void Cleanup (int iExitCode)
{
// Cleanup allocated objects
shrLog("Starting Cleanup...\n\n");
if(cPathAndName)free(cPathAndName);
if(cSourceCL)free(cSourceCL);
if(ckKernel)clReleaseKernel(ckKernel);
if(cpProgram)clReleaseProgram(cpProgram);
if(cqCommandQueue)clReleaseCommandQueue(cqCommandQueue);
if(cxGPUContext)clReleaseContext(cxGPUContext);
if(cmDevSrcA)clReleaseMemObject(cmDevSrcA);
if(cmDevSrcB)clReleaseMemObject(cmDevSrcB);
if(cmDevDst)clReleaseMemObject(cmDevDst);
// Free host memory
free(srcA);
free(srcB);
free (dst);
free(Golden);
// finalize logs and leave
if (bNoPrompt)
{
shrLogEx(LOGBOTH | CLOSELOG, 0, "oclVectorAdd.exe Exiting...\n");
}
else
{
shrLogEx(LOGBOTH | CLOSELOG, 0, "oclVectorAdd.exe Exiting...\nPress <Enter> to Quit\n");
getchar();
}
exit (iExitCode);
}
// Helper to clean up
//*****************************************************************************
void Cleanup(int iExitCode)
{
// shrLog("\nStarting Cleanup...\n\n");
// Cleanup allocated objects
if(nbodyGPU)delete nbodyGPU;
if(cqCommandQueue)clReleaseCommandQueue(cqCommandQueue);
if(cxContext)clReleaseContext(cxContext);
if(hPos)delete [] hPos;
if(hVel)delete [] hVel;
if(hColor)delete [] hColor;
if(renderer)delete renderer;
// finalize logs and leave
if (bNoPrompt || bQATest)
{
// shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\n", cExecutablePath);
}
else
{
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\nPress <Enter> to Quit\n", cExecutablePath);
#ifdef WIN32
getchar();
#endif
}
exit (iExitCode);
}
void Cleanup(int iExitCode)
{
// cleanup allocated objects
//shrLog("\nStarting Cleanup...\n\n");
if(cPathAndName)free(cPathAndName);
if(cSourceCL)free(cSourceCL);
if(ScalseKernel)clReleaseKernel(ScalseKernel);
if(TransformKernel)clReleaseKernel(TransformKernel);
if(LongToShortKernel)clReleaseKernel(LongToShortKernel);
if(cpProgram)clReleaseProgram(cpProgram);
if(volumeSamplerLinear)clReleaseSampler(volumeSamplerLinear);
if(volumeSamplerNearest)clReleaseSampler(volumeSamplerNearest);
if(transferFuncSampler)clReleaseSampler(transferFuncSampler);
if(d_volumeArray)clReleaseMemObject(d_volumeArray);
if(d_transferFuncArray)clReleaseMemObject(d_transferFuncArray);
if(pbo_cl)clReleaseMemObject(pbo_cl);
if(d_transferpoint)clReleaseMemObject(d_transferpoint);
if(d_transpoint)clReleaseMemObject(d_transpoint);
if(d_scalepoint)clReleaseMemObject(d_scalepoint);
if(d_invViewMatrix)clReleaseMemObject(d_invViewMatrix);
if(cqCommandQueue)clReleaseCommandQueue(cqCommandQueue);
if(cxGPUContext)clReleaseContext(cxGPUContext);
if(d_boxmax)clReleaseMemObject(d_boxmax);
if (d_boxmin)clReleaseMemObject(d_boxmin);
// finalize logs and leave
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\nPress <Enter> to Quit\n", cExecutableName);
#ifdef WIN32
getchar();
#endif
exit (iExitCode);
}
// Cleanup and exit code
// *********************************************************************
void Cleanup(int iExitCode)
{
// Cleanup allocated objects
shrLog("Starting Cleanup...\n\n");
if(cdDevices)free(cdDevices);
if(cPathAndName)free(cPathAndName);
if(cSourceCL)free(cSourceCL);
if(ceEvent)clReleaseEvent(ceEvent);
if(ckKernel)clReleaseKernel(ckKernel);
if(cpProgram)clReleaseProgram(cpProgram);
if(cqCommandQueue)clReleaseCommandQueue(cqCommandQueue);
if(cxGPUContext)clReleaseContext(cxGPUContext);
if (cmM)clReleaseMemObject(cmM);
if (cmV)clReleaseMemObject(cmV);
if (cmW)clReleaseMemObject(cmW);
// Free host memory
free(M);
free(V);
free(W);
free(Golden);
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\n", cExecutableName);
exit (iExitCode);
}
extern "C" void initScan(cl_context cxGPUContext, cl_command_queue cqParamCommandQue, const char **argv) {
cl_int ciErrNum;
size_t kernelLength;
shrLog(" ...loading Scan.cl\n");
char *cScan = oclLoadProgSource(shrFindFilePath("Scan.cl", argv[0]), "// My comment\n", &kernelLength);
oclCheckError(cScan != NULL, shrTRUE);
shrLog(" ...creating scan program\n");
cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&cScan, &kernelLength, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog(" ...building scan program\n");
ciErrNum = clBuildProgram(cpProgram, 0, NULL, compileOptions, NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclScan.ptx");
oclCheckError(ciErrNum, CL_SUCCESS);
}
shrLog(" ...creating scan kernels\n");
ckScanExclusiveLocal1 = clCreateKernel(cpProgram, "scanExclusiveLocal1", &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
ckScanExclusiveLocal2 = clCreateKernel(cpProgram, "scanExclusiveLocal2", &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
ckUniformUpdate = clCreateKernel(cpProgram, "uniformUpdate", &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog( " ...checking minimum supported workgroup size\n");
//Check for work group size
cl_device_id device;
size_t szScanExclusiveLocal1, szScanExclusiveLocal2, szUniformUpdate;
ciErrNum = clGetCommandQueueInfo(cqParamCommandQue, CL_QUEUE_DEVICE, sizeof(cl_device_id), &device, NULL);
ciErrNum |= clGetKernelWorkGroupInfo(ckScanExclusiveLocal1, device, CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &szScanExclusiveLocal1, NULL);
ciErrNum |= clGetKernelWorkGroupInfo(ckScanExclusiveLocal2, device, CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &szScanExclusiveLocal2, NULL);
ciErrNum |= clGetKernelWorkGroupInfo(ckUniformUpdate, device, CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &szUniformUpdate, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
if( (szScanExclusiveLocal1 < WORKGROUP_SIZE) || (szScanExclusiveLocal2 < WORKGROUP_SIZE) || (szUniformUpdate < WORKGROUP_SIZE) ) {
shrLog("ERROR: Minimum work-group size %u required by this application is not supported on this device.\n", WORKGROUP_SIZE);
exit(0);
}
shrLog(" ...allocating internal buffers\n");
d_Buffer = clCreateBuffer(cxGPUContext, CL_MEM_READ_WRITE, (MAX_BATCH_ELEMENTS / (4 * WORKGROUP_SIZE)) * sizeof(uint), NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
//Discard temp storage
free(cScan);
}
// Function to clean up and exit
//*****************************************************************************
void Cleanup(int iExitCode)
{
shrLog("\nStarting Cleanup...\n\n");
// Delete main particle system instance
if (psystem) delete psystem;
// Cleanup OpenCL
shutdownOpenCL();
// finalize logs and leave
if (bNoPrompt || bQATest)
{
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\n", cExecutableName);
}
else
{
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\nPress <Enter> to Quit\n", cExecutableName);
#ifdef WIN32
getchar();
#endif
}
exit (iExitCode);
}
///////////////////////////////////////////////////////////////////////////
//print results in a database format
///////////////////////////////////////////////////////////////////////////
void printResultsCSV(unsigned int *memSizes, double* bandwidths, unsigned int count, memcpyKind kind, accessMode accMode, memoryMode memMode, int iNumDevs)
{
unsigned int i;
double dSeconds = 0.0;
std::string sConfig;
// log config information
if (kind == DEVICE_TO_DEVICE)
{
sConfig += "D2D";
}
else
{
if (kind == DEVICE_TO_HOST)
{
sConfig += "D2H";
}
else if (kind == HOST_TO_DEVICE)
{
sConfig += "H2D";
}
if(memMode == PAGEABLE)
{
sConfig += "-Paged";
}
else if (memMode == PINNED)
{
sConfig += "-Pinned";
}
if(accMode == DIRECT)
{
sConfig += "-Direct";
}
else if (accMode == MAPPED)
{
sConfig += "-Mapped";
}
}
for(i = 0; i < count; i++)
{
dSeconds = (double)memSizes[i] / (bandwidths[i] * (double)(1<<20));
shrLogEx(LOGBOTH | MASTER, 0, "oclBandwidthTest-%s, Bandwidth = %.1f MB/s, Time = %.5f s, Size = %u Bytes, NumDevsUsed = %i\n", sConfig.c_str(), bandwidths[i], dSeconds, memSizes[i], iNumDevs);
}
}
// Kernel function
//*****************************************************************************
int executeKernel(cl_int radius)
{
// set global and local work item dimensions
szLocalWorkSize[0] = 16;
szLocalWorkSize[1] = 16;
szGlobalWorkSize[0] = shrRoundUp((int)szLocalWorkSize[0], image_width);
szGlobalWorkSize[1] = shrRoundUp((int)szLocalWorkSize[1], image_height);
// set the args values
cl_int tilew = (cl_int)szLocalWorkSize[0]+(2*radius);
ciErrNum = clSetKernelArg(ckKernel, 4, sizeof(tilew), &tilew);
ciErrNum |= clSetKernelArg(ckKernel, 5, sizeof(radius), &radius);
cl_float threshold = 0.8f;
ciErrNum |= clSetKernelArg(ckKernel, 6, sizeof(threshold), &threshold);
cl_float highlight = 4.0f;
ciErrNum |= clSetKernelArg(ckKernel, 7, sizeof(highlight), &highlight);
// Local memory
ciErrNum |= clSetKernelArg(ckKernel, 8, (szLocalWorkSize[0]+(2*16))*(szLocalWorkSize[1]+(2*16))*sizeof(int), NULL);
// launch computation kernel
#ifdef GPU_PROFILING
int nIter = 30;
for( int i=-1; i< nIter; ++i) {
if( i ==0 )
shrDeltaT(0);
#endif
ciErrNum |= clEnqueueNDRangeKernel(cqCommandQueue, ckKernel, 2, NULL,
szGlobalWorkSize, szLocalWorkSize,
0, NULL, NULL);
#ifdef GPU_PROFILING
}
clFinish(cqCommandQueue);
double dSeconds = shrDeltaT(0)/(double)nIter;
double dNumTexels = (double)image_width * (double)image_height;
double mtexps = 1.0e-6 * dNumTexels/dSeconds;
shrLogEx(LOGBOTH | MASTER, 0, "oclPostprocessGL, Throughput = %.4f MTexels/s, Time = %.5f s, Size = %.0f Texels, NumDevsUsed = %u, Workgroup = %u\n",
mtexps, dSeconds, dNumTexels, uiNumDevsUsed, szLocalWorkSize[0] * szLocalWorkSize[1]);
#endif
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
return 0;
}
// Function to clean up and exit
//*****************************************************************************
void Cleanup(int iExitCode)
{
// Cleanup allocated objects
shrLog("\nStarting Cleanup...\n\n");
// Release all the OpenCL Objects
if(cpProgram)clReleaseProgram(cpProgram);
for (cl_uint i = 0; i < GpuDevMngr->uiUsefulDevCt; i++)
{
if(ckSobel[i])clReleaseKernel(ckSobel[i]);
if(cmDevBufIn[i])clReleaseMemObject(cmDevBufIn[i]);
if(cmDevBufOut[i])clReleaseMemObject(cmDevBufOut[i]);
}
if(uiInput)clEnqueueUnmapMemObject(cqCommandQueue[0], cmPinnedBufIn, (void*)uiInput, 0, NULL, NULL);
if(uiOutput)clEnqueueUnmapMemObject(cqCommandQueue[0], cmPinnedBufOut, (void*)uiOutput, 0, NULL, NULL);
if(cmPinnedBufIn)clReleaseMemObject(cmPinnedBufIn);
if(cmPinnedBufOut)clReleaseMemObject(cmPinnedBufOut);
for (cl_uint i = 0; i < GpuDevMngr->uiUsefulDevCt; i++)
{
if(cqCommandQueue[i])clReleaseCommandQueue(cqCommandQueue[i]);
}
if(cxGPUContext)clReleaseContext(cxGPUContext);
// free the host allocs
if(cSourceCL)free(cSourceCL);
if(cPathAndName)free(cPathAndName);
if(cmDevBufIn) delete [] cmDevBufIn;
if(cmDevBufOut) delete [] cmDevBufOut;
if(szAllocDevBytes) delete [] szAllocDevBytes;
if(uiInHostPixOffsets) delete [] uiInHostPixOffsets;
if(uiOutHostPixOffsets) delete [] uiOutHostPixOffsets;
if(uiDevImageHeight) delete [] uiDevImageHeight;
if(GpuDevMngr) delete GpuDevMngr;
if(cqCommandQueue) delete [] cqCommandQueue;
// Cleanup GL objects if used
if (!bQATest)
{
DeInitGL();
}
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\n", cExecutableName);
shrQAFinishExit2(bQATest, *pArgc, (const char **)pArgv, ( iExitCode == EXIT_SUCCESS ) ? QA_PASSED : QA_FAILED);
}
////////////////////////////////////////////////////////////////////////////////
//! Run a simple benchmark test for CUDA
////////////////////////////////////////////////////////////////////////////////
void
runBenchmark( int argc, char **argv )
{
int devID = 0;
shrLog("[runBenchmark]: [%s]\n", sSDKsample);
devID = cutilChooseCudaDevice(argc, argv);
loadImageData(argc, argv);
initCuda();
g_CheckRender = new CheckBackBuffer(width, height, 4, false);
g_CheckRender->setExecPath(argv[0]);
unsigned int *d_result;
cutilSafeCall( cudaMalloc( (void **)&d_result, width*height*sizeof(unsigned int)) );
// warm-up
boxFilterRGBA(d_img, d_temp, d_temp, width, height, filter_radius, iterations, nthreads);
cutilSafeCall( cutilDeviceSynchronize() );
// Start round-trip timer and process iCycles loops on the GPU
iterations = 1; // standard 1-pass filtering
const int iCycles = 150;
double dProcessingTime = 0.0;
shrLog("\nRunning BoxFilterGPU for %d cycles...\n\n", iCycles);
shrDeltaT(2);
for (int i = 0; i < iCycles; i++)
{
dProcessingTime += boxFilterRGBA(d_img, d_temp, d_img, width, height, filter_radius, iterations, nthreads);
}
// check if kernel execution generated an error and sync host
cutilCheckMsg("Error: boxFilterRGBA Kernel execution FAILED");
cutilSafeCall(cutilDeviceSynchronize());
// Get average computation time
dProcessingTime /= (double)iCycles;
// log testname, throughput, timing and config info to sample and master logs
shrLogEx(LOGBOTH | MASTER, 0, "boxFilter-texture, Throughput = %.4f M RGBA Pixels/s, Time = %.5f s, Size = %u RGBA Pixels, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * width * height)/dProcessingTime, dProcessingTime,
(width * height), 1, nthreads);
shrLog("\n");
}
//-----------------------------------------------------------------------------
// Name: CreateKernelProgram()
// Desc: Creates OpenCL program and kernel instances
//-----------------------------------------------------------------------------
HRESULT CreateKernelProgram(
const char *exepath, const char *clName, const char *clPtx, const char *kernelEntryPoint,
cl_program &cpProgram,
cl_kernel &ckKernel )
{
// Program Setup
size_t program_length;
const char* source_path = shrFindFilePath(clName, exepath);
char *source = oclLoadProgSource(source_path, "", &program_length);
oclCheckErrorEX(source != NULL, shrTRUE, pCleanup);
// create the program
cpProgram = clCreateProgramWithSource(cxGPUContext, 1,(const char **) &source, &program_length, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
free(source);
// build the program
#ifdef USE_STAGING_BUFFER
static char *opts = "-cl-fast-relaxed-math -DUSE_STAGING_BUFFER";
#else
static char *opts = "-cl-fast-relaxed-math";
#endif
ciErrNum = clBuildProgram(cpProgram, 0, NULL, opts, NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), clPtx);
Cleanup(EXIT_FAILURE);
}
// create the kernel
ckKernel = clCreateKernel(cpProgram, kernelEntryPoint, &ciErrNum);
if (!ckKernel)
{
Cleanup(EXIT_FAILURE);
}
// set the args values
return ciErrNum ? E_FAIL : S_OK;
}
// Function to clean up and exit
//*****************************************************************************
void Cleanup(int iExitCode)
{
// Cleanup allocated objects
shrLog("\nStarting Cleanup...\n\n");
if(pbo_source)deletePBO(&pbo_source);
if(pbo_dest)deletePBO(&pbo_dest);
if(tex_screen)deleteTexture(&tex_screen);
if(ckKernel)clReleaseKernel(ckKernel);
if(cpProgram)clReleaseProgram(cpProgram);
if(cl_pbos[0])clReleaseMemObject(cl_pbos[0]);
if(cl_pbos[1])clReleaseMemObject(cl_pbos[1]);
if(cqCommandQueue)clReleaseCommandQueue(cqCommandQueue);
