device.push_back(device);
cl::Context context(chosen_device);
cl::CommandQueue queue(context, device);
//--------------------------------------------------------------------------------
// Run sequential matmul
//--------------------------------------------------------------------------------
initmat(N, h_A, h_B, h_C);
timer.reset();
printf("\n===== Sequential, matrix mult (dot prod), order %d on host CPU ======\n",N);
for(int i = 0; i < COUNT; i++)
{
zero_mat(N, h_C);
start_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0;
seq_mat_mul_sdot(N, h_A, h_B, h_C);
run_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0 - start_time;
results(N, h_C, run_time);
}
//--------------------------------------------------------------------------------
// Setup the buffers, initialize matrices, and write them into global memory
//--------------------------------------------------------------------------------
// Reset A, B and C matrices (just to play it safe)
initmat(N, h_A, h_B, h_C);
d_a = cl::Buffer(context, h_A.begin(), h_A.end(), true);
d_b = cl::Buffer(context, h_B.begin(), h_B.end(), true);
d_c = cl::Buffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * size);
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... Naive
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
cl::Program program(context, kernelsource, true);
// Create the compute kernel from the program
cl::make_kernel<int, cl::Buffer, cl::Buffer, cl::Buffer> naive_mmul(program, "mmul");
printf("\n===== OpenCL, matrix mult, C(i,j) per work item, order %d ======\n",N);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(N, h_C);
start_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0;
// Execute the kernel over the entire range of C matrix elements ... computing
// a dot product for each element of the product matrix. The local work
// group size is set to NULL ... so I'm telling the OpenCL runtime to
// figure out a local work group size for me.
cl::NDRange global(N, N);
naive_mmul(cl::EnqueueArgs(queue, global),
N, d_a, d_b, d_c);
queue.finish();
run_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0 - start_time;
cl::copy(queue, d_c, h_C.begin(), h_C.end());
results(N, h_C, run_time);
} // end for loop
} catch (cl::Error err)
{
std::cout << "Exception\n";
std::cerr << "ERROR: "
<< err.what()
<< "("
<< err_code(err.err())
<< ")"
<< std::endl;
}
return EXIT_SUCCESS;
}
int main(int argc, char *argv[])
{
float *h_A; // A matrix
float *h_B; // B matrix
float *h_C; // C = A*B matrix
int N; // A[N][N], B[N][N], C[N][N]
int size; // number of elements in each matrix
cl_mem d_a, d_b, d_c; // Matrices in device memory
double start_time; // Starting time
double run_time; // timing data
char * kernelsource; // kernel source string
cl_int err; // error code returned from OpenCL calls
cl_device_id device; // compute device id
cl_context context; // compute context
cl_command_queue commands; // compute command queue
cl_program program; // compute program
cl_kernel kernel; // compute kernel
N = ORDER;
size = N * N;
h_A = (float *)malloc(size * sizeof(float));
h_B = (float *)malloc(size * sizeof(float));
h_C = (float *)malloc(size * sizeof(float));
//--------------------------------------------------------------------------------
// Create a context, queue and device.
//--------------------------------------------------------------------------------
cl_uint deviceIndex = 0;
parseArguments(argc, argv, &deviceIndex);
// Get list of devices
cl_device_id devices[MAX_DEVICES];
unsigned numDevices = getDeviceList(devices);
// Check device index in range
if (deviceIndex >= numDevices)
{
printf("Invalid device index (try '--list')\n");
return EXIT_FAILURE;
}
device = devices[deviceIndex];
char name[MAX_INFO_STRING];
getDeviceName(device, name);
printf("\nUsing OpenCL device: %s\n", name);
// Create a compute context
context = clCreateContext(0, 1, &device, NULL, NULL, &err);
checkError(err, "Creating context");
// Create a command queue
commands = clCreateCommandQueue(context, device, 0, &err);
checkError(err, "Creating command queue");
//--------------------------------------------------------------------------------
// Run sequential version on the host
//--------------------------------------------------------------------------------
initmat(N, h_A, h_B, h_C);
printf("\n===== Sequential, matrix mult (dot prod), order %d on host CPU ======\n",ORDER);
for(int i = 0; i < COUNT; i++)
{
zero_mat(N, h_C);
start_time = wtime();
seq_mat_mul_sdot(N, h_A, h_B, h_C);
run_time = wtime() - start_time;
results(N, h_C, run_time);
}
//--------------------------------------------------------------------------------
// Setup the buffers, initialize matrices, and write them into global memory
//--------------------------------------------------------------------------------
// Reset A, B and C matrices (just to play it safe)
initmat(N, h_A, h_B, h_C);
d_a = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(float) * size, h_A, &err);
checkError(err, "Creating buffer d_a");
d_b = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(float) * size, h_B, &err);
checkError(err, "Creating buffer d_b");
d_c = clCreateBuffer(context, CL_MEM_WRITE_ONLY,
sizeof(float) * size, NULL, &err);
checkError(err, "Creating buffer d_c");
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... Naive