if(cxGPUContext)clReleaseContext(cxGPUContext);
shrLogEx(LOGBOTH | CLOSELOG, 0, "%s Exiting...\n", cExecutableName);
// finalize logs and leave
shrQAFinish2(bQATest, *pArgc, (const char **)pArgv, (iExitCode == 0) ? QA_PASSED : QA_FAILED);
exit (iExitCode);
}
// QATest sequence without any GL calls
//*****************************************************************************
void TestNoGL()
{
// Warmup call to assure OpenCL driver is awake
psystem->update(timestep);
// Start timer 0 and process n loops on the GPU
const int iCycles = 20;
shrDeltaT(0);
for (int i = 0; i < iCycles; i++)
{
psystem->update(timestep);
}
// Get elapsed time and throughput, then log to sample and master logs
double dAvgTime = shrDeltaT(0)/(double)iCycles;
shrLogEx(LOGBOTH | MASTER, 0, "oclParticles, Throughput = %.4f KParticles/s, Time = %.5f s, Size = %u particles, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-3 * numParticles)/dAvgTime, dAvgTime, numParticles, 1, 0);
// Cleanup and exit
shrQAFinish2(true, *pArgc, (const char **)pArgv, QA_PASSED);
Cleanup (EXIT_SUCCESS);
}
void RunProfiling(int iterations, unsigned int uiWorkgroup)
{
// once without timing to prime the GPU
nbody->update(activeParams.m_timestep);
nbody->synchronizeThreads();
// Start timer 0 and process n loops on the GPU
shrDeltaT(FUNCTIME);
for (int i = 0; i < iterations; ++i)
{
nbody->update(activeParams.m_timestep);
}
nbody->synchronizeThreads();
// Get elapsed time and throughput, then log to sample and master logs
double dSeconds = shrDeltaT(FUNCTIME);
double dGigaInteractionsPerSecond = 0.0;
double dGigaFlops = 0.0;
ComputePerfStats(dGigaInteractionsPerSecond, dGigaFlops, dSeconds, iterations);
shrLogEx(LOGBOTH | MASTER, 0, "oclNBody-%s, Throughput = %.4f GFLOP/s, Time = %.5f s, Size = %u bodies, NumDevsUsed = %u, Workgroup = %u\n",
(bDouble ? "DP" : "SP"), dGigaFlops, dSeconds/(double)iterations, numBodies, uiNumDevsUsed, uiWorkgroup);
}
// Run a test sequence without any GL
//*****************************************************************************
void TestNoGL()
{
// Warmup call to assure OpenCL driver is awake
// note this function has a finish for all queues at its end, so no further host sync is needed
SobelFilterGPU (uiInput, uiOutput);
// Start timer 0 and process n loops on the GPU
const int iCycles = 150;
dProcessingTime = 0.0;
shrLog("\nRunning SobelFilterGPU for %d cycles...\n\n", iCycles);
shrDeltaT(2);
for (int i = 0; i < iCycles; i++)
{
// note this function has a finish for all queues at its end, so no further host sync is needed
dProcessingTime += SobelFilterGPU (uiInput, uiOutput);
}
// Get round-trip and average computation time
double dRoundtripTime = shrDeltaT(2)/(double)iCycles;
dProcessingTime /= (double)iCycles;
// log throughput, timing and config info to sample and master logs
shrLogEx(LOGBOTH | MASTER, 0, "oclSobelFilter, Throughput = %.4f M RGB Pixels/s, Time = %.5f s, Size = %u RGB Pixels, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * uiImageWidth * uiImageHeight)/dProcessingTime, dProcessingTime, (uiImageWidth * uiImageHeight), GpuDevMngr->uiUsefulDevCt, szLocalWorkSize[0] * szLocalWorkSize[1]);
shrLog("\nRoundTrip Time = %.5f s, Equivalent FPS = %.1f\n\n", dRoundtripTime, 1.0/dRoundtripTime);
// Compute on host
cl_uint* uiGolden = (cl_uint*)malloc(szBuffBytes);
SobelFilterHost(uiInput, uiGolden, uiImageWidth, uiImageHeight, fThresh);
// Compare GPU and Host results: Allow variance of 1 GV in up to 0.01% of pixels
shrLog("Comparing GPU Result to CPU Result...\n");
shrBOOL bMatch = shrCompareuit(uiGolden, uiOutput, (uiImageWidth * uiImageHeight), 1.0f, 0.0001f);
shrLog("\nGPU Result %s CPU Result within tolerance...\n", (bMatch == shrTRUE) ? "matches" : "DOESN'T match");
// Cleanup and exit
free(uiGolden);
Cleanup((bMatch == shrTRUE) ? EXIT_SUCCESS : EXIT_FAILURE);
}
// Main function
// *********************************************************************
int main(int argc, char **argv)
{
gp_argc = &argc;
gp_argv = &argv;
shrQAStart(argc, argv);
// Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, NULL);
shrLog("clGetPlatformID...\n");
// Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, NULL);
shrLog("clGetPlatformID...\n");
//Get all the devices
cl_uint uiNumDevices = 0; // Number of devices available
cl_uint uiTargetDevice = 0; // Default Device to compute on
cl_uint uiNumComputeUnits; // Number of compute units (SM's on NV GPU)
shrLog("Get the Device info and select Device...\n");
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 0, NULL, &uiNumDevices);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, NULL);
cdDevices = (cl_device_id *)malloc(uiNumDevices * sizeof(cl_device_id) );
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, uiNumDevices, cdDevices, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, NULL);
// Get command line device options and config accordingly
shrLog(" # of Devices Available = %u\n", uiNumDevices);
if(shrGetCmdLineArgumentu(argc, (const char**)argv, "device", &uiTargetDevice)== shrTRUE)
{
uiTargetDevice = CLAMP(uiTargetDevice, 0, (uiNumDevices - 1));
}
shrLog(" Using Device %u: ", uiTargetDevice);
oclPrintDevName(LOGBOTH, cdDevices[uiTargetDevice]);
ciErrNum = clGetDeviceInfo(cdDevices[uiTargetDevice], CL_DEVICE_MAX_COMPUTE_UNITS, sizeof(uiNumComputeUnits), &uiNumComputeUnits, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, NULL);
shrLog("\n # of Compute Units = %u\n", uiNumComputeUnits);
// get command line arg for quick test, if provided
bNoPrompt = shrCheckCmdLineFlag(argc, (const char**)argv, "noprompt");
// start logs
cExecutableName = argv[0];
shrSetLogFileName ("oclDotProduct.txt");
shrLog("%s Starting...\n\n# of float elements per Array \t= %u\n", argv[0], iNumElements);
// set and log Global and Local work size dimensions
szLocalWorkSize = 256;
szGlobalWorkSize = shrRoundUp((int)szLocalWorkSize, iNumElements); // rounded up to the nearest multiple of the LocalWorkSize
shrLog("Global Work Size \t\t= %u\nLocal Work Size \t\t= %u\n# of Work Groups \t\t= %u\n\n",
szGlobalWorkSize, szLocalWorkSize, (szGlobalWorkSize % szLocalWorkSize + szGlobalWorkSize/szLocalWorkSize));
// Allocate and initialize host arrays
shrLog( "Allocate and Init Host Mem...\n");
srcA = (void *)malloc(sizeof(cl_float4) * szGlobalWorkSize);
srcB = (void *)malloc(sizeof(cl_float4) * szGlobalWorkSize);
dst = (void *)malloc(sizeof(cl_float) * szGlobalWorkSize);
Golden = (void *)malloc(sizeof(cl_float) * iNumElements);
shrFillArray((float*)srcA, 4 * iNumElements);
shrFillArray((float*)srcB, 4 * iNumElements);
// Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Get a GPU device
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 1, &cdDevices[uiTargetDevice], NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Create the context
cxGPUContext = clCreateContext(0, 1, &cdDevices[uiTargetDevice], NULL, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Create a command-queue
shrLog("clCreateCommandQueue...\n");
cqCommandQueue = clCreateCommandQueue(cxGPUContext, cdDevices[uiTargetDevice], 0, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Allocate the OpenCL buffer memory objects for source and result on the device GMEM
shrLog("clCreateBuffer (SrcA, SrcB and Dst in Device GMEM)...\n");
cmDevSrcA = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, sizeof(cl_float) * szGlobalWorkSize * 4, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cmDevSrcB = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, sizeof(cl_float) * szGlobalWorkSize * 4, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cmDevDst = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, sizeof(cl_float) * szGlobalWorkSize, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Read the OpenCL kernel in from source file
shrLog("oclLoadProgSource (%s)...\n", cSourceFile);
cPathAndName = shrFindFilePath(cSourceFile, argv[0]);
oclCheckErrorEX(cPathAndName != NULL, shrTRUE, pCleanup);
cSourceCL = oclLoadProgSource(cPathAndName, "", &szKernelLength);
oclCheckErrorEX(cSourceCL != NULL, shrTRUE, pCleanup);
// Create the program
shrLog("clCreateProgramWithSource...\n");
cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&cSourceCL, &szKernelLength, &ciErrNum);
// Build the program with 'mad' Optimization option
#ifdef MAC
char* flags = "-cl-fast-relaxed-math -DMAC";
#else
char* flags = "-cl-fast-relaxed-math";
#endif
shrLog("clBuildProgram...\n");
ciErrNum = clBuildProgram(cpProgram, 0, NULL, NULL, NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclDotProduct.ptx");
Cleanup(EXIT_FAILURE);
}
// Create the kernel
shrLog("clCreateKernel (DotProduct)...\n");
ckKernel = clCreateKernel(cpProgram, "DotProduct", &ciErrNum);
// Set the Argument values
shrLog("clSetKernelArg 0 - 3...\n\n");
ciErrNum = clSetKernelArg(ckKernel, 0, sizeof(cl_mem), (void*)&cmDevSrcA);
ciErrNum |= clSetKernelArg(ckKernel, 1, sizeof(cl_mem), (void*)&cmDevSrcB);
ciErrNum |= clSetKernelArg(ckKernel, 2, sizeof(cl_mem), (void*)&cmDevDst);
ciErrNum |= clSetKernelArg(ckKernel, 3, sizeof(cl_int), (void*)&iNumElements);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// --------------------------------------------------------
// Core sequence... copy input data to GPU, compute, copy results back
// Asynchronous write of data to GPU device
shrLog("clEnqueueWriteBuffer (SrcA and SrcB)...\n");
ciErrNum = clEnqueueWriteBuffer(cqCommandQueue, cmDevSrcA, CL_FALSE, 0, sizeof(cl_float) * szGlobalWorkSize * 4, srcA, 0, NULL, NULL);
ciErrNum |= clEnqueueWriteBuffer(cqCommandQueue, cmDevSrcB, CL_FALSE, 0, sizeof(cl_float) * szGlobalWorkSize * 4, srcB, 0, NULL, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Launch kernel
shrLog("clEnqueueNDRangeKernel (DotProduct)...\n");
ciErrNum = clEnqueueNDRangeKernel(cqCommandQueue, ckKernel, 1, NULL, &szGlobalWorkSize, &szLocalWorkSize, 0, NULL, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Read back results and check accumulated errors
shrLog("clEnqueueReadBuffer (Dst)...\n\n");
ciErrNum = clEnqueueReadBuffer(cqCommandQueue, cmDevDst, CL_TRUE, 0, sizeof(cl_float) * szGlobalWorkSize, dst, 0, NULL, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Compute and compare results for golden-host and report errors and pass/fail
shrLog("Comparing against Host/C++ computation...\n\n");
DotProductHost ((const float*)srcA, (const float*)srcB, (float*)Golden, iNumElements);
shrBOOL bMatch = shrComparefet((const float*)Golden, (const float*)dst, (unsigned int)iNumElements, 0.0f, 0);
// Cleanup and leave
Cleanup (EXIT_SUCCESS);
}
////////////////////////////////////////////////////////////////////////////////
// Test driver
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv)
{
cl_platform_id cpPlatform;
cl_device_id cdDevice;
cl_context cxGPUContext; //OpenCL context
cl_command_queue cqCommandQueue; //OpenCL command queue
cl_mem c_Kernel, d_Input, d_Buffer, d_Output; //OpenCL memory buffer objects
cl_float *h_Kernel, *h_Input, *h_Buffer, *h_OutputCPU, *h_OutputGPU;
cl_int ciErrNum;
const unsigned int imageW = 3072;
const unsigned int imageH = 3072;
shrQAStart(argc, argv);
// set logfile name and start logs
shrSetLogFileName ("oclConvolutionSeparable.txt");
shrLog("%s Starting...\n\n", argv[0]);
shrLog("Allocating and initializing host memory...\n");
h_Kernel = (cl_float *)malloc(KERNEL_LENGTH * sizeof(cl_float));
h_Input = (cl_float *)malloc(imageW * imageH * sizeof(cl_float));
h_Buffer = (cl_float *)malloc(imageW * imageH * sizeof(cl_float));
h_OutputCPU = (cl_float *)malloc(imageW * imageH * sizeof(cl_float));
h_OutputGPU = (cl_float *)malloc(imageW * imageH * sizeof(cl_float));
srand(2009);
for(unsigned int i = 0; i < KERNEL_LENGTH; i++)
h_Kernel[i] = (cl_float)(rand() % 16);
for(unsigned int i = 0; i < imageW * imageH; i++)
h_Input[i] = (cl_float)(rand() % 16);
shrLog("Initializing OpenCL...\n");
//Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckError(ciErrNum, CL_SUCCESS);
//Get the devices
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 1, &cdDevice, NULL);
//Create the context
cxGPUContext = clCreateContext(0, 1, &cdDevice, NULL, NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
//Create a command-queue
cqCommandQueue = clCreateCommandQueue(cxGPUContext, cdDevice, CL_QUEUE_PROFILING_ENABLE, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("Initializing OpenCL separable convolution...\n");
initConvolutionSeparable(cxGPUContext, cqCommandQueue, (const char **)argv);
shrLog("Creating OpenCL memory objects...\n");
c_Kernel = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, KERNEL_LENGTH * sizeof(cl_float), h_Kernel, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
d_Input = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, imageW * imageH * sizeof(cl_float), h_Input, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
d_Buffer = clCreateBuffer(cxGPUContext, CL_MEM_READ_WRITE, imageW * imageH * sizeof(cl_float), NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
d_Output = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, imageW * imageH * sizeof(cl_float), NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("Applying separable convolution to %u x %u image...\n\n", imageW, imageH);
//Just a single run or a warmup iteration
convolutionRows(
NULL,
d_Buffer,
d_Input,
c_Kernel,
imageW,
imageH
);
convolutionColumns(
NULL,
d_Output,
d_Buffer,
c_Kernel,
imageW,
imageH
);
#ifdef GPU_PROFILING
const int numIterations = 16;
cl_event startMark, endMark;
ciErrNum = clEnqueueMarker(cqCommandQueue, &startMark);
ciErrNum |= clFinish(cqCommandQueue);
shrCheckError(ciErrNum, CL_SUCCESS);
shrDeltaT(0);
for(int iter = 0; iter < numIterations; iter++){
convolutionRows(
cqCommandQueue,
d_Buffer,
d_Input,
c_Kernel,
imageW,
imageH
);
convolutionColumns(
cqCommandQueue,
d_Output,
d_Buffer,
c_Kernel,
imageW,
imageH
);
}
ciErrNum = clEnqueueMarker(cqCommandQueue, &endMark);
ciErrNum |= clFinish(cqCommandQueue);
shrCheckError(ciErrNum, CL_SUCCESS);
//Calculate performance metrics by wallclock time
double gpuTime = shrDeltaT(0) / (double)numIterations;
shrLogEx(LOGBOTH | MASTER, 0, "oclConvolutionSeparable, Throughput = %.4f MPixels/s, Time = %.5f s, Size = %u Pixels, NumDevsUsed = %i, Workgroup = %u\n",
(1.0e-6 * (double)(imageW * imageH)/ gpuTime), gpuTime, (imageW * imageH), 1, 0);
//Get OpenCL profiler info
cl_ulong startTime = 0, endTime = 0;
ciErrNum = clGetEventProfilingInfo(startMark, CL_PROFILING_COMMAND_END, sizeof(cl_ulong), &startTime, NULL);
ciErrNum |= clGetEventProfilingInfo(endMark, CL_PROFILING_COMMAND_END, sizeof(cl_ulong), &endTime, NULL);
shrCheckError(ciErrNum, CL_SUCCESS);
shrLog("\nOpenCL time: %.5f s\n\n", 1.0e-9 * ((double)endTime - (double)startTime)/ (double)numIterations);
#endif
shrLog("Reading back OpenCL results...\n\n");
ciErrNum = clEnqueueReadBuffer(cqCommandQueue, d_Output, CL_TRUE, 0, imageW * imageH * sizeof(cl_float), h_OutputGPU, 0, NULL, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("Comparing against Host/C++ computation...\n");
convolutionRowHost(h_Buffer, h_Input, h_Kernel, imageW, imageH, KERNEL_RADIUS);
convolutionColumnHost(h_OutputCPU, h_Buffer, h_Kernel, imageW, imageH, KERNEL_RADIUS);
double sum = 0, delta = 0;
double L2norm;
for(unsigned int i = 0; i < imageW * imageH; i++){
delta += (h_OutputCPU[i] - h_OutputGPU[i]) * (h_OutputCPU[i] - h_OutputGPU[i]);
sum += h_OutputCPU[i] * h_OutputCPU[i];
}
L2norm = sqrt(delta / sum);
shrLog("Relative L2 norm: %.3e\n\n", L2norm);
// cleanup
closeConvolutionSeparable();
ciErrNum = clReleaseMemObject(d_Output);
ciErrNum |= clReleaseMemObject(d_Buffer);
ciErrNum |= clReleaseMemObject(d_Input);
ciErrNum |= clReleaseMemObject(c_Kernel);
ciErrNum |= clReleaseCommandQueue(cqCommandQueue);
ciErrNum |= clReleaseContext(cxGPUContext);
oclCheckError(ciErrNum, CL_SUCCESS);
free(h_OutputGPU);
free(h_OutputCPU);
free(h_Buffer);
free(h_Input);
free(h_Kernel);
// finish
shrQAFinishExit(argc, (const char **)argv, (L2norm < 1e-6) ? QA_PASSED : QA_FAILED);
}
bool getTargetDeviceGlobalMemSize(memsize_t *result, const int argc, const char **argv)
{
bool ok = true;
cl_platform_id platform = 0;
cl_context context = 0;
cl_device_id *devices = 0;
cl_uint deviceCount = 0;
cl_uint targetDevice = 0;
cl_ulong memsize = 0;
cl_int errnum = 0;
// Get the NVIDIA platform
if (ok)
{
shrLog(" oclGetPlatformID\n");
errnum = oclGetPlatformID(&platform);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("oclGetPlatformID (no platforms found).\n");
ok = false;
}
}
// Get the list of GPU devices associated with the platform
if (ok)
{
shrLog(" clGetDeviceIDs\n");
errnum = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 0, NULL, &deviceCount);
devices = (cl_device_id *)malloc(deviceCount * sizeof(cl_device_id) );
errnum = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, deviceCount, devices, NULL);
if ((deviceCount == 0) || (errnum != CL_SUCCESS))
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clGetDeviceIDs (returned error or no devices found).\n");
ok = false;
}
}
// Create the OpenCL context
if (ok)
{
shrLog(" clCreateContext\n");
context = clCreateContext(0, deviceCount, devices, NULL, NULL, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateContext (returned %d).\n", errnum);
ok = false;
}
}
// Select target device (device 0 by default)
if (ok)
{
char *device = 0;
if (shrGetCmdLineArgumentstr(argc, argv, "device", &device))
{
targetDevice = (cl_uint)atoi(device);
if (targetDevice >= deviceCount)
{
shrLogEx(LOGBOTH | ERRORMSG, -2000, STDERROR);
shrLog("invalid target device specified on command line (device %d does not exist).\n", targetDevice);
ok = false;
}
}
else
{
targetDevice = 0;
}
if (device)
{
free(device);
}
}
// Query target device for maximum memory allocation
if (ok)
{
shrLog(" clGetDeviceInfo\n");
errnum = clGetDeviceInfo(devices[targetDevice], CL_DEVICE_GLOBAL_MEM_SIZE, sizeof(cl_ulong), &memsize, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clGetDeviceInfo (returned %d).\n", errnum);
ok = false;
}
}
// Save the result
if (ok)
{
*result = (memsize_t)memsize;
}
// Cleanup
if (devices)
free(devices);
if (context)
clReleaseContext(context);
return ok;
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv)
{
shrQAStart(argc, argv);
// start logs
shrSetLogFileName ("oclSimpleMultiGPU.txt");
shrLog("%s Starting, Array = %u float values...\n\n", argv[0], DATA_N);
// OpenCL
cl_platform_id cpPlatform;
cl_uint ciDeviceCount;
cl_device_id* cdDevices;
cl_context cxGPUContext;
cl_device_id cdDevice; // GPU device
int deviceNr[MAX_GPU_COUNT];
cl_command_queue commandQueue[MAX_GPU_COUNT];
cl_mem d_Data[MAX_GPU_COUNT];
cl_mem d_Result[MAX_GPU_COUNT];
cl_program cpProgram;
cl_kernel reduceKernel[MAX_GPU_COUNT];
cl_event GPUDone[MAX_GPU_COUNT];
cl_event GPUExecution[MAX_GPU_COUNT];
size_t programLength;
cl_int ciErrNum;
char cDeviceName [256];
cl_mem h_DataBuffer;
// Vars for reduction results
float h_SumGPU[MAX_GPU_COUNT * ACCUM_N];
float *h_Data;
double sumGPU;
double sumCPU, dRelError;
// allocate and init host buffer with with some random generated input data
h_Data = (float *)malloc(DATA_N * sizeof(float));
shrFillArray(h_Data, DATA_N);
// start timer & logs
shrLog("Setting up OpenCL on the Host...\n\n");
shrDeltaT(1);
// Annotate profiling state
#ifdef GPU_PROFILING
shrLog("OpenCL Profiling is enabled...\n\n");
#endif
//Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clGetPlatformID...\n");
//Get the devices
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 0, NULL, &ciDeviceCount);
oclCheckError(ciErrNum, CL_SUCCESS);
cdDevices = (cl_device_id *)malloc(ciDeviceCount * sizeof(cl_device_id) );
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, ciDeviceCount, cdDevices, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clGetDeviceIDs...\n");
//Create the context
cxGPUContext = clCreateContext(0, ciDeviceCount, cdDevices, NULL, NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateContext...\n");
// Set up command queue(s) for GPU's specified on the command line or all GPU's
if(shrCheckCmdLineFlag(argc, (const char **)argv, "device"))
{
// User specified GPUs
int ciMaxDeviceID = ciDeviceCount-1;
ciDeviceCount = 0;
char* deviceList;
char* deviceStr;
char* next_token;
shrGetCmdLineArgumentstr(argc, (const char **)argv, "device", &deviceList);
#ifdef WIN32
deviceStr = strtok_s (deviceList," ,.-", &next_token);
#else
deviceStr = strtok (deviceList," ,.-");
#endif
// Create command queues for all Requested GPU's
while(deviceStr != NULL)
{
// get & log device index # and name
deviceNr[ciDeviceCount] = atoi(deviceStr);
if( deviceNr[ciDeviceCount] > ciMaxDeviceID ) {
shrLog(" Invalid user specified device ID: %d\n", deviceNr[ciDeviceCount]);
return 1;
}
cdDevice = oclGetDev(cxGPUContext, deviceNr[ciDeviceCount]);
ciErrNum = clGetDeviceInfo(cdDevice, CL_DEVICE_NAME, sizeof(cDeviceName), cDeviceName, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog(" Device %i: %s\n\n", deviceNr[ciDeviceCount], cDeviceName);
// create a command que
commandQueue[ciDeviceCount] = clCreateCommandQueue(cxGPUContext, cdDevice, CL_QUEUE_PROFILING_ENABLE, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateCommandQueue\n");
++ciDeviceCount;
#ifdef WIN32
deviceStr = strtok_s (NULL," ,.-", &next_token);
#else
deviceStr = strtok (NULL," ,.-");
#endif
}
free(deviceList);
}
else
{
// Find out how many GPU's to compute on all available GPUs
size_t nDeviceBytes;
ciErrNum = clGetContextInfo(cxGPUContext, CL_CONTEXT_DEVICES, 0, NULL, &nDeviceBytes);
oclCheckError(ciErrNum, CL_SUCCESS);
ciDeviceCount = (cl_uint)nDeviceBytes/sizeof(cl_device_id);
for(unsigned int i = 0; i < ciDeviceCount; ++i )
{
// get & log device index # and name
deviceNr[i] = i;
cdDevice = oclGetDev(cxGPUContext, i);
ciErrNum = clGetDeviceInfo(cdDevice, CL_DEVICE_NAME, sizeof(cDeviceName), cDeviceName, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog(" Device %i: %s\n", i, cDeviceName);
// create a command que
commandQueue[i] = clCreateCommandQueue(cxGPUContext, cdDevice, CL_QUEUE_PROFILING_ENABLE, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateCommandQueue\n\n");
}
}
// Load the OpenCL source code from the .cl file
const char* source_path = shrFindFilePath("simpleMultiGPU.cl", argv[0]);
char *source = oclLoadProgSource(source_path, "", &programLength);
oclCheckError(source != NULL, shrTRUE);
shrLog("oclLoadProgSource\n");
// Create the program for all GPUs in the context
cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&source, &programLength, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateProgramWithSource\n");
// build the program
ciErrNum = clBuildProgram(cpProgram, 0, NULL, "-cl-fast-relaxed-math", NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclSimpleMultiGPU.ptx");
oclCheckError(ciErrNum, CL_SUCCESS);
}
shrLog("clBuildProgram\n");
// Create host buffer with page-locked memory
h_DataBuffer = clCreateBuffer(cxGPUContext, CL_MEM_COPY_HOST_PTR | CL_MEM_ALLOC_HOST_PTR,
DATA_N * sizeof(float), h_Data, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateBuffer (Page-locked Host)\n\n");
// Create buffers for each GPU, with data divided evenly among GPU's
int sizePerGPU = DATA_N / ciDeviceCount;
int workOffset[MAX_GPU_COUNT];
int workSize[MAX_GPU_COUNT];
workOffset[0] = 0;
for(unsigned int i = 0; i < ciDeviceCount; ++i )
{
workSize[i] = (i != (ciDeviceCount - 1)) ? sizePerGPU : (DATA_N - workOffset[i]);
// Input buffer
d_Data[i] = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, workSize[i] * sizeof(float), NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateBuffer (Input)\t\tDev %i\n", i);
// Copy data from host to device
ciErrNum = clEnqueueCopyBuffer(commandQueue[i], h_DataBuffer, d_Data[i], workOffset[i] * sizeof(float),
0, workSize[i] * sizeof(float), 0, NULL, NULL);
shrLog("clEnqueueCopyBuffer (Input)\tDev %i\n", i);
// Output buffer
d_Result[i] = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, ACCUM_N * sizeof(float), NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateBuffer (Output)\t\tDev %i\n", i);
// Create kernel
reduceKernel[i] = clCreateKernel(cpProgram, "reduce", &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateKernel\t\t\tDev %i\n", i);
// Set the args values and check for errors
ciErrNum |= clSetKernelArg(reduceKernel[i], 0, sizeof(cl_mem), &d_Result[i]);
ciErrNum |= clSetKernelArg(reduceKernel[i], 1, sizeof(cl_mem), &d_Data[i]);
ciErrNum |= clSetKernelArg(reduceKernel[i], 2, sizeof(int), &workSize[i]);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clSetKernelArg\t\t\tDev %i\n\n", i);
workOffset[i + 1] = workOffset[i] + workSize[i];
}
// Set # of work items in work group and total in 1 dimensional range
size_t localWorkSize[] = {THREAD_N};
size_t globalWorkSize[] = {ACCUM_N};
// Start timer and launch reduction kernel on each GPU, with data split between them
shrLog("Launching Kernels on GPU(s)...\n\n");
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
ciErrNum = clEnqueueNDRangeKernel(commandQueue[i], reduceKernel[i], 1, 0, globalWorkSize, localWorkSize,
0, NULL, &GPUExecution[i]);
oclCheckError(ciErrNum, CL_SUCCESS);
}
// Copy result from device to host for each device
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
ciErrNum = clEnqueueReadBuffer(commandQueue[i], d_Result[i], CL_FALSE, 0, ACCUM_N * sizeof(float),
h_SumGPU + i * ACCUM_N, 0, NULL, &GPUDone[i]);
oclCheckError(ciErrNum, CL_SUCCESS);
}
// Synchronize with the GPUs and do accumulated error check
clWaitForEvents(ciDeviceCount, GPUDone);
shrLog("clWaitForEvents complete...\n\n");
// Aggregate results for multiple GPU's and stop/log processing time
sumGPU = 0;
for(unsigned int i = 0; i < ciDeviceCount * ACCUM_N; i++)
{
sumGPU += h_SumGPU[i];
}
// Print Execution Times for each GPU
#ifdef GPU_PROFILING
shrLog("Profiling Information for GPU Processing:\n\n");
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
cdDevice = oclGetDev(cxGPUContext, deviceNr[i]);
clGetDeviceInfo(cdDevice, CL_DEVICE_NAME, sizeof(cDeviceName), cDeviceName, NULL);
shrLog("Device %i : %s\n", deviceNr[i], cDeviceName);
shrLog(" Reduce Kernel : %.5f s\n", executionTime(GPUExecution[i]));
shrLog(" Copy Device->Host : %.5f s\n\n\n", executionTime(GPUDone[i]));
}
#endif
// Run the computation on the Host CPU and log processing time
shrLog("Launching Host/CPU C++ Computation...\n\n");
sumCPU = 0;
for(unsigned int i = 0; i < DATA_N; i++)
{
sumCPU += h_Data[i];
}
// Check GPU result against CPU result
dRelError = 100.0 * fabs(sumCPU - sumGPU) / fabs(sumCPU);
shrLog("Comparing against Host/C++ computation...\n");
shrLog(" GPU sum: %f\n CPU sum: %f\n", sumGPU, sumCPU);
shrLog(" Relative Error (100.0 * Error / Golden) = %f \n\n", dRelError);
// cleanup
free(source);
free(h_Data);
for(unsigned int i = 0; i < ciDeviceCount; ++i )
{
clReleaseKernel(reduceKernel[i]);
clReleaseCommandQueue(commandQueue[i]);
}
clReleaseProgram(cpProgram);
clReleaseContext(cxGPUContext);
// finish
shrQAFinishExit(argc, (const char **)argv, (dRelError < 1e-4) ? QA_PASSED : QA_FAILED);
}
// Main program
//*****************************************************************************
int main(int argc, char** argv)
{
pArgc = &argc;
pArgv = argv;
shrQAStart(argc, argv);
// Start logs
cExecutableName = argv[0];
shrSetLogFileName ("oclSobelFilter.txt");
shrLog("%s Starting (Using %s)...\n\n", argv[0], clSourcefile);
// Get command line args for quick test or QA test, if provided
bNoPrompt = (bool)shrCheckCmdLineFlag(argc, (const char**)argv, "noprompt");
bQATest = (bool)shrCheckCmdLineFlag(argc, (const char**)argv, "qatest");
// Menu items
if (!(bQATest))
{
ShowMenuItems();
}
// Find the path from the exe to the image file
cPathAndName = shrFindFilePath(cImageFile, argv[0]);
oclCheckErrorEX(cPathAndName != NULL, shrTRUE, pCleanup);
shrLog("Image File\t = %s\nImage Dimensions = %u w x %u h x %u bpp\n\n", cPathAndName, uiImageWidth, uiImageHeight, sizeof(unsigned int)<<3);
// Initialize OpenGL items (if not No-GL QA test)
shrLog("%sInitGL...\n\n", bQATest ? "Skipping " : "Calling ");
if (!(bQATest))
{
InitGL(&argc, argv);
}
//Get the NVIDIA platform if available, otherwise use default
char cBuffer[1024];
bool bNV = false;
shrLog("Get Platform ID... ");
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
ciErrNum = clGetPlatformInfo (cpPlatform, CL_PLATFORM_NAME, sizeof(cBuffer), cBuffer, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("%s\n\n", cBuffer);
bNV = (strstr(cBuffer, "NVIDIA") != NULL);
//Get the devices
shrLog("Get Device Info...\n");
cl_uint uiNumAllDevs = 0;
GpuDevMngr = new DeviceManager(cpPlatform, &uiNumAllDevs, pCleanup);
// Get selected device if specified, otherwise examine avaiable ones and choose by perf
cl_int iSelectedDevice = 0;
if((shrGetCmdLineArgumenti(argc, (const char**)argv, "device", &iSelectedDevice)) || (uiNumAllDevs == 1))
{
// Use 1 selected device
GpuDevMngr->uiUsefulDevCt = 1;
iSelectedDevice = CLAMP((cl_uint)iSelectedDevice, 0, (uiNumAllDevs - 1));
GpuDevMngr->uiUsefulDevs[0] = iSelectedDevice;
GpuDevMngr->fLoadProportions[0] = 1.0f;
shrLog(" Using 1 Selected Device for Sobel Filter Computation...\n");
}
else
{