//--------------------------------------------------------------------------------
kernelsource = getKernelSource("../C_elem.cl");
// Create the comput program from the source buffer
program = clCreateProgramWithSource(context, 1, (const char **) & kernelsource, NULL, &err);
checkError(err, "Creating program with C_elem.cl");
free(kernelsource);
// Build the program
err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
if (err != CL_SUCCESS)
{
size_t len;
char buffer[2048];
printf("Error: Failed to build program executable!\n%s\n", err_code(err));
clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, sizeof(buffer), buffer, &len);
printf("%s\n", buffer);
return EXIT_FAILURE;
}
// Create the compute kernel from the program
kernel = clCreateKernel(program, "mmul", &err);
checkError(err, "Creating kernel from C_elem.cl");
printf("\n===== OpenCL, matrix mult, C(i,j) per work item, order %d ======\n",N);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(N, h_C);
err = clSetKernelArg(kernel, 0, sizeof(int), &N);
err |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &d_a);
err |= clSetKernelArg(kernel, 2, sizeof(cl_mem), &d_b);
err |= clSetKernelArg(kernel, 3, sizeof(cl_mem), &d_c);
checkError(err, "Setting kernel args");
start_time = wtime();
// Execute the kernel over the entire range of C matrix elements ... computing
// a dot product for each element of the product matrix. The local work
// group size is set to NULL ... so I'm telling the OpenCL runtime to
// figure out a local work group size for me.
const size_t global[2] = {N, N};
err = clEnqueueNDRangeKernel(
commands,
kernel,
2, NULL,
global, NULL,
0, NULL, NULL);
checkError(err, "Enqueueing kernel");
err = clFinish(commands);
checkError(err, "Waiting for kernel to finish");
run_time = wtime() - start_time;
err = clEnqueueReadBuffer(
commands, d_c, CL_TRUE, 0,
sizeof(float) * size, h_C,
0, NULL, NULL);
checkError(err, "Copying back d_c");
results(N, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item
//--------------------------------------------------------------------------------
kernelsource = getKernelSource("../C_row.cl");
// Create the comput program from the source buffer
program = clCreateProgramWithSource(context, 1, (const char **) & kernelsource, NULL, &err);
checkError(err, "Creating program with C_row.cl");
free(kernelsource);
// Build the program
err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
if (err != CL_SUCCESS)
{
size_t len;
char buffer[2048];
printf("Error: Failed to build program executable!\n%s\n", err_code(err));
clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, sizeof(buffer), buffer, &len);
printf("%s\n", buffer);
return EXIT_FAILURE;
}
// Create the compute kernel from the program
kernel = clCreateKernel(program, "mmul", &err);
checkError(err, "Creating kernel from C_row.cl");
printf("\n===== OpenCL, matrix mult, C row per work item, order %d ======\n",N);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(N, h_C);
err = clSetKernelArg(kernel, 0, sizeof(int), &N);
err |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &d_a);
err |= clSetKernelArg(kernel, 2, sizeof(cl_mem), &d_b);
err |= clSetKernelArg(kernel, 3, sizeof(cl_mem), &d_c);
checkError(err, "Setting kernel args");
start_time = wtime();
// Execute the kernel over the rows of the C matrix ... computing
// a dot product for each element of the product matrix.
const size_t global = N;
err = clEnqueueNDRangeKernel(
commands,
kernel,
1, NULL,
&global, NULL,
0, NULL, NULL);
checkError(err, "Enqueueing kernel");
err = clFinish(commands);
checkError(err, "Waiting for kernel to finish");
run_time = wtime() - start_time;
err = clEnqueueReadBuffer(
commands, d_c, CL_TRUE, 0,
sizeof(float) * size, h_C,
0, NULL, NULL);
checkError(err, "Reading back d_c");
results(N, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... C row per work item, A row in pivate memory
//--------------------------------------------------------------------------------
kernelsource = getKernelSource("../C_row_priv.cl");
// Create the comput program from the source buffer
program = clCreateProgramWithSource(context, 1, (const char **) & kernelsource, NULL, &err);
checkError(err, "Creating program from C_row_priv.cl");
free(kernelsource);
// Build the program
err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
if (err != CL_SUCCESS)
{
size_t len;
char buffer[2048];
printf("Error: Failed to build program executable!\n%s\n", err_code(err));
clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, sizeof(buffer), buffer, &len);
printf("%s\n", buffer);
return EXIT_FAILURE;
}
// Create the compute kernel from the program
kernel = clCreateKernel(program, "mmul", &err);
checkError(err, "Creating kernel from C_row_priv.cl");
printf("\n===== OpenCL, matrix mult, C row, A row in priv mem, order %d ======\n",N);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(N, h_C);
err = clSetKernelArg(kernel, 0, sizeof(int), &N);
err |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &d_a);
err |= clSetKernelArg(kernel, 2, sizeof(cl_mem), &d_b);
err |= clSetKernelArg(kernel, 3, sizeof(cl_mem), &d_c);
checkError(err, "Setting kernel args");
start_time = wtime();
// Execute the kernel over the rows of the C matrix ... computing
// a dot product for each element of the product matrix.