// Use available useful devices and Compute the device load proportions
ciErrNum = GpuDevMngr->GetDevLoadProportions(bNV);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
if (GpuDevMngr->uiUsefulDevCt == 1)
{
iSelectedDevice = GpuDevMngr->uiUsefulDevs[0];
}
shrLog(" Using %u Device(s) for Sobel Filter Computation\n", GpuDevMngr->uiUsefulDevCt);
}
//Create the context
shrLog("\nclCreateContext...\n\n");
cxGPUContext = clCreateContext(0, uiNumAllDevs, GpuDevMngr->cdDevices, NULL, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Allocate per-device OpenCL objects for useful devices
cqCommandQueue = new cl_command_queue[GpuDevMngr->uiUsefulDevCt];
ckSobel = new cl_kernel[GpuDevMngr->uiUsefulDevCt];
cmDevBufIn = new cl_mem[GpuDevMngr->uiUsefulDevCt];
cmDevBufOut = new cl_mem[GpuDevMngr->uiUsefulDevCt];
szAllocDevBytes = new size_t[GpuDevMngr->uiUsefulDevCt];
uiInHostPixOffsets = new cl_uint[GpuDevMngr->uiUsefulDevCt];
uiOutHostPixOffsets = new cl_uint[GpuDevMngr->uiUsefulDevCt];
uiDevImageHeight = new cl_uint[GpuDevMngr->uiUsefulDevCt];
// Create command queue(s) for device(s)
shrLog("clCreateCommandQueue...\n");
for (cl_uint i = 0; i < GpuDevMngr->uiUsefulDevCt; i++)
{
cqCommandQueue[i] = clCreateCommandQueue(cxGPUContext, GpuDevMngr->cdDevices[GpuDevMngr->uiUsefulDevs[i]], 0, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog(" CommandQueue %u, Device %u, Device Load Proportion = %.2f, ", i, GpuDevMngr->uiUsefulDevs[i], GpuDevMngr->fLoadProportions[i]);
oclPrintDevName(LOGBOTH, GpuDevMngr->cdDevices[GpuDevMngr->uiUsefulDevs[i]]);
shrLog("\n");
}
// Allocate pinned input and output host image buffers: mem copy operations to/from pinned memory is much faster than paged memory
szBuffBytes = uiImageWidth * uiImageHeight * sizeof (unsigned int);
cmPinnedBufIn = clCreateBuffer(cxGPUContext, CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, szBuffBytes, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cmPinnedBufOut = clCreateBuffer(cxGPUContext, CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, szBuffBytes, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("\nclCreateBuffer (Input and Output Pinned Host buffers)...\n");
// Get mapped pointers for writing to pinned input and output host image pointers
uiInput = (cl_uint*)clEnqueueMapBuffer(cqCommandQueue[0], cmPinnedBufIn, CL_TRUE, CL_MAP_WRITE, 0, szBuffBytes, 0, NULL, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
uiOutput = (cl_uint*)clEnqueueMapBuffer(cqCommandQueue[0], cmPinnedBufOut, CL_TRUE, CL_MAP_READ, 0, szBuffBytes, 0, NULL, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("clEnqueueMapBuffer (Pointer to Input and Output pinned host buffers)...\n");
// Load image data from file to pinned input host buffer
ciErrNum = shrLoadPPM4ub(cPathAndName, (unsigned char **)&uiInput, &uiImageWidth, &uiImageHeight);
oclCheckErrorEX(ciErrNum, shrTRUE, pCleanup);
shrLog("Load Input Image to Input pinned host buffer...\n");
// Read the kernel in from file
free(cPathAndName);
cPathAndName = shrFindFilePath(clSourcefile, argv[0]);
oclCheckErrorEX(cPathAndName != NULL, shrTRUE, pCleanup);
cSourceCL = oclLoadProgSource(cPathAndName, "// My comment\n", &szKernelLength);
oclCheckErrorEX(cSourceCL != NULL, shrTRUE, pCleanup);
shrLog("Load OpenCL Prog Source from File...\n");
// Create the program object
cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&cSourceCL, &szKernelLength, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("clCreateProgramWithSource...\n");
// Build the program with 'mad' Optimization option
#ifdef MAC
char *flags = "-cl-fast-relaxed-math -DMAC";
#else
char *flags = "-cl-fast-relaxed-math";
#endif
ciErrNum = clBuildProgram(cpProgram, 0, NULL, flags, NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// On error: write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclSobelFilter.ptx");
Cleanup(EXIT_FAILURE);
}
shrLog("clBuildProgram...\n\n");
// Determine, the size/shape of the image portions for each dev and create the device buffers
unsigned uiSumHeight = 0;
for (cl_uint i = 0; i < GpuDevMngr->uiUsefulDevCt; i++)
{
// Create kernel instance
ckSobel[i] = clCreateKernel(cpProgram, "ckSobel", &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("clCreateKernel (ckSobel), Device %u...\n", i);
// Allocations and offsets for the portion of the image worked on by each device
if (GpuDevMngr->uiUsefulDevCt == 1)
{
// One device processes the whole image with no offset
uiDevImageHeight[i] = uiImageHeight;
uiInHostPixOffsets[i] = 0;
uiOutHostPixOffsets[i] = 0;
szAllocDevBytes[i] = uiDevImageHeight[i] * uiImageWidth * sizeof(cl_uint);
}
else if (i == 0)
{
// Multiple devices, top stripe zone including topmost row of image:
// Over-allocate on device by 1 row
// Set offset and size to copy extra 1 padding row H2D (below bottom of stripe)
// Won't return the last row (dark/garbage row) D2H
uiInHostPixOffsets[i] = 0;
uiOutHostPixOffsets[i] = 0;
uiDevImageHeight[i] = (cl_uint)(GpuDevMngr->fLoadProportions[GpuDevMngr->uiUsefulDevs[i]] * (float)uiImageHeight); // height is proportional to dev perf
uiSumHeight += uiDevImageHeight[i];
uiDevImageHeight[i] += 1;
szAllocDevBytes[i] = uiDevImageHeight[i] * uiImageWidth * sizeof(cl_uint);
}
else if (i < (GpuDevMngr->uiUsefulDevCt - 1))
{
// Multiple devices, middle stripe zone:
// Over-allocate on device by 2 rows
// Set offset and size to copy extra 2 padding rows H2D (above top and below bottom of stripe)
// Won't return the first and last rows (dark/garbage rows) D2H
uiInHostPixOffsets[i] = (uiSumHeight - 1) * uiImageWidth;
uiOutHostPixOffsets[i] = uiInHostPixOffsets[i] + uiImageWidth;
uiDevImageHeight[i] = (cl_uint)(GpuDevMngr->fLoadProportions[GpuDevMngr->uiUsefulDevs[i]] * (float)uiImageHeight); // height is proportional to dev perf
uiSumHeight += uiDevImageHeight[i];
uiDevImageHeight[i] += 2;
szAllocDevBytes[i] = uiDevImageHeight[i] * uiImageWidth * sizeof(cl_uint);
}
else
{
// Multiple devices, last boundary tile:
// Over-allocate on device by 1 row
// Set offset and size to copy extra 1 padding row H2D (above top of stripe)
// Won't return the first row (dark/garbage rows D2H
uiInHostPixOffsets[i] = (uiSumHeight - 1) * uiImageWidth;
uiOutHostPixOffsets[i] = uiInHostPixOffsets[i] + uiImageWidth;
uiDevImageHeight[i] = uiImageHeight - uiSumHeight; // "leftover" rows
uiSumHeight += uiDevImageHeight[i];
uiDevImageHeight[i] += 1;
szAllocDevBytes[i] = uiDevImageHeight[i] * uiImageWidth * sizeof(cl_uint);
}
shrLog("Image Height (rows) for Device %u = %u...\n", i, uiDevImageHeight[i]);
// Create the device buffers in GMEM on each device
cmDevBufIn[i] = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, szAllocDevBytes[i], NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cmDevBufOut[i] = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, szAllocDevBytes[i], NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("clCreateBuffer (Input and Output GMEM buffers, Device %u)...\n", i);
// Set the common argument values for the Median kernel instance for each device
int iLocalPixPitch = iBlockDimX + 2;
ciErrNum = clSetKernelArg(ckSobel[i], 0, sizeof(cl_mem), (void*)&cmDevBufIn[i]);
ciErrNum |= clSetKernelArg(ckSobel[i], 1, sizeof(cl_mem), (void*)&cmDevBufOut[i]);
ciErrNum |= clSetKernelArg(ckSobel[i], 2, (iLocalPixPitch * (iBlockDimY + 2) * sizeof(cl_uchar4)), NULL);
ciErrNum |= clSetKernelArg(ckSobel[i], 3, sizeof(cl_int), (void*)&iLocalPixPitch);
ciErrNum |= clSetKernelArg(ckSobel[i], 4, sizeof(cl_uint), (void*)&uiImageWidth);
ciErrNum |= clSetKernelArg(ckSobel[i], 6, sizeof(cl_float), (void*)&fThresh);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
shrLog("clSetKernelArg (0-4), Device %u...\n\n", i);
}
// Set common global and local work sizes for Median kernel
szLocalWorkSize[0] = iBlockDimX;
szLocalWorkSize[1] = iBlockDimY;
szGlobalWorkSize[0] = shrRoundUp((int)szLocalWorkSize[0], uiImageWidth);
// init running timers
shrDeltaT(0); // timer 0 used for computation timing
shrDeltaT(1); // timer 1 used for fps computation
// Start main GLUT rendering loop for processing and rendering,
// or otherwise run No-GL Q/A test sequence
if (!(bQATest))
{
glutMainLoop();
}
else
{
TestNoGL();
}
Cleanup(EXIT_SUCCESS);
}
bool runTest(int argc, const char **argv)
{
bool ok = true;
float *host_output;
float *device_output;
float *input;
float *coeff;
int defaultDim;
int dimx;
int dimy;
int dimz;
int outerDimx;
int outerDimy;
int outerDimz;
int radius;
int timesteps;
size_t volumeSize;
memsize_t memsize;
const float lowerBound = 0.0f;
const float upperBound = 1.0f;
// Determine default dimensions
shrLog("Set-up, based upon target device GMEM size...\n");
if (ok)
{
// Get the memory size of the target device
shrLog(" getTargetDeviceGlobalMemSize\n");
ok = getTargetDeviceGlobalMemSize(&memsize, argc, argv);
}
if (ok)
{
// We can never use all the memory so to keep things simple we aim to
// use around half the total memory
memsize /= 2;
// Most of our memory use is taken up by the input and output buffers -
// two buffers of equal size - and for simplicity the volume is a cube:
// dim = floor( (N/2)^(1/3) )
defaultDim = (int)floor(pow((memsize / (2.0 * sizeof(float))), 1.0/3.0));
// By default, make the volume edge size an integer multiple of 128B to
// improve performance by coalescing memory accesses, in a real
// application it would make sense to pad the lines accordingly
int roundTarget = 128 / sizeof(float);
defaultDim = defaultDim / roundTarget * roundTarget;
defaultDim -= k_radius_default * 2;
// Check dimension is valid
if (defaultDim < k_dim_min)
{
shrLogEx(LOGBOTH | ERRORMSG, -1000, STDERROR);
shrLog("\tinsufficient device memory (maximum volume on device is %d, must be between %d and %d).\n", defaultDim, k_dim_min, k_dim_max);
ok = false;
}
else if (defaultDim > k_dim_max)
{
defaultDim = k_dim_max;
}
}
// For QA testing, override default volume size
if (ok)
{
if (shrCheckCmdLineFlag(argc, argv, "qatest"))
{
defaultDim = MIN(defaultDim, k_dim_qa);
}
}
// Parse command line arguments
if (ok)
{
char *dim = 0;
if (shrGetCmdLineArgumentstr(argc, argv, "dimx", &dim))
{
dimx = (int)atoi(dim);
if (dimx < k_dim_min || dimx > k_dim_max)
{
shrLogEx(LOGBOTH | ERRORMSG, -1001, STDERROR);
shrLog("\tdimx out of range (%d requested, must be between %d and %d), see header files for details.\n", dimx, k_dim_min, k_dim_max);
ok = false;
}
}
else
{
dimx = defaultDim;
}
if (shrGetCmdLineArgumentstr(argc, argv, "dimy", &dim))
{
dimy = (int)atoi(dim);
if (dimy < k_dim_min || dimy > k_dim_max)
{
shrLogEx(LOGBOTH | ERRORMSG, -1002, STDERROR);
shrLog("\tdimy out of range (%d requested, must be between %d and %d), see header files for details.\n", dimy, k_dim_min, k_dim_max);
ok = false;
}
}
else
{
dimy = defaultDim;
}
if (shrGetCmdLineArgumentstr(argc, argv, "dimz", &dim))
{
dimz = (int)atoi(dim);
if (dimz < k_dim_min || dimz > k_dim_max)
{
shrLogEx(LOGBOTH | ERRORMSG, -1003, STDERROR);
shrLog("\tdimz out of range (%d requested, must be between %d and %d), see header files for details.\n", dimz, k_dim_min, k_dim_max);
ok = false;
}
}
else
{
dimz = defaultDim;
}
if (shrGetCmdLineArgumentstr(argc, argv, "radius", &dim))
{
radius = (int)atoi(dim);
if (radius < k_radius_min || radius >= k_radius_max)
{
shrLogEx(LOGBOTH | ERRORMSG, -1004, STDERROR);
shrLog("\tradius out of range (%d requested, must be between %d and %d), see header files for details.\n", radius, k_radius_min, k_radius_max);
ok = false;
}
}
else
{
radius = k_radius_default;
}
if (shrGetCmdLineArgumentstr(argc, argv, "timesteps", &dim))
{
timesteps = (int)atoi(dim);
if (timesteps < k_timesteps_min || radius >= k_timesteps_max)
{
shrLogEx(LOGBOTH | ERRORMSG, -1005, STDERROR);
shrLog("\ttimesteps out of range (%d requested, must be between %d and %d), see header files for details.\n", timesteps, k_timesteps_min, k_timesteps_max);
ok = false;
}
}
else
{
timesteps = k_timesteps_default;
}
if (dim)
free(dim);
}
// Determine volume size
if (ok)
{
outerDimx = dimx + 2 * radius;
outerDimy = dimy + 2 * radius;
outerDimz = dimz + 2 * radius;
volumeSize = outerDimx * outerDimy * outerDimz;
}
// Allocate memory
if (ok)
{
shrLog(" calloc host_output\n");
if ((host_output = (float *)calloc(volumeSize, sizeof(float))) == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -1006, STDERROR);
shrLog("\tInsufficient memory for host_output calloc, please try a smaller volume (use --help for syntax).\n");
ok = false;
}
}
if (ok)
{
shrLog(" malloc input\n");
if ((input = (float *)malloc(volumeSize * sizeof(float))) == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -1007, STDERROR);
shrLog("\tInsufficient memory for input malloc, please try a smaller volume (use --help for syntax).\n");
ok = false;
}
}
if (ok)
{
shrLog(" malloc coeff\n");
if ((coeff = (float *)malloc((radius + 1) * sizeof(float))) == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -1008, STDERROR);
shrLog("\tInsufficient memory for coeff malloc, please try a smaller volume (use --help for syntax).\n");
ok = false;
}
}
// Create coefficients
if (ok)
{
for (int i = 0 ; i <= radius ; i++)
{
coeff[i] = 0.1f;
}
}
// Generate data
if (ok)
{
shrLog(" generateRandomData\n\n");
generateRandomData(input, outerDimx, outerDimy, outerDimz, lowerBound, upperBound);
}
if (ok)
{
shrLog("FDTD on %d x %d x %d volume with symmetric filter radius %d for %d timesteps...\n\n", dimx, dimy, dimz, radius, timesteps);
}
// Execute on the host
if (ok)
{
shrLog("fdtdReference...\n");
ok = fdtdReference(host_output, input, coeff, dimx, dimy, dimz, radius, timesteps);
shrLog("fdtdReference complete\n");
}
// Allocate memory
if (ok)
{
shrLog(" calloc device_output\n");
if ((device_output = (float *)calloc(volumeSize, sizeof(float))) == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -1009, STDERROR);
shrLog("\tInsufficient memory for device output calloc, please try a smaller volume (use --help for syntax).\n");
ok = false;
}
}
// Execute on the device
if (ok)
{
shrLog("fdtdGPU...\n");
ok = fdtdGPU(device_output, input, coeff, dimx, dimy, dimz, radius, timesteps, argc, argv);
shrLog("fdtdGPU complete\n");
}
// Compare the results
if (ok)
{
float tolerance = 0.0001f;
shrLog("\nCompareData (tolerance %f)...\n", tolerance);
ok = compareData(device_output, host_output, dimx, dimy, dimz, radius, tolerance);
}
return ok;
}
////////////////////////////////////////////////////////////////////////////////
//! Run a simple test for
////////////////////////////////////////////////////////////////////////////////
int runTest(int argc, const char** argv)
{
cl_platform_id cpPlatform = NULL;
cl_uint ciDeviceCount = 0;
cl_device_id *cdDevices = NULL;
cl_int ciErrNum = CL_SUCCESS;
//Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
if (ciErrNum != CL_SUCCESS)
{
shrLog("Error: Failed to create OpenCL context!\n");
return ciErrNum;
}
//Get the devices
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 0, NULL, &ciDeviceCount);
cdDevices = (cl_device_id *)malloc(ciDeviceCount * sizeof(cl_device_id) );
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, ciDeviceCount, cdDevices, NULL);
if (ciErrNum != CL_SUCCESS)
{
shrLog("Error: Failed to create OpenCL context!\n");
return ciErrNum;
}
//Create the context
cxGPUContext = clCreateContext(0, ciDeviceCount, cdDevices, NULL, NULL, &ciErrNum);
if (ciErrNum != CL_SUCCESS)
{
shrLog("Error: Failed to create OpenCL context!\n");
return ciErrNum;
}
if(shrCheckCmdLineFlag(argc, (const char**)argv, "device"))
{
// User specified GPUs
char* deviceList;
char* deviceStr;
char* next_token;
shrGetCmdLineArgumentstr(argc, (const char**)argv, "device", &deviceList);
#ifdef WIN32
deviceStr = strtok_s (deviceList," ,.-", &next_token);
#else
deviceStr = strtok (deviceList," ,.-");
#endif
ciDeviceCount = 0;
while(deviceStr != NULL)
{
// get and print the device for this queue
cl_device_id device = oclGetDev(cxGPUContext, atoi(deviceStr));
if( device == (cl_device_id) -1 ) {
shrLog(" Device %s does not exist!\n", deviceStr);
return -1;
}
shrLog("Device %s: ", deviceStr);
oclPrintDevName(LOGBOTH, device);
shrLog("\n");
// create command queue
commandQueue[ciDeviceCount] = clCreateCommandQueue(cxGPUContext, device, CL_QUEUE_PROFILING_ENABLE, &ciErrNum);
if (ciErrNum != CL_SUCCESS)
{
shrLog(" Error %i in clCreateCommandQueue call !!!\n\n", ciErrNum);
return ciErrNum;
}
++ciDeviceCount;
#ifdef WIN32
deviceStr = strtok_s (NULL," ,.-", &next_token);
#else
deviceStr = strtok (NULL," ,.-");
#endif
}
free(deviceList);
}
else
{
// Find out how many GPU's to compute on all available GPUs
size_t nDeviceBytes;
ciErrNum |= clGetContextInfo(cxGPUContext, CL_CONTEXT_DEVICES, 0, NULL, &nDeviceBytes);
ciDeviceCount = (cl_uint)nDeviceBytes/sizeof(cl_device_id);
if (ciErrNum != CL_SUCCESS)
{
shrLog(" Error %i in clGetDeviceIDs call !!!\n\n", ciErrNum);
return ciErrNum;
}
else if (ciDeviceCount == 0)
{
shrLog(" There are no devices supporting OpenCL (return code %i)\n\n", ciErrNum);
return -1;
}
// create command-queues
for(unsigned int i = 0; i < ciDeviceCount; ++i)
{
// get and print the device for this queue
cl_device_id device = oclGetDev(cxGPUContext, i);
shrLog("Device %d: ", i);
oclPrintDevName(LOGBOTH, device);
shrLog("\n");
// create command queue
commandQueue[i] = clCreateCommandQueue(cxGPUContext, device, CL_QUEUE_PROFILING_ENABLE, &ciErrNum);
if (ciErrNum != CL_SUCCESS)
{
shrLog(" Error %i in clCreateCommandQueue call !!!\n\n", ciErrNum);
return ciErrNum;
}
}
}
// Optional Command-line multiplier for matrix sizes
shrGetCmdLineArgumenti(argc, (const char**)argv, "sizemult", &iSizeMultiple);
iSizeMultiple = CLAMP(iSizeMultiple, 1, 10);
uiWA = WA * iSizeMultiple;
uiHA = HA * iSizeMultiple;
uiWB = WB * iSizeMultiple;
uiHB = HB * iSizeMultiple;
uiWC = WC * iSizeMultiple;
uiHC = HC * iSizeMultiple;
shrLog("\nUsing Matrix Sizes: A(%u x %u), B(%u x %u), C(%u x %u)\n",
uiWA, uiHA, uiWB, uiHB, uiWC, uiHC);
// allocate host memory for matrices A and B
unsigned int size_A = uiWA * uiHA;
unsigned int mem_size_A = sizeof(float) * size_A;
float* h_A_data = (float*)malloc(mem_size_A);
unsigned int size_B = uiWB * uiHB;
unsigned int mem_size_B = sizeof(float) * size_B;
float* h_B_data = (float*)malloc(mem_size_B);
// initialize host memory
srand(2006);
shrFillArray(h_A_data, size_A);
shrFillArray(h_B_data, size_B);
// allocate host memory for result
unsigned int size_C = uiWC * uiHC;
unsigned int mem_size_C = sizeof(float) * size_C;
float* h_C = (float*) malloc(mem_size_C);
// create OpenCL buffer pointing to the host memory
cl_mem h_A = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_USE_HOST_PTR,
mem_size_A, h_A_data, &ciErrNum);
if (ciErrNum != CL_SUCCESS)
{
shrLog("Error: clCreateBuffer\n");
return ciErrNum;
}
// Program Setup
size_t program_length;
const char* header_path = shrFindFilePath("matrixMul.h", argv[0]);
oclCheckError(header_path != NULL, shrTRUE);
char* header = oclLoadProgSource(header_path, "", &program_length);
if(!header)
{
shrLog("Error: Failed to load the header %s!\n", header_path);
return -1000;
}
const char* source_path = shrFindFilePath("matrixMul.cl", argv[0]);
oclCheckError(source_path != NULL, shrTRUE);
char *source = oclLoadProgSource(source_path, header, &program_length);
if(!source)
{
shrLog("Error: Failed to load compute program %s!\n", source_path);
return -2000;
}
// create the program
cl_program cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&source,
&program_length, &ciErrNum);
if (ciErrNum != CL_SUCCESS)
{
shrLog("Error: Failed to create program\n");
return ciErrNum;
}
free(header);
free(source);
// build the program
ciErrNum = clBuildProgram(cpProgram, 0, NULL, "-cl-fast-relaxed-math", NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then return error
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclMatrixMul.ptx");
return ciErrNum;
}
// write out PTX if requested on the command line
if(shrCheckCmdLineFlag(argc, argv, "dump-ptx") )
{
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclMatrixMul.ptx");
}
// Create Kernel
for(unsigned int i = 0; i < ciDeviceCount; ++i) {
multiplicationKernel[i] = clCreateKernel(cpProgram, "matrixMul", &ciErrNum);
if (ciErrNum != CL_SUCCESS)
{
shrLog("Error: Failed to create kernel\n");
return ciErrNum;
}
}
// Run multiplication on 1..deviceCount GPUs to compare improvement
shrLog("\nRunning Computations on 1 - %d GPU's...\n\n", ciDeviceCount);
for(unsigned int k = 1; k <= ciDeviceCount; ++k)
{
matrixMulGPU(k, h_A, h_B_data, mem_size_B, h_C);
}
// compute reference solution
shrLog("Comparing results with CPU computation... \n\n");
float* reference = (float*) malloc(mem_size_C);
computeGold(reference, h_A_data, h_B_data, uiHA, uiWA, uiWB);
// check result
shrBOOL res = shrCompareL2fe(reference, h_C, size_C, 1.0e-6f);
if (res != shrTRUE)
{
printDiff(reference, h_C, uiWC, uiHC, 100, 1.0e-5f);
}
// clean up OCL resources
ciErrNum = clReleaseMemObject(h_A);
for(unsigned int k = 0; k < ciDeviceCount; ++k)
{
ciErrNum |= clReleaseKernel( multiplicationKernel[k] );
ciErrNum |= clReleaseCommandQueue( commandQueue[k] );
}
ciErrNum |= clReleaseProgram(cpProgram);
ciErrNum |= clReleaseContext(cxGPUContext);
if(ciErrNum != CL_SUCCESS)
{
shrLog("Error: Failure releasing OpenCL resources: %d\n", ciErrNum);
return ciErrNum;
}
// clean up memory
free(h_A_data);
free(h_B_data);
free(h_C);
free(reference);
return ((shrTRUE == res) ? CL_SUCCESS : -3000);
}
// Main function
// *********************************************************************
int main(int argc, char** argv)
{
shrQAStart(argc, argv);
int use_gpu = 0;
for(int i = 0; i < argc && argv; i++)
{
if(!argv[i])
continue;
if(strstr(argv[i], "cpu"))
use_gpu = 0;
else if(strstr(argv[i], "gpu"))
use_gpu = 1;
}
// start logs
shrSetLogFileName ("oclDXTCompression.txt");
shrLog("%s Starting...\n\n", argv[0]);
cl_platform_id cpPlatform = NULL;
cl_uint uiNumDevices = 0;
cl_device_id *cdDevices = NULL;
cl_context cxGPUContext;
cl_command_queue cqCommandQueue;
cl_program cpProgram;
cl_kernel ckKernel;
cl_mem cmMemObjs[3];
cl_mem cmAlphaTable4, cmProds4;
cl_mem cmAlphaTable3, cmProds3;
size_t szGlobalWorkSize[1];
size_t szLocalWorkSize[1];
cl_int ciErrNum;
// Get the path of the filename
char *filename;
if (shrGetCmdLineArgumentstr(argc, (const char **)argv, "image", &filename)) {
image_filename = filename;
}
// load image
const char* image_path = shrFindFilePath(image_filename, argv[0]);
oclCheckError(image_path != NULL, shrTRUE);
shrLoadPPM4ub(image_path, (unsigned char **)&h_img, &width, &height);
oclCheckError(h_img != NULL, shrTRUE);
shrLog("Loaded '%s', %d x %d pixels\n\n", image_path, width, height);
// Convert linear image to block linear.
const uint memSize = width * height * sizeof(cl_uint);
uint* block_image = (uint*)malloc(memSize);
// Convert linear image to block linear.
for(uint by = 0; by < height/4; by++) {
for(uint bx = 0; bx < width/4; bx++) {
for (int i = 0; i < 16; i++) {
const int x = i & 3;
const int y = i / 4;
block_image[(by * width/4 + bx) * 16 + i] =
((uint *)h_img)[(by * 4 + y) * 4 * (width/4) + bx * 4 + x];
}
}
}
// Get the NVIDIA platform
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckError(ciErrNum, CL_SUCCESS);
// Get the platform's GPU devices
ciErrNum = clGetDeviceIDs(cpPlatform, use_gpu?CL_DEVICE_TYPE_GPU:CL_DEVICE_TYPE_CPU, 0, NULL, &uiNumDevices);
oclCheckError(ciErrNum, CL_SUCCESS);
cdDevices = (cl_device_id *)malloc(uiNumDevices * sizeof(cl_device_id) );
ciErrNum = clGetDeviceIDs(cpPlatform, use_gpu?CL_DEVICE_TYPE_GPU:CL_DEVICE_TYPE_CPU, uiNumDevices, cdDevices, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
// Create the context
cxGPUContext = clCreateContext(0, uiNumDevices, cdDevices, NULL, NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// get and log device
cl_device_id device;
if( shrCheckCmdLineFlag(argc, (const char **)argv, "device") ) {
int device_nr = 0;
shrGetCmdLineArgumenti(argc, (const char **)argv, "device", &device_nr);
device = oclGetDev(cxGPUContext, device_nr);
if( device == (cl_device_id)-1 ) {
shrLog(" Invalid GPU Device: devID=%d. %d valid GPU devices detected\n\n", device_nr, uiNumDevices);
shrLog(" exiting...\n");
return -1;
}
} else {
device = oclGetMaxFlopsDev(cxGPUContext);
}
oclPrintDevName(LOGBOTH, device);
shrLog("\n");
// create a command-queue
cqCommandQueue = clCreateCommandQueue(cxGPUContext, device, 0, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// Memory Setup
// Constants
cmAlphaTable4 = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, 4 * sizeof(cl_float), (void*)&alphaTable4[0], &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
cmProds4 = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, 4 * sizeof(cl_int), (void*)&prods4[0], &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
cmAlphaTable3 = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, 4 * sizeof(cl_float), (void*)&alphaTable3[0], &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
cmProds3 = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, 4 * sizeof(cl_int), (void*)&prods3[0], &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// Compute permutations.
cl_uint permutations[1024];
computePermutations(permutations);
// Upload permutations.
cmMemObjs[0] = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(cl_uint) * 1024, permutations, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// Image
cmMemObjs[1] = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, memSize, NULL, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// Result
const uint compressedSize = (width / 4) * (height / 4) * 8;
cmMemObjs[2] = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, compressedSize, NULL , &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
unsigned int * h_result = (uint*)malloc(compressedSize);
// Program Setup
size_t program_length;
const char* source_path = shrFindFilePath("DXTCompression.cl", argv[0]);
oclCheckError(source_path != NULL, shrTRUE);
char *source = oclLoadProgSource(source_path, "", &program_length);
oclCheckError(source != NULL, shrTRUE);
// create the program
cpProgram = clCreateProgramWithSource(cxGPUContext, 1,
(const char **) &source, &program_length, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// build the program
ciErrNum = clBuildProgram(cpProgram, 0, NULL, "-cl-fast-relaxed-math", NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclDXTCompression.ptx");
oclCheckError(ciErrNum, CL_SUCCESS);
}
// create the kernel
ckKernel = clCreateKernel(cpProgram, "compress", &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
// set the args values
ciErrNum = clSetKernelArg(ckKernel, 0, sizeof(cl_mem), (void *) &cmMemObjs[0]);
ciErrNum |= clSetKernelArg(ckKernel, 1, sizeof(cl_mem), (void *) &cmMemObjs[1]);
ciErrNum |= clSetKernelArg(ckKernel, 2, sizeof(cl_mem), (void *) &cmMemObjs[2]);
ciErrNum |= clSetKernelArg(ckKernel, 3, sizeof(cl_mem), (void*)&cmAlphaTable4);
ciErrNum |= clSetKernelArg(ckKernel, 4, sizeof(cl_mem), (void*)&cmProds4);
ciErrNum |= clSetKernelArg(ckKernel, 5, sizeof(cl_mem), (void*)&cmAlphaTable3);
ciErrNum |= clSetKernelArg(ckKernel, 6, sizeof(cl_mem), (void*)&cmProds3);
oclCheckError(ciErrNum, CL_SUCCESS);
// Copy input data host to device
clEnqueueWriteBuffer(cqCommandQueue, cmMemObjs[1], CL_FALSE, 0, sizeof(cl_uint) * width * height, block_image, 0,0,0);
// Determine launch configuration and run timed computation numIterations times
int blocks = ((width + 3) / 4) * ((height + 3) / 4); // rounds up by 1 block in each dim if %4 != 0
// Restrict the numbers of blocks to launch on low end GPUs to avoid kernel timeout
cl_uint compute_units;
clGetDeviceInfo(device, CL_DEVICE_MAX_COMPUTE_UNITS, sizeof(compute_units), &compute_units, NULL);
int blocksPerLaunch = MIN(blocks, 768 * (int)compute_units);
// set work-item dimensions
szGlobalWorkSize[0] = blocksPerLaunch * NUM_THREADS;
szLocalWorkSize[0]= NUM_THREADS;
#ifdef GPU_PROFILING
shrLog("\nRunning DXT Compression on %u x %u image...\n", width, height);
shrLog("\n%u Workgroups, %u Work Items per Workgroup, %u Work Items in NDRange...\n\n",
blocks, NUM_THREADS, blocks * NUM_THREADS);
int numIterations = 50;
for (int i = -1; i < numIterations; ++i) {
if (i == 0) { // start timing only after the first warmup iteration
clFinish(cqCommandQueue); // flush command queue
shrDeltaT(0); // start timer
}
#endif
// execute kernel
for( int j=0; j<blocks; j+= blocksPerLaunch ) {
clSetKernelArg(ckKernel, 7, sizeof(int), &j);
szGlobalWorkSize[0] = MIN( blocksPerLaunch, blocks-j ) * NUM_THREADS;
ciErrNum = clEnqueueNDRangeKernel(cqCommandQueue, ckKernel, 1, NULL,
szGlobalWorkSize, szLocalWorkSize,
0, NULL, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
}
#ifdef GPU_PROFILING
}
clFinish(cqCommandQueue);
double dAvgTime = shrDeltaT(0) / (double)numIterations;
shrLogEx(LOGBOTH | MASTER, 0, "oclDXTCompression, Throughput = %.4f MPixels/s, Time = %.5f s, Size = %u Pixels, NumDevsUsed = %i, Workgroup = %d\n",
(1.0e-6 * (double)(width * height)/ dAvgTime), dAvgTime, (width * height), 1, szLocalWorkSize[0]);
#endif
// blocking read output
ciErrNum = clEnqueueReadBuffer(cqCommandQueue, cmMemObjs[2], CL_TRUE, 0,
compressedSize, h_result, 0, NULL, NULL);
oclCheckError(ciErrNum, CL_SUCCESS);
// Write DDS file.