const size_t global = N;
const size_t local = ORDER / 16;
err = clEnqueueNDRangeKernel(
commands,
kernel,
1, NULL,
&global, &local,
0, NULL, NULL);
checkError(err, "Enqueueing kernel");
err = clFinish(commands);
checkError(err, "Waiting for kernel to finish");
run_time = wtime() - start_time;
err = clEnqueueReadBuffer(
commands, d_c, CL_TRUE, 0,
sizeof(float) * size, h_C,
0, NULL, NULL);
checkError(err, "Reading back d_c");
results(N, h_C, run_time);
} // end for loop
//--------------------------------------------------------------------------------
// Clean up!
//--------------------------------------------------------------------------------
free(h_A);
free(h_B);
free(h_C);
clReleaseMemObject(d_a);
clReleaseMemObject(d_b);
clReleaseMemObject(d_c);
clReleaseProgram(program);
clReleaseKernel(kernel);
clReleaseCommandQueue(commands);
clReleaseContext(context);
return EXIT_SUCCESS;
}
int main(void)
{
int Mdim, Ndim, Pdim; // A[N][P], B[P][M], C[N][M]
int szA, szB, szC; // Number of elements in each matrix
double start_time; // Starting time
double run_time; // Timing
util::Timer timer; // Timing
Ndim = ORDER;
Pdim = ORDER;
Mdim = ORDER;
szA = Ndim * Pdim;
szB = Pdim * Mdim;
szC = Ndim * Mdim;
std::vector<float> h_A(szA); // Host memory for Matrix A
std::vector<float> h_B(szB); // Host memory for Matrix B
std::vector<float> h_C(szC); // Host memory for Matrix C
cl::Buffer d_a, d_b, d_c; // Matrices in device memory
initmat(Mdim, Ndim, Pdim, h_A, h_B, h_C);
timer.reset();
printf("\n===== Sequential, matrix mult (dot prod), order %d on host CPU ======\n",ORDER);
for(int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0;
seq_mat_mul_sdot(Mdim, Ndim, Pdim, h_A, h_B, h_C);
run_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0 - start_time;
results(Mdim, Ndim, Pdim, h_C, run_time);
}
try
{
//--------------------------------------------------------------------------------
// Create a context and queue for DEVICE
//--------------------------------------------------------------------------------
cl::Context context(DEVICE);
cl::CommandQueue queue(context);
//--------------------------------------------------------------------------------
// Setup the buffers, initialize matrices, and write them into global memory
//--------------------------------------------------------------------------------
// Reset A, B and C matrices (just to play it safe)
initmat(Mdim, Ndim, Pdim, h_A, h_B, h_C);
d_a = cl::Buffer(context, begin(h_A), end(h_A), true);
d_b = cl::Buffer(context, begin(h_B), end(h_B), true);
d_c = cl::Buffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * szC);
//--------------------------------------------------------------------------------
// OpenCL matrix multiplication ... Naive
//--------------------------------------------------------------------------------
// Create the compute program from the source buffer
cl::Program program(context, kernelsource, true);
// Create the compute kernel from the program
auto naive_mmul = cl::make_kernel<int, int, int, cl::Buffer, cl::Buffer, cl::Buffer>(program, "mmul");
printf("\n===== OpenCL, matrix mult, C(i,j) per work item, order %d ======\n",Ndim);
// Do the multiplication COUNT times
for (int i = 0; i < COUNT; i++)
{
zero_mat(Ndim, Mdim, h_C);
start_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0;
// Execute the kernel over the entire range of C matrix elements ... computing
// a dot product for each element of the product matrix. The local work
// group size is set to NULL ... so I'm telling the OpenCL runtime to
// figure out a local work group size for me.
cl::NDRange global(Ndim, Mdim);
naive_mmul(cl::EnqueueArgs(queue, global),
Mdim, Ndim, Pdim, d_a, d_b, d_c);
queue.finish();
run_time = static_cast<double>(timer.getTimeMilliseconds()) / 1000.0 - start_time;
cl::copy(queue, d_c, begin(h_C), end(h_C));
results(Mdim, Ndim, Pdim, h_C, run_time);
} // end for loop
} catch (cl::Error err)
{
std::cout << "Exception\n";
std::cerr << "ERROR: "
<< err.what()
<< "("
<< err_code(err.err())
<< ")"
<< std::endl;
}
return EXIT_SUCCESS;
}