FILE* fp = NULL;
char output_filename[1024];
#ifdef WIN32
strcpy_s(output_filename, 1024, image_path);
strcpy_s(output_filename + strlen(image_path) - 3, 1024 - strlen(image_path) + 3, "dds");
fopen_s(&fp, output_filename, "wb");
#else
strcpy(output_filename, image_path);
strcpy(output_filename + strlen(image_path) - 3, "dds");
fp = fopen(output_filename, "wb");
#endif
oclCheckError(fp != NULL, shrTRUE);
DDSHeader header;
header.fourcc = FOURCC_DDS;
header.size = 124;
header.flags = (DDSD_WIDTH|DDSD_HEIGHT|DDSD_CAPS|DDSD_PIXELFORMAT|DDSD_LINEARSIZE);
header.height = height;
header.width = width;
header.pitch = compressedSize;
header.depth = 0;
header.mipmapcount = 0;
memset(header.reserved, 0, sizeof(header.reserved));
header.pf.size = 32;
header.pf.flags = DDPF_FOURCC;
header.pf.fourcc = FOURCC_DXT1;
header.pf.bitcount = 0;
header.pf.rmask = 0;
header.pf.gmask = 0;
header.pf.bmask = 0;
header.pf.amask = 0;
header.caps.caps1 = DDSCAPS_TEXTURE;
header.caps.caps2 = 0;
header.caps.caps3 = 0;
header.caps.caps4 = 0;
header.notused = 0;
fwrite(&header, sizeof(DDSHeader), 1, fp);
fwrite(h_result, compressedSize, 1, fp);
fclose(fp);
// Make sure the generated image matches the reference image (regression check)
shrLog("\nComparing against Host/C++ computation...\n");
const char* reference_image_path = shrFindFilePath(refimage_filename, argv[0]);
oclCheckError(reference_image_path != NULL, shrTRUE);
// read in the reference image from file
#ifdef WIN32
fopen_s(&fp, reference_image_path, "rb");
#else
fp = fopen(reference_image_path, "rb");
#endif
oclCheckError(fp != NULL, shrTRUE);
fseek(fp, sizeof(DDSHeader), SEEK_SET);
uint referenceSize = (width / 4) * (height / 4) * 8;
uint * reference = (uint *)malloc(referenceSize);
fread(reference, referenceSize, 1, fp);
fclose(fp);
// compare the reference image data to the sample/generated image
float rms = 0;
for (uint y = 0; y < height; y += 4)
{
for (uint x = 0; x < width; x += 4)
{
// binary comparison of data
uint referenceBlockIdx = ((y/4) * (width/4) + (x/4));
uint resultBlockIdx = ((y/4) * (width/4) + (x/4));
int cmp = compareBlock(((BlockDXT1 *)h_result) + resultBlockIdx, ((BlockDXT1 *)reference) + referenceBlockIdx);
// log deviations, if any
if (cmp != 0.0f)
{
compareBlock(((BlockDXT1 *)h_result) + resultBlockIdx, ((BlockDXT1 *)reference) + referenceBlockIdx);
shrLog("Deviation at (%d, %d):\t%f rms\n", x/4, y/4, float(cmp)/16/3);
}
rms += cmp;
}
}
rms /= width * height * 3;
shrLog("RMS(reference, result) = %f\n\n", rms);
// Free OpenCL resources
oclDeleteMemObjs(cmMemObjs, 3);
clReleaseMemObject(cmAlphaTable4);
clReleaseMemObject(cmProds4);
clReleaseMemObject(cmAlphaTable3);
clReleaseMemObject(cmProds3);
clReleaseKernel(ckKernel);
clReleaseProgram(cpProgram);
clReleaseCommandQueue(cqCommandQueue);
clReleaseContext(cxGPUContext);
// Free host memory
free(source);
free(h_img);
// finish
shrQAFinishExit(argc, (const char **)argv, (rms <= ERROR_THRESHOLD) ? QA_PASSED : QA_FAILED);
}
int main(int argc, char **argv)
{
GpuProfiling::initProf();
// Start logs
shrSetLogFileName ("scan.txt");
shrLog("%s Starting...\n\n", argv[0]);
//Use command-line specified CUDA device, otherwise use device with highest Gflops/s
if( cutCheckCmdLineFlag(argc, (const char**)argv, "device") )
cutilDeviceInit(argc, argv);
else
cudaSetDevice( cutGetMaxGflopsDeviceId() );
uint *d_Input, *d_Output;
uint *h_Input, *h_OutputCPU, *h_OutputGPU;
uint hTimer;
const uint N = 13 * 1048576 / 2;
shrLog("Allocating and initializing host arrays...\n");
cutCreateTimer(&hTimer);
h_Input = (uint *)malloc(N * sizeof(uint));
h_OutputCPU = (uint *)malloc(N * sizeof(uint));
h_OutputGPU = (uint *)malloc(N * sizeof(uint));
srand(2009);
for(uint i = 0; i < N; i++)
h_Input[i] = rand();
shrLog("Allocating and initializing CUDA arrays...\n");
cutilSafeCall( cudaMalloc((void **)&d_Input, N * sizeof(uint)) );
cutilSafeCall( cudaMalloc((void **)&d_Output, N * sizeof(uint)) );
cutilSafeCall( cudaMemcpy(d_Input, h_Input, N * sizeof(uint), cudaMemcpyHostToDevice) );
shrLog("Initializing CUDA-C scan...\n\n");
initScan();
int globalFlag = 1;
size_t szWorkgroup;
const int iCycles = 100;
shrLog("*** Running GPU scan for short arrays (%d identical iterations)...\n\n", iCycles);
for(uint arrayLength = MIN_SHORT_ARRAY_SIZE; arrayLength <= MAX_SHORT_ARRAY_SIZE; arrayLength <<= 1){
shrLog("Running scan for %u elements (%u arrays)...\n", arrayLength, N / arrayLength);
cutilSafeCall( cudaThreadSynchronize() );
cutResetTimer(hTimer);
cutStartTimer(hTimer);
for(int i = 0; i < iCycles; i++)
{
szWorkgroup = scanExclusiveShort(d_Output, d_Input, N / arrayLength, arrayLength);
}
cutilSafeCall( cudaThreadSynchronize());
cutStopTimer(hTimer);
double timerValue = 1.0e-3 * cutGetTimerValue(hTimer) / iCycles;
shrLog("Validating the results...\n");
shrLog("...reading back GPU results\n");
cutilSafeCall( cudaMemcpy(h_OutputGPU, d_Output, N * sizeof(uint), cudaMemcpyDeviceToHost) );
shrLog(" ...scanExclusiveHost()\n");
scanExclusiveHost(h_OutputCPU, h_Input, N / arrayLength, arrayLength);
// Compare GPU results with CPU results and accumulate error for this test
shrLog(" ...comparing the results\n");
int localFlag = 1;
for(uint i = 0; i < N; i++)
{
if(h_OutputCPU[i] != h_OutputGPU[i])
{
localFlag = 0;
break;
}
}
// Log message on individual test result, then accumulate to global flag
shrLog(" ...Results %s\n\n", (localFlag == 1) ? "Match" : "DON'T Match !!!");
globalFlag = globalFlag && localFlag;
// Data log
if (arrayLength == MAX_SHORT_ARRAY_SIZE)
{
shrLog("\n");
shrLogEx(LOGBOTH | MASTER, 0, "scan-Short, Throughput = %.4f MElements/s, Time = %.5f s, Size = %u Elements, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * (double)arrayLength/timerValue), timerValue, arrayLength, 1, szWorkgroup);
shrLog("\n");
}
}
shrLog("***Running GPU scan for large arrays (%u identical iterations)...\n\n", iCycles);
for(uint arrayLength = MIN_LARGE_ARRAY_SIZE; arrayLength <= MAX_LARGE_ARRAY_SIZE; arrayLength <<= 1){
shrLog("Running scan for %u elements (%u arrays)...\n", arrayLength, N / arrayLength);
cutilSafeCall( cudaThreadSynchronize() );
cutResetTimer(hTimer);
cutStartTimer(hTimer);
for(int i = 0; i < iCycles; i++)
{
szWorkgroup = scanExclusiveLarge(d_Output, d_Input, N / arrayLength, arrayLength);
}
cutilSafeCall( cudaThreadSynchronize() );
cutStopTimer(hTimer);
double timerValue = 1.0e-3 * cutGetTimerValue(hTimer) / iCycles;
shrLog("Validating the results...\n");
shrLog("...reading back GPU results\n");
cutilSafeCall( cudaMemcpy(h_OutputGPU, d_Output, N * sizeof(uint), cudaMemcpyDeviceToHost) );
shrLog("...scanExclusiveHost()\n");
scanExclusiveHost(h_OutputCPU, h_Input, N / arrayLength, arrayLength);
// Compare GPU results with CPU results and accumulate error for this test
shrLog(" ...comparing the results\n");
int localFlag = 1;
for(uint i = 0; i < N; i++)
{
if(h_OutputCPU[i] != h_OutputGPU[i])
{
localFlag = 0;
break;
}
}
// Log message on individual test result, then accumulate to global flag
shrLog(" ...Results %s\n\n", (localFlag == 1) ? "Match" : "DON'T Match !!!");
globalFlag = globalFlag && localFlag;
// Data log
if (arrayLength == MAX_LARGE_ARRAY_SIZE)
{
shrLog("\n");
shrLogEx(LOGBOTH | MASTER, 0, "scan-Large, Throughput = %.4f MElements/s, Time = %.5f s, Size = %u Elements, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * (double)arrayLength/timerValue), timerValue, arrayLength, 1, szWorkgroup);
shrLog("\n");
}
}
// pass or fail (cumulative... all tests in the loop)
shrLog(globalFlag ? "PASSED\n\n" : "FAILED\n\n");
GpuProfiling::printResults();
shrLog("Shutting down...\n");
closeScan();
cutilSafeCall( cudaFree(d_Output));
cutilSafeCall( cudaFree(d_Input));
cutilCheckError( cutDeleteTimer(hTimer) );
cudaThreadExit();
exit(0);
shrEXIT(argc, (const char**)argv);
}
bool fdtdGPU(float *output, const float *input, const float *coeff, const int dimx, const int dimy, const int dimz, const int radius, const int timesteps, const int argc, const char **argv)
{
bool ok = true;
const int outerDimx = dimx + 2 * radius;
const int outerDimy = dimy + 2 * radius;
const int outerDimz = dimz + 2 * radius;
const size_t volumeSize = outerDimx * outerDimy * outerDimz;
cl_context context = 0;
cl_platform_id platform = 0;
cl_device_id *devices = 0;
cl_command_queue commandQueue = 0;
cl_mem bufferOut = 0;
cl_mem bufferIn = 0;
cl_mem bufferCoeff = 0;
cl_program program = 0;
cl_kernel kernel = 0;
cl_event *kernelEvents = 0;
#ifdef GPU_PROFILING
cl_ulong kernelEventStart;
cl_ulong kernelEventEnd;
#endif
double hostElapsedTimeS;
char *cPathAndName = 0;
char *cSourceCL = 0;
size_t szKernelLength;
size_t globalWorkSize[2];
size_t localWorkSize[2];
cl_uint deviceCount = 0;
cl_uint targetDevice = 0;
cl_int errnum = 0;
char buildOptions[128];
// Ensure that the inner data starts on a 128B boundary
const int padding = (128 / sizeof(float)) - radius;
const size_t paddedVolumeSize = volumeSize + padding;
#ifdef GPU_PROFILING
const int profileTimesteps = timesteps - 1;
if (ok)
{
if (profileTimesteps < 1)
{
shrLog(" cannot profile with fewer than two timesteps (timesteps=%d), profiling is disabled.\n", timesteps);
}
}
#endif
// Get the NVIDIA platform
if (ok)
{
shrLog(" oclGetPlatformID...\n");
errnum = oclGetPlatformID(&platform);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("oclGetPlatformID (returned %d).\n", errnum);
ok = false;
}
}
// Get the list of GPU devices associated with the platform
if (ok)
{
shrLog(" clGetDeviceIDs");
errnum = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 0, NULL, &deviceCount);
devices = (cl_device_id *)malloc(deviceCount * sizeof(cl_device_id) );
errnum = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, deviceCount, devices, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clGetDeviceIDs (returned %d).\n", errnum);
ok = false;
}
}
// Create the OpenCL context
if (ok)
{
shrLog(" clCreateContext...\n");
context = clCreateContext(0, deviceCount, devices, NULL, NULL, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateContext (returned %d).\n", errnum);
ok = false;
}
}
// Select target device (device 0 by default)
if (ok)
{
char *device = 0;
if (shrGetCmdLineArgumentstr(argc, argv, "device", &device))
{
targetDevice = (cl_uint)atoi(device);
if (targetDevice >= deviceCount)
{
shrLogEx(LOGBOTH | ERRORMSG, -2001, STDERROR);
shrLog("invalid target device specified on command line (device %d does not exist).\n", targetDevice);
ok = false;
}
}
else
{
targetDevice = 0;
}
if (device)
{
free(device);
}
}
// Create a command-queue
if (ok)
{
shrLog(" clCreateCommandQueue\n");
commandQueue = clCreateCommandQueue(context, devices[targetDevice], CL_QUEUE_PROFILING_ENABLE, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateCommandQueue (returned %d).\n", errnum);
ok = false;
}
}
// Create memory buffer objects
if (ok)
{
shrLog(" clCreateBuffer bufferOut\n");
bufferOut = clCreateBuffer(context, CL_MEM_READ_WRITE, paddedVolumeSize * sizeof(float), NULL, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateBuffer (returned %d).\n", errnum);
ok = false;
}
}
if (ok)
{
shrLog(" clCreateBuffer bufferIn\n");
bufferIn = clCreateBuffer(context, CL_MEM_READ_WRITE, paddedVolumeSize * sizeof(float), NULL, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateBuffer (returned %d).\n", errnum);
ok = false;
}
}
if (ok)
{
shrLog(" clCreateBuffer bufferCoeff\n");
bufferCoeff = clCreateBuffer(context, CL_MEM_READ_ONLY, (radius + 1) * sizeof(float), NULL, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateBuffer (returned %d).\n", errnum);
ok = false;
}
}
// Load the kernel from file
if (ok)
{
shrLog(" shrFindFilePath\n");
cPathAndName = shrFindFilePath(clSourceFile, argv[0]);
if (cPathAndName == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -2002, STDERROR);
shrLog("shrFindFilePath returned null.\n");
ok = false;
}
}
if (ok)
{
shrLog(" oclLoadProgSource\n");
cSourceCL = oclLoadProgSource(cPathAndName, "// Preamble\n", &szKernelLength);
if (cSourceCL == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -2003, STDERROR);
shrLog("oclLoadProgSource returned null.\n");
ok = false;
}
}
// Create the program
if (ok)
{
shrLog(" clCreateProgramWithSource\n");
program = clCreateProgramWithSource(context, 1, (const char **)&cSourceCL, &szKernelLength, &errnum);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateProgramWithSource (returned %d).\n", errnum);
ok = false;
}
}
// Check for a command-line specified work group size
size_t userWorkSize;
int localWorkMaxY;
if (ok)
{
int userWorkSizeInt;
if (shrGetCmdLineArgumenti(argc, argv, "work-group-size", &userWorkSizeInt))
{
// We can't clamp to CL_KERNEL_WORK_GROUP_SIZE yet since that is
// dependent on the build.
if (userWorkSizeInt < k_localWorkMin || userWorkSizeInt > k_localWorkMax)
{
shrLogEx(LOGBOTH | ERRORMSG, -2004, STDERROR);
shrLog("invalid work group size specified on command line (must be between %d and %d).\n", k_localWorkMin, k_localWorkMax);
ok = false;
}
// Constrain to a multiple of k_localWorkX
userWorkSize = (userWorkSizeInt / k_localWorkX * k_localWorkX);
}
else
{
userWorkSize = k_localWorkY * k_localWorkX;
}
// Divide by k_localWorkX (integer division to clamp)
localWorkMaxY = userWorkSize / k_localWorkX;
}
// Build the program
if (ok)
{
#ifdef WIN32
if (sprintf_s(buildOptions, sizeof(buildOptions), "-DRADIUS=%d -DMAXWORKX=%d -DMAXWORKY=%d -cl-fast-relaxed-math", radius, k_localWorkX, localWorkMaxY) < 0)
{
shrLogEx(LOGBOTH | ERRORMSG, -2005, STDERROR);
shrLog("sprintf_s (failed).\n");
ok = false;
}
#else
if (snprintf(buildOptions, sizeof(buildOptions), "-DRADIUS=%d -DMAXWORKX=%d -DMAXWORKY=%d -cl-fast-relaxed-math", radius, k_localWorkX, localWorkMaxY) < 0)
{
shrLogEx(LOGBOTH | ERRORMSG, -2005, STDERROR);
shrLog("snprintf (failed).\n");
ok = false;
}
#endif
}
if (ok)
{
shrLog(" clBuildProgram (%s)\n", buildOptions);
errnum = clBuildProgram(program, 0, NULL, buildOptions, NULL, NULL);
if (errnum != CL_SUCCESS)
{
char buildLog[10240];
clGetProgramBuildInfo(program, devices[0], CL_PROGRAM_BUILD_LOG, sizeof(buildLog), buildLog, NULL);
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clBuildProgram (returned %d).\n", errnum);
shrLog("Log:\n%s\n", buildLog);
ok = false;
}
}
// Create the kernel
if (ok)
{
shrLog(" clCreateKernel\n");
kernel = clCreateKernel(program, "FiniteDifferences", &errnum);
if (kernel == (cl_kernel)NULL || errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clCreateKernel (returned %d).\n", errnum);
ok = false;
}
}
// Get the maximum work group size
size_t maxWorkSize;
if (ok)
{
shrLog(" clGetKernelWorkGroupInfo\n");
errnum = clGetKernelWorkGroupInfo(kernel, devices[targetDevice], CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &maxWorkSize, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clGetKernelWorkGroupInfo (returned %d).\n", errnum);
ok = false;
}
}
// Set the work group size
if (ok)
{
userWorkSize = CLAMP(userWorkSize, k_localWorkMin, maxWorkSize);
localWorkSize[0] = k_localWorkX;
localWorkSize[1] = userWorkSize / k_localWorkX;
globalWorkSize[0] = localWorkSize[0] * (unsigned int)ceil((float)dimx / localWorkSize[0]);
globalWorkSize[1] = localWorkSize[1] * (unsigned int)ceil((float)dimy / localWorkSize[1]);
shrLog(" set local work group size to %dx%d\n", localWorkSize[0], localWorkSize[1]);
shrLog(" set total work size to %dx%d\n", globalWorkSize[0], globalWorkSize[1]);
}
// Copy the input to the device input buffer
if (ok)
{
shrLog(" clEnqueueWriteBuffer bufferIn\n");
errnum = clEnqueueWriteBuffer(commandQueue, bufferIn, CL_TRUE, padding * sizeof(float), volumeSize * sizeof(float), input, 0, NULL, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clEnqueueWriteBuffer bufferIn (returned %d).\n", errnum);
ok = false;
}
}
// Copy the input to the device output buffer (actually only need the halo)
if (ok)
{
shrLog(" clEnqueueWriteBuffer bufferOut\n");
errnum = clEnqueueWriteBuffer(commandQueue, bufferOut, CL_TRUE, padding * sizeof(float), volumeSize * sizeof(float), input, 0, NULL, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clEnqueueWriteBuffer bufferOut (returned %d).\n", errnum);
ok = false;
}
}
// Copy the coefficients to the device coefficient buffer
if (ok)
{
shrLog(" clEnqueueWriteBuffer bufferCoeff\n");
errnum = clEnqueueWriteBuffer(commandQueue, bufferCoeff, CL_TRUE, 0, (radius + 1) * sizeof(float), coeff, 0, NULL, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clEnqueueWriteBuffer bufferCoeff (returned %d).\n", errnum);
ok = false;
}
}
// Allocate the events
if (ok)
{
shrLog(" calloc events\n");
if ((kernelEvents = (cl_event *)calloc(timesteps, sizeof(cl_event))) == NULL)
{
shrLogEx(LOGBOTH | ERRORMSG, -2006, STDERROR);
shrLog("Insufficient memory for events calloc, please try a smaller volume (use --help for syntax).\n");
ok = false;
}
}
// Start the clock
shrDeltaT(0);
// Set the constant arguments
if (ok)
{
shrLog(" clSetKernelArg 2-6\n");
errnum = clSetKernelArg(kernel, 2, sizeof(cl_mem), (void *)&bufferCoeff);
errnum |= clSetKernelArg(kernel, 3, sizeof(int), &dimx);
errnum |= clSetKernelArg(kernel, 4, sizeof(int), &dimy);
errnum |= clSetKernelArg(kernel, 5, sizeof(int), &dimz);
errnum |= clSetKernelArg(kernel, 6, sizeof(int), &padding);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clSetKernelArg 2-6 (returned %d).\n", errnum);
ok = false;
}
}
// Execute the FDTD
cl_mem bufferSrc = bufferIn;
cl_mem bufferDst = bufferOut;
if (ok)
{
shrLog(" GPU FDTD loop\n");
}
for (int it = 0 ; ok && it < timesteps ; it++)
{
shrLog("\tt = %d ", it);
// Set the dynamic arguments
if (ok)
{
shrLog(" clSetKernelArg 0-1,");
errnum = clSetKernelArg(kernel, 0, sizeof(cl_mem), (void *)&bufferDst);
errnum |= clSetKernelArg(kernel, 1, sizeof(cl_mem), (void *)&bufferSrc);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clSetKernelArg 0-1 (returned %d).\n", errnum);
ok = false;
}
}
// Launch the kernel
if (ok)
{
shrLog(" clEnqueueNDRangeKernel\n");
errnum = clEnqueueNDRangeKernel(commandQueue, kernel, 2, NULL, globalWorkSize, localWorkSize, 0, NULL, &kernelEvents[it]);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clEnqueueNDRangeKernel (returned %d).\n", errnum);
ok = false;
}
}
// Toggle the buffers
cl_mem tmp = bufferSrc;
bufferSrc = bufferDst;
bufferDst = tmp;
}
if (ok)
shrLog("\n");
// Wait for the kernel to complete
if (ok)
{
shrLog(" clWaitForEvents\n");
errnum = clWaitForEvents(1, &kernelEvents[timesteps-1]);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clWaitForEvents (returned %d).\n", errnum);
ok = false;
}
}
// Stop the clock
hostElapsedTimeS = shrDeltaT(0);
// Read the result back, result is in bufferSrc (after final toggle)
if (ok)
{
shrLog(" clEnqueueReadBuffer\n");
errnum = clEnqueueReadBuffer(commandQueue, bufferSrc, CL_TRUE, padding * sizeof(float), volumeSize * sizeof(float), output, 0, NULL, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clEnqueueReadBuffer bufferSrc (returned %d).\n", errnum);
ok = false;
}
}
// Report time
#ifdef GPU_PROFILING
double elapsedTime = 0.0;
if (ok && profileTimesteps > 0)
shrLog(" Collect profile information\n");
for (int it = 1 ; ok && it <= profileTimesteps ; it++)
{
shrLog("\tt = %d ", it);
shrLog(" clGetEventProfilingInfo,", it);
errnum = clGetEventProfilingInfo(kernelEvents[it], CL_PROFILING_COMMAND_START, sizeof(cl_ulong), &kernelEventStart, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clGetEventProfilingInfo (returned %d).\n", errnum);
ok = false;
}
shrLog(" clGetEventProfilingInfo\n", it);
errnum = clGetEventProfilingInfo(kernelEvents[it], CL_PROFILING_COMMAND_END, sizeof(cl_ulong), &kernelEventEnd, NULL);
if (errnum != CL_SUCCESS)
{
shrLogEx(LOGBOTH | ERRORMSG, errnum, STDERROR);
shrLog("clGetEventProfilingInfo (returned %d).\n", errnum);
ok = false;
}
elapsedTime += (double)kernelEventEnd - (double)kernelEventStart;
}
if (ok && profileTimesteps > 0)
{
shrLog("\n");
// Convert nanoseconds to seconds
elapsedTime *= 1.0e-9;
double avgElapsedTime = elapsedTime / (double)profileTimesteps;
// Determine number of computations per timestep
size_t pointsComputed = dimx * dimy * dimz;
// Determine throughput
double throughputM = 1.0e-6 * (double)pointsComputed / avgElapsedTime;
shrLogEx(LOGBOTH | MASTER, 0, "oclFDTD3d, Throughput = %.4f MPoints/s, Time = %.5f s, Size = %u Points, NumDevsUsed = %i, Workgroup = %u\n",
throughputM, avgElapsedTime, pointsComputed, 1, localWorkSize[0] * localWorkSize[1]);
}
#endif
// Cleanup
if (kernelEvents)
{
for (int it = 0 ; it < timesteps ; it++)
{
if (kernelEvents[it])
clReleaseEvent(kernelEvents[it]);
}
free(kernelEvents);
}
if (kernel)
clReleaseKernel(kernel);
if (program)
clReleaseProgram(program);
if (cSourceCL)
free(cSourceCL);
if (cPathAndName)
free(cPathAndName);
if (bufferCoeff)
clReleaseMemObject(bufferCoeff);
if (bufferIn)
clReleaseMemObject(bufferIn);
if (bufferOut)
clReleaseMemObject(bufferOut);
if (commandQueue)
clReleaseCommandQueue(commandQueue);
if (devices)
free(devices);
if (context)
clReleaseContext(context);
return ok;
}
// Function to read in kernel from uncompiled source, create the OCL program and build the OCL program
// **************************************************************************************************
int CreateProgramAndKernel(cl_context cxGPUContext, cl_device_id* cdDevices, const char *kernel_name, cl_kernel *kernel, bool bDouble)
{
cl_program cpProgram;
size_t szSourceLen;
cl_int ciErrNum = CL_SUCCESS;
// Read the kernel in from file
shrLog("\nLoading Uncompiled kernel from .cl file, using %s\n", clSourcefile);
char* cPathAndFile = shrFindFilePath(clSourcefile, cExecutablePath);
oclCheckError(cPathAndFile != NULL, shrTRUE);
char* pcSource = oclLoadProgSource(cPathAndFile, "", &szSourceLen);
oclCheckError(pcSource != NULL, shrTRUE);
// Check OpenCL version -> vec3 types are supported only from version 1.1 and above
char cOCLVersion[32];
clGetDeviceInfo(cdDevices[0], CL_DEVICE_VERSION, sizeof(cOCLVersion), &cOCLVersion, 0);
int iVec3Length = 3;
if( strncmp("OpenCL 1.0", cOCLVersion, 10) == 0 ) {
iVec3Length = 4;
}
//for double precision
char *pcSourceForDouble;
std::stringstream header;
if (bDouble)
{
header << "#define REAL double";
header << std::endl;
header << "#define REAL4 double4";
header << std::endl;
header << "#define REAL3 double" << iVec3Length;
header << std::endl;
header << "#define ZERO3 {0.0, 0.0, 0.0" << ((iVec3Length == 4) ? ", 0.0}" : "}");
header << std::endl;
}
else
{
header << "#define REAL float";
header << std::endl;
header << "#define REAL4 float4";
header << std::endl;
header << "#define REAL3 float" << iVec3Length;
header << std::endl;
header << "#define ZERO3 {0.0f, 0.0f, 0.0f" << ((iVec3Length == 4) ? ", 0.0f}" : "}");
header << std::endl;
}
header << pcSource;
pcSourceForDouble = (char *)malloc(header.str().size() + 1);
szSourceLen = header.str().size();
#ifdef WIN32
strcpy_s(pcSourceForDouble, szSourceLen + 1, header.str().c_str());
#else
strcpy(pcSourceForDouble, header.str().c_str());
#endif
// create the program
cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&pcSourceForDouble, &szSourceLen, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateProgramWithSource\n");
// Build the program with 'mad' Optimization option
#ifdef MAC
char *flags = "-cl-fast-relaxed-math -DMAC";
#else
char *flags = "-cl-fast-relaxed-math";
#endif
ciErrNum = clBuildProgram(cpProgram, 0, NULL, flags, NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclNbody.ptx");
oclCheckError(ciErrNum, CL_SUCCESS);
}
shrLog("clBuildProgram\n");
// create the kernel
*kernel = clCreateKernel(cpProgram, kernel_name, &ciErrNum);
oclCheckError(ciErrNum, CL_SUCCESS);
shrLog("clCreateKernel\n");
size_t wgSize;
ciErrNum = clGetKernelWorkGroupInfo(*kernel, cdDevices[0], CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &wgSize, NULL);
if (wgSize == 64) {
shrLog(
"ERROR: Minimum work-group size 256 required by this application is not supported on this device.\n");
exit(0);
}
free(pcSourceForDouble);
return 0;
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int
main( int argc, char** argv)
{
//start logs
shrSetLogFileName ("volumeRender.txt");
shrLog("%s Starting...\n\n", argv[0]);
if (cutCheckCmdLineFlag(argc, (const char **)argv, "qatest") ||
cutCheckCmdLineFlag(argc, (const char **)argv, "noprompt"))
{
g_bQAReadback = true;
fpsLimit = frameCheckNumber;
}
if (cutCheckCmdLineFlag(argc, (const char **)argv, "glverify"))
{
g_bQAGLVerify = true;
fpsLimit = frameCheckNumber;
}
if (g_bQAReadback) {
// use command-line specified CUDA device, otherwise use device with highest Gflops/s
if( cutCheckCmdLineFlag(argc, (const char**)argv, "device") ) {
cutilDeviceInit(argc, argv);
} else {
cudaSetDevice( cutGetMaxGflopsDeviceId() );
}
} else {
// First initialize OpenGL context, so we can properly set the GL for CUDA.
// This is necessary in order to achieve optimal performance with OpenGL/CUDA interop.
initGL( &argc, argv );
// use command-line specified CUDA device, otherwise use device with highest Gflops/s
if( cutCheckCmdLineFlag(argc, (const char**)argv, "device") ) {
cutilGLDeviceInit(argc, argv);
} else {
cudaGLSetGLDevice( cutGetMaxGflopsDeviceId() );
}
/*
int device;
struct cudaDeviceProp prop;
cudaGetDevice( &device );
cudaGetDeviceProperties( &prop, device );
if( !strncmp( "Tesla", prop.name, 5 ) ) {
shrLog("This sample needs a card capable of OpenGL and display.\n");
shrLog("Please choose a different device with the -device=x argument.\n");
cutilExit(argc, argv);
}
*/
}
// parse arguments
char *filename;
if (cutGetCmdLineArgumentstr( argc, (const char**) argv, "file", &filename)) {
volumeFilename = filename;
}
int n;
if (cutGetCmdLineArgumenti( argc, (const char**) argv, "size", &n)) {
volumeSize.width = volumeSize.height = volumeSize.depth = n;
}
if (cutGetCmdLineArgumenti( argc, (const char**) argv, "xsize", &n)) {
volumeSize.width = n;
}
if (cutGetCmdLineArgumenti( argc, (const char**) argv, "ysize", &n)) {
volumeSize.height = n;
}
if (cutGetCmdLineArgumenti( argc, (const char**) argv, "zsize", &n)) {
volumeSize.depth = n;
}
// load volume data
char* path = shrFindFilePath(volumeFilename, argv[0]);
if (path == 0) {
shrLog("Error finding file '%s'\n", volumeFilename);
exit(EXIT_FAILURE);
}
size_t size = volumeSize.width*volumeSize.height*volumeSize.depth*sizeof(VolumeType);
void *h_volume = loadRawFile(path, size);
initCuda(h_volume, volumeSize);
free(h_volume);
cutilCheckError( cutCreateTimer( &timer));
shrLog("Press '=' and '-' to change density\n"
" ']' and '[' to change brightness\n"
" ';' and ''' to modify transfer function offset\n"
" '.' and ',' to modify transfer function scale\n\n");
// calculate new grid size
gridSize = dim3(iDivUp(width, blockSize.x), iDivUp(height, blockSize.y));
if (g_bQAReadback) {
g_CheckRender = new CheckBackBuffer(width, height, 4, false);
g_CheckRender->setPixelFormat(GL_RGBA);
g_CheckRender->setExecPath(argv[0]);
g_CheckRender->EnableQAReadback(true);
uint *d_output;
cutilSafeCall(cudaMalloc((void**)&d_output, width*height*sizeof(uint)));
cutilSafeCall(cudaMemset(d_output, 0, width*height*sizeof(uint)));
float modelView[16] =
{
1.0f, 0.0f, 0.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 1.0f, 0.0f,
0.0f, 0.0f, 4.0f, 1.0f
};
invViewMatrix[0] = modelView[0]; invViewMatrix[1] = modelView[4]; invViewMatrix[2] = modelView[8]; invViewMatrix[3] = modelView[12];
invViewMatrix[4] = modelView[1]; invViewMatrix[5] = modelView[5]; invViewMatrix[6] = modelView[9]; invViewMatrix[7] = modelView[13];
invViewMatrix[8] = modelView[2]; invViewMatrix[9] = modelView[6]; invViewMatrix[10] = modelView[10]; invViewMatrix[11] = modelView[14];
// call CUDA kernel, writing results to PBO
copyInvViewMatrix(invViewMatrix, sizeof(float4)*3);
// Start timer 0 and process n loops on the GPU
int nIter = 10;
for (int i = -1; i < nIter; i++)
{
if( i == 0 ) {
cudaThreadSynchronize();
cutStartTimer(timer);
}
render_kernel(gridSize, blockSize, d_output, width, height, density, brightness, transferOffset, transferScale);
}
cudaThreadSynchronize();
cutStopTimer(timer);
// Get elapsed time and throughput, then log to sample and master logs
double dAvgTime = cutGetTimerValue(timer)/(nIter * 1000.0);
shrLogEx(LOGBOTH | MASTER, 0, "volumeRender, Throughput = %.4f MTexels/s, Time = %.5f s, Size = %u Texels, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * width * height)/dAvgTime, dAvgTime, (width * height), 1, blockSize.x * blockSize.y);
cutilCheckMsg("Error: render_kernel() execution FAILED");
cutilSafeCall( cudaThreadSynchronize() );
cutilSafeCall( cudaMemcpy(g_CheckRender->imageData(), d_output, width*height*4, cudaMemcpyDeviceToHost) );
g_CheckRender->savePPM(sOriginal[g_Index], true, NULL);
if (!g_CheckRender->PPMvsPPM(sOriginal[g_Index], sReference[g_Index], MAX_EPSILON_ERROR, THRESHOLD)) {
shrLog("\nFAILED\n\n");
} else {
shrLog("\nPASSED\n\n");
}
cudaFree(d_output);
freeCudaBuffers();
if (g_CheckRender) {
delete g_CheckRender; g_CheckRender = NULL;
}
} else {
// This is the normal rendering path for VolumeRender
glutDisplayFunc(display);
glutKeyboardFunc(keyboard);
glutMouseFunc(mouse);
glutMotionFunc(motion);
glutReshapeFunc(reshape);
glutIdleFunc(idle);
initPixelBuffer();
if (g_bQAGLVerify) {
g_CheckRender = new CheckBackBuffer(width, height, 4);
g_CheckRender->setPixelFormat(GL_RGBA);
g_CheckRender->setExecPath(argv[0]);
g_CheckRender->EnableQAReadback(true);
}
atexit(cleanup);
glutMainLoop();
}
cudaThreadExit();
shrEXIT(argc, (const char**)argv);
}
// Main function
// *********************************************************************
int main(int argc, char** argv)
{
shrQAStart(argc, argv);
// get command line arg for quick test, if provided
bNoPrompt = shrCheckCmdLineFlag(argc, (const char **)argv, "noprompt");
// start logs
cExecutableName = argv[0];
shrSetLogFileName ("oclMatVecMul.txt");
shrLog("%s Starting...\n\n", argv[0]);
// calculate matrix height given GPU memory
shrLog("Determining Matrix height from available GPU mem...\n");
memsize_t memsize;
getTargetDeviceGlobalMemSize(&memsize, argc, (const char **)argv);
height = memsize/width/16;
if (height > MAX_HEIGHT)
height = MAX_HEIGHT;
shrLog(" Matrix width\t= %u\n Matrix height\t= %u\n\n", width, height);
// Allocate and initialize host arrays
shrLog("Allocate and Init Host Mem...\n\n");
unsigned int size = width * height;
unsigned int mem_size_M = size * sizeof(float);
M = (float*)malloc(mem_size_M);
unsigned int mem_size_V = width * sizeof(float);
V = (float*)malloc(mem_size_V);
unsigned int mem_size_W = height * sizeof(float);
W = (float*)malloc(mem_size_W);
shrFillArray(M, size);
shrFillArray(V, width);
Golden = (float*)malloc(mem_size_W);
MatVecMulHost(M, V, width, height, Golden);
//Get the NVIDIA platform
shrLog("Get the Platform ID...\n\n");
ciErrNum = oclGetPlatformID(&cpPlatform);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
//Get all the devices
shrLog("Get the Device info and select Device...\n");
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, 0, NULL, &uiNumDevices);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cdDevices = (cl_device_id *)malloc(uiNumDevices * sizeof(cl_device_id) );
ciErrNum = clGetDeviceIDs(cpPlatform, CL_DEVICE_TYPE_GPU, uiNumDevices, cdDevices, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Set target device and Query number of compute units on targetDevice
shrLog(" # of Devices Available = %u\n", uiNumDevices);
if(shrGetCmdLineArgumentu(argc, (const char **)argv, "device", &targetDevice)== shrTRUE)
{
targetDevice = CLAMP(targetDevice, 0, (uiNumDevices - 1));
}
shrLog(" Using Device %u: ", targetDevice);
oclPrintDevName(LOGBOTH, cdDevices[targetDevice]);
cl_uint num_compute_units;
clGetDeviceInfo(cdDevices[targetDevice], CL_DEVICE_MAX_COMPUTE_UNITS, sizeof(num_compute_units), &num_compute_units, NULL);
shrLog("\n # of Compute Units = %u\n\n", num_compute_units);
//Create the context
shrLog("clCreateContext...\n");
cxGPUContext = clCreateContext(0, uiNumDevsUsed, &cdDevices[targetDevice], NULL, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Create a command-queue
shrLog("clCreateCommandQueue...\n");
cqCommandQueue = clCreateCommandQueue(cxGPUContext, cdDevices[targetDevice], CL_QUEUE_PROFILING_ENABLE, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Allocate the OpenCL buffer memory objects for source and result on the device GMEM
shrLog("clCreateBuffer (M, V and W in device global memory, mem_size_m = %u)...\n", mem_size_M);
cmM = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, mem_size_M, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cmV = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, mem_size_V, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cmW = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, mem_size_W, NULL, &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Read the OpenCL kernel in from source file
shrLog("oclLoadProgSource (%s)...\n", cSourceFile);
cPathAndName = shrFindFilePath(cSourceFile, argv[0]);
oclCheckErrorEX(cPathAndName != NULL, shrTRUE, pCleanup);
cSourceCL = oclLoadProgSource(cPathAndName, "", &szKernelLength);
oclCheckErrorEX(cSourceCL != NULL, shrTRUE, pCleanup);
// Create the program
shrLog("clCreateProgramWithSource...\n");
cpProgram = clCreateProgramWithSource(cxGPUContext, 1, (const char **)&cSourceCL, &szKernelLength, &ciErrNum);
// Build the program
shrLog("clBuildProgram...\n");
ciErrNum = clBuildProgram(cpProgram, uiNumDevsUsed, &cdDevices[targetDevice], "-cl-fast-relaxed-math", NULL, NULL);
if (ciErrNum != CL_SUCCESS)
{
// write out standard error, Build Log and PTX, then cleanup and exit
shrLogEx(LOGBOTH | ERRORMSG, ciErrNum, STDERROR);
oclLogBuildInfo(cpProgram, oclGetFirstDev(cxGPUContext));
oclLogPtx(cpProgram, oclGetFirstDev(cxGPUContext), "oclMatVecMul.ptx");
shrQAFinish(argc, (const char **)argv, QA_FAILED);
Cleanup(EXIT_FAILURE);
}
// --------------------------------------------------------
// Core sequence... copy input data to GPU, compute, copy results back
// Asynchronous write of data to GPU device
shrLog("clEnqueueWriteBuffer (M and V)...\n\n");
ciErrNum = clEnqueueWriteBuffer(cqCommandQueue, cmM, CL_FALSE, 0, mem_size_M, M, 0, NULL, NULL);
ciErrNum |= clEnqueueWriteBuffer(cqCommandQueue, cmV, CL_FALSE, 0, mem_size_V, V, 0, NULL, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Kernels
const char* kernels[] = {
"MatVecMulUncoalesced0",
"MatVecMulUncoalesced1",
"MatVecMulCoalesced0",
"MatVecMulCoalesced1",
"MatVecMulCoalesced2",
"MatVecMulCoalesced3" };
for (int k = 0; k < (int)(sizeof(kernels)/sizeof(char*)); ++k) {
shrLog("Running with Kernel %s...\n\n", kernels[k]);
// Clear result
shrLog(" Clear result with clEnqueueWriteBuffer (W)...\n");
memset(W, 0, mem_size_W);
ciErrNum = clEnqueueWriteBuffer(cqCommandQueue, cmW, CL_FALSE, 0, mem_size_W, W, 0, NULL, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Create the kernel
shrLog(" clCreateKernel...\n");
if (ckKernel) {
clReleaseKernel(ckKernel);
ckKernel = 0;
}
ckKernel = clCreateKernel(cpProgram, kernels[k], &ciErrNum);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Set and log Global and Local work size dimensions
szLocalWorkSize = 256;
if (k == 0)
szGlobalWorkSize = shrRoundUp((int)szLocalWorkSize, height); // rounded up to the nearest multiple of the LocalWorkSize
else
// Some experiments should be done here for determining the best global work size for a given device
// We will assume here that we can run 2 work-groups per compute unit
szGlobalWorkSize = 2 * num_compute_units * szLocalWorkSize;
shrLog(" Global Work Size \t\t= %u\n Local Work Size \t\t= %u\n # of Work Groups \t\t= %u\n",
szGlobalWorkSize, szLocalWorkSize, (szGlobalWorkSize % szLocalWorkSize + szGlobalWorkSize/szLocalWorkSize));
// Set the Argument values
shrLog(" clSetKernelArg...\n\n");
int n = 0;
ciErrNum = clSetKernelArg(ckKernel, n++, sizeof(cl_mem), (void*)&cmM);
ciErrNum |= clSetKernelArg(ckKernel, n++, sizeof(cl_mem), (void*)&cmV);
ciErrNum |= clSetKernelArg(ckKernel, n++, sizeof(cl_int), (void*)&width);
ciErrNum |= clSetKernelArg(ckKernel, n++, sizeof(cl_int), (void*)&height);
ciErrNum |= clSetKernelArg(ckKernel, n++, sizeof(cl_mem), (void*)&cmW);
if (k > 1)
ciErrNum |= clSetKernelArg(ckKernel, n++, szLocalWorkSize * sizeof(float), 0);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Launch kernel
shrLog(" clEnqueueNDRangeKernel (%s)...\n", kernels[k]);
ciErrNum = clEnqueueNDRangeKernel(cqCommandQueue, ckKernel, 1, NULL, &szGlobalWorkSize, &szLocalWorkSize, 0, NULL, &ceEvent);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
// Read back results and check accumulated errors
shrLog(" clEnqueueReadBuffer (W)...\n");
ciErrNum = clEnqueueReadBuffer(cqCommandQueue, cmW, CL_TRUE, 0, mem_size_W, W, 0, NULL, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
#ifdef GPU_PROFILING
// Execution time
ciErrNum = clWaitForEvents(1, &ceEvent);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
cl_ulong start, end;
ciErrNum = clGetEventProfilingInfo(ceEvent, CL_PROFILING_COMMAND_END, sizeof(cl_ulong), &end, NULL);
ciErrNum |= clGetEventProfilingInfo(ceEvent, CL_PROFILING_COMMAND_START, sizeof(cl_ulong), &start, NULL);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
double dSeconds = 1.0e-9 * (double)(end - start);
shrLog(" Kernel execution time: %.5f s\n\n", dSeconds);
#endif
// Compare results for golden-host and report errors and pass/fail
shrLog(" Comparing against Host/C++ computation...\n\n");
shrBOOL res = shrCompareL2fe(Golden, W, height, 1e-6f);
shrLog(" GPU Result %s CPU Result within allowable tolerance\n\n", (res == shrTRUE) ? "MATCHES" : "DOESN'T MATCH");
bPassFlag &= (res == shrTRUE);
// Release event
ciErrNum = clReleaseEvent(ceEvent);
oclCheckErrorEX(ciErrNum, CL_SUCCESS, pCleanup);
ceEvent = 0;
}
// Master status Pass/Fail (all tests)
shrQAFinish(argc, (const char **)argv, (bPassFlag ? QA_PASSED : QA_FAILED) );
// Cleanup and leave
Cleanup (EXIT_SUCCESS);
}
void matrixMulGPU(cl_uint ciDeviceCount, cl_mem h_A, float* h_B_data, unsigned int mem_size_B, float* h_C )
{
cl_mem d_A[MAX_GPU_COUNT];
cl_mem d_C[MAX_GPU_COUNT];
cl_mem d_B[MAX_GPU_COUNT];
cl_event GPUDone[MAX_GPU_COUNT];
cl_event GPUExecution[MAX_GPU_COUNT];
// Start the computation on each available GPU
// Create buffers for each GPU
// Each GPU will compute sizePerGPU rows of the result
int sizePerGPU = uiHA / ciDeviceCount;
int workOffset[MAX_GPU_COUNT];
int workSize[MAX_GPU_COUNT];
workOffset[0] = 0;
for(unsigned int i=0; i < ciDeviceCount; ++i)
{
// Input buffer
workSize[i] = (i != (ciDeviceCount - 1)) ? sizePerGPU : (uiHA - workOffset[i]);
d_A[i] = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY, workSize[i] * sizeof(float) * uiWA, NULL,NULL);
// Copy only assigned rows from host to device
clEnqueueCopyBuffer(commandQueue[i], h_A, d_A[i], workOffset[i] * sizeof(float) * uiWA,
0, workSize[i] * sizeof(float) * uiWA, 0, NULL, NULL);
// create OpenCL buffer on device that will be initiatlize from the host memory on first use
// on device
d_B[i] = clCreateBuffer(cxGPUContext, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
mem_size_B, h_B_data, NULL);
// Output buffer
d_C[i] = clCreateBuffer(cxGPUContext, CL_MEM_WRITE_ONLY, workSize[i] * uiWC * sizeof(float), NULL,NULL);
// set the args values
clSetKernelArg(multiplicationKernel[i], 0, sizeof(cl_mem), (void *) &d_C[i]);
clSetKernelArg(multiplicationKernel[i], 1, sizeof(cl_mem), (void *) &d_A[i]);
clSetKernelArg(multiplicationKernel[i], 2, sizeof(cl_mem), (void *) &d_B[i]);
clSetKernelArg(multiplicationKernel[i], 3, sizeof(float) * BLOCK_SIZE *BLOCK_SIZE, 0 );
clSetKernelArg(multiplicationKernel[i], 4, sizeof(float) * BLOCK_SIZE *BLOCK_SIZE, 0 );
clSetKernelArg(multiplicationKernel[i], 5, sizeof(cl_int), (void *) &uiWA);
clSetKernelArg(multiplicationKernel[i], 6, sizeof(cl_int), (void *) &uiWB);
if(i+1 < ciDeviceCount)
workOffset[i + 1] = workOffset[i] + workSize[i];
}
// Execute Multiplication on all GPUs in parallel
size_t localWorkSize[] = {BLOCK_SIZE, BLOCK_SIZE};
size_t globalWorkSize[] = {shrRoundUp(BLOCK_SIZE, uiWC), shrRoundUp(BLOCK_SIZE, workSize[0])};
// Launch kernels on devices
#ifdef GPU_PROFILING
int nIter = 30;
for (int j = -1; j < nIter; j++)
{
// Sync all queues to host and start timer first time through loop
if(j == 0){
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
clFinish(commandQueue[i]);
}
shrDeltaT(0);
}
#endif
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
// Multiplication - non-blocking execution: launch and push to device(s)
globalWorkSize[1] = shrRoundUp(BLOCK_SIZE, workSize[i]);
clEnqueueNDRangeKernel(commandQueue[i], multiplicationKernel[i], 2, 0, globalWorkSize, localWorkSize,
0, NULL, &GPUExecution[i]);
clFlush(commandQueue[i]);
}
#ifdef GPU_PROFILING
}
#endif
// sync all queues to host
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
clFinish(commandQueue[i]);
}
#ifdef GPU_PROFILING
// stop and log timer
double dSeconds = shrDeltaT(0)/(double)nIter;
double dNumOps = 2.0 * (double)uiWA * (double)uiHA * (double)uiWB;
double gflops = 1.0e-9 * dNumOps/dSeconds;
shrLogEx(LOGBOTH | MASTER, 0, "oclMatrixMul, Throughput = %.4f GFlops/s, Time = %.5f s, Size = %.0f, NumDevsUsed = %d, Workgroup = %u\n",
gflops, dSeconds, dNumOps, ciDeviceCount, localWorkSize[0] * localWorkSize[1]);
// Print kernel timing per GPU
shrLog("\n");
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
shrLog(" Kernel execution time on GPU %d \t: %.5f s\n", i, executionTime(GPUExecution[i]));
}
shrLog("\n");
#endif
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
// Non-blocking copy of result from device to host
clEnqueueReadBuffer(commandQueue[i], d_C[i], CL_FALSE, 0, uiWC * sizeof(float) * workSize[i],
h_C + workOffset[i] * uiWC, 0, NULL, &GPUDone[i]);
}
// CPU sync with GPU
clWaitForEvents(ciDeviceCount, GPUDone);
// Release mem and event objects
for(unsigned int i = 0; i < ciDeviceCount; i++)
{
clReleaseMemObject(d_A[i]);
clReleaseMemObject(d_C[i]);
clReleaseMemObject(d_B[i]);
clReleaseEvent(GPUExecution[i]);
clReleaseEvent(GPUDone[i]);
}
}
int main(int argc, char **argv)
{
uchar *h_Data;
uint *h_HistogramCPU, *h_HistogramGPU;
uchar *d_Data;
uint *d_Histogram;
uint hTimer;
int PassFailFlag = 1;
uint byteCount = 64 * 1048576;
uint uiSizeMult = 1;
cudaDeviceProp deviceProp;
deviceProp.major = 0;
deviceProp.minor = 0;
int dev;
shrQAStart(argc, argv);
// set logfile name and start logs
shrSetLogFileName ("histogram.txt");
//Use command-line specified CUDA device, otherwise use device with highest Gflops/s
if( shrCheckCmdLineFlag(argc, (const char**)argv, "device") ) {
dev = cutilDeviceInit(argc, argv);
if (dev < 0) {
printf("No CUDA Capable Devices found, exiting...\n");
shrQAFinishExit(argc, (const char **)argv, QA_WAIVED);
}
} else {
cudaSetDevice( dev = cutGetMaxGflopsDeviceId() );
cutilSafeCall( cudaChooseDevice(&dev, &deviceProp) );
}
cutilSafeCall( cudaGetDeviceProperties(&deviceProp, dev) );
printf("CUDA device [%s] has %d Multi-Processors, Compute %d.%d\n",
deviceProp.name, deviceProp.multiProcessorCount, deviceProp.major, deviceProp.minor);
int version = deviceProp.major * 0x10 + deviceProp.minor;
if(version < 0x11)
{
printf("There is no device supporting a minimum of CUDA compute capability 1.1 for this SDK sample\n");
cutilDeviceReset();
shrQAFinishExit(argc, (const char **)argv, QA_WAIVED);
}
cutilCheckError(cutCreateTimer(&hTimer));
// Optional Command-line multiplier to increase size of array to histogram
if (shrGetCmdLineArgumentu(argc, (const char**)argv, "sizemult", &uiSizeMult))
{
uiSizeMult = CLAMP(uiSizeMult, 1, 10);
byteCount *= uiSizeMult;
}
shrLog("Initializing data...\n");
shrLog("...allocating CPU memory.\n");
h_Data = (uchar *)malloc(byteCount);
h_HistogramCPU = (uint *)malloc(HISTOGRAM256_BIN_COUNT * sizeof(uint));
h_HistogramGPU = (uint *)malloc(HISTOGRAM256_BIN_COUNT * sizeof(uint));
shrLog("...generating input data\n");
srand(2009);
for(uint i = 0; i < byteCount; i++)
h_Data[i] = rand() % 256;
shrLog("...allocating GPU memory and copying input data\n\n");
cutilSafeCall( cudaMalloc((void **)&d_Data, byteCount ) );
cutilSafeCall( cudaMalloc((void **)&d_Histogram, HISTOGRAM256_BIN_COUNT * sizeof(uint) ) );
cutilSafeCall( cudaMemcpy(d_Data, h_Data, byteCount, cudaMemcpyHostToDevice) );
{
shrLog("Starting up 64-bin histogram...\n\n");
initHistogram64();
shrLog("Running 64-bin GPU histogram for %u bytes (%u runs)...\n\n", byteCount, numRuns);
for(int iter = -1; iter < numRuns; iter++){
//iter == -1 -- warmup iteration
if(iter == 0){
cutilSafeCall( cutilDeviceSynchronize() );
cutilCheckError( cutResetTimer(hTimer) );
cutilCheckError( cutStartTimer(hTimer) );
}
histogram64(d_Histogram, d_Data, byteCount);
}
cutilSafeCall( cutilDeviceSynchronize() );
cutilCheckError( cutStopTimer(hTimer));
double dAvgSecs = 1.0e-3 * (double)cutGetTimerValue(hTimer) / (double)numRuns;
shrLog("histogram64() time (average) : %.5f sec, %.4f MB/sec\n\n", dAvgSecs, ((double)byteCount * 1.0e-6) / dAvgSecs);
shrLogEx(LOGBOTH | MASTER, 0, "histogram64, Throughput = %.4f MB/s, Time = %.5f s, Size = %u Bytes, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * (double)byteCount / dAvgSecs), dAvgSecs, byteCount, 1, HISTOGRAM64_THREADBLOCK_SIZE);
shrLog("\nValidating GPU results...\n");
shrLog(" ...reading back GPU results\n");
cutilSafeCall( cudaMemcpy(h_HistogramGPU, d_Histogram, HISTOGRAM64_BIN_COUNT * sizeof(uint), cudaMemcpyDeviceToHost) );
shrLog(" ...histogram64CPU()\n");
histogram64CPU(
h_HistogramCPU,
h_Data,
byteCount
);
shrLog(" ...comparing the results...\n");
for(uint i = 0; i < HISTOGRAM64_BIN_COUNT; i++)
if(h_HistogramGPU[i] != h_HistogramCPU[i]) PassFailFlag = 0;
shrLog(PassFailFlag ? " ...64-bin histograms match\n\n" : " ***64-bin histograms do not match!!!***\n\n" );
shrLog("Shutting down 64-bin histogram...\n\n\n");
closeHistogram64();
}
{
shrLog("Initializing 256-bin histogram...\n");
initHistogram256();
shrLog("Running 256-bin GPU histogram for %u bytes (%u runs)...\n\n", byteCount, numRuns);
for(int iter = -1; iter < numRuns; iter++){
//iter == -1 -- warmup iteration
if(iter == 0){
cutilSafeCall( cutilDeviceSynchronize() );
cutilCheckError( cutResetTimer(hTimer) );
cutilCheckError( cutStartTimer(hTimer) );
}
histogram256(d_Histogram, d_Data, byteCount);
}
cutilSafeCall( cutilDeviceSynchronize() );
cutilCheckError( cutStopTimer(hTimer));
double dAvgSecs = 1.0e-3 * (double)cutGetTimerValue(hTimer) / (double)numRuns;
shrLog("histogram256() time (average) : %.5f sec, %.4f MB/sec\n\n", dAvgSecs, ((double)byteCount * 1.0e-6) / dAvgSecs);
shrLogEx(LOGBOTH | MASTER, 0, "histogram256, Throughput = %.4f MB/s, Time = %.5f s, Size = %u Bytes, NumDevsUsed = %u, Workgroup = %u\n",
(1.0e-6 * (double)byteCount / dAvgSecs), dAvgSecs, byteCount, 1, HISTOGRAM256_THREADBLOCK_SIZE);
shrLog("\nValidating GPU results...\n");
shrLog(" ...reading back GPU results\n");
cutilSafeCall( cudaMemcpy(h_HistogramGPU, d_Histogram, HISTOGRAM256_BIN_COUNT * sizeof(uint), cudaMemcpyDeviceToHost) );
shrLog(" ...histogram256CPU()\n");
histogram256CPU(
h_HistogramCPU,
h_Data,
byteCount
);
shrLog(" ...comparing the results\n");
for(uint i = 0; i < HISTOGRAM256_BIN_COUNT; i++)
if(h_HistogramGPU[i] != h_HistogramCPU[i]) PassFailFlag = 0;
shrLog(PassFailFlag ? " ...256-bin histograms match\n\n" : " ***256-bin histograms do not match!!!***\n\n" );
shrLog("Shutting down 256-bin histogram...\n\n\n");
closeHistogram256();
}
shrLog("Shutting down...\n");
cutilCheckError(cutDeleteTimer(hTimer));
cutilSafeCall( cudaFree(d_Histogram) );
cutilSafeCall( cudaFree(d_Data) );
free(h_HistogramGPU);
free(h_HistogramCPU);
free(h_Data);
cutilDeviceReset();
shrLog("%s - Test Summary\n", sSDKsample);
// pass or fail (for both 64 bit and 256 bit histograms)
shrQAFinishExit(argc, (const char **)argv, (PassFailFlag ? QA_PASSED : QA_FAILED));
}
