pbf_dam_sim::pbf_dam_sim(scalar_t space)
{
init_cond = make_shared<pbf_dam_init_cond>(space);
init_cond->getParameter(simulatee.parameter);
init_cond->getExternalForce(simulatee.external);
auto domain = init_cond->getDomainRange();
const auto num_capacity = 40000;
simulatee.allocate(num_capacity, domain.second);
buffer.allocate(num_capacity, simulatee.ns->getMaxPairParticleNum());
vector<glm::vec3> x;
vector<glm::vec3> v;
init_cond->getDomainParticlePhaseHost(x, v);
simulatee.phase.num = x.size();
cout << "initial particle number: " << x.size() << endl;
#pragma region gl_interpo_init
swVBOs::getInstance().enroll("pbf_particle");
glBindBuffer(GL_ARRAY_BUFFER, swVBOs::getInstance().findVBO("pbf_particle"));
glBufferData(GL_ARRAY_BUFFER, x.size() * sizeof(glm::vec3), x.data(), GL_STATIC_DRAW);
gpuErrchk(cudaDeviceSynchronize());
cudaGraphicsGLRegisterBuffer(&cu_res, swVBOs::getInstance().findVBO("pbf_particle"), cudaGraphicsMapFlagsNone);
#ifndef NDEBUG
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaDeviceSynchronize());
#endif
// modify particles data
cudaFree(simulatee.phase.x);
cudaMemcpy(simulatee.phase.v, v.data(), v.size() * sizeof(dom_dim), cudaMemcpyHostToDevice);
#pragma endregion
}
void oskar_device_check_error(int* status)
{
if (*status) return;
#ifdef OSKAR_HAVE_CUDA
*status = (int) cudaPeekAtLastError();
#endif
}
void pbf_dam_sim::simulateOneStep()
{
//simulatee.external.body_force
cudaGraphicsMapResources(1, &cu_res);
#ifndef NDEBUG
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaDeviceSynchronize());
#endif
size_t pos_size;
cudaGraphicsResourceGetMappedPointer((void**)&simulatee.phase.x, &pos_size, cu_res);
#ifndef NDEBUG
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaDeviceSynchronize());
#endif
one_step(simulatee, buffer, domain, 3);
cudaGraphicsUnmapResources(1, &cu_res);
simulatee.phase.x = NULL;
}
int main() {
// Initialize variables
double *h_u; h_u = (double*)malloc(sizeof(double)*(NX*NY*NZ));
// Set Domain Initial Condition and BCs
Call_IC(h_u);
// GPU Memory Arrays
double *d_u; checkCuda(cudaMalloc((void**)&d_u, sizeof(double)*(NX*NY)));
double *d_un; checkCuda(cudaMalloc((void**)&d_un,sizeof(double)*(NX*NY)));
// Copy Initial Condition from host to device
checkCuda(cudaMemcpy(d_u, h_u,sizeof(double)*(NX*NY),cudaMemcpyHostToDevice));
checkCuda(cudaMemcpy(d_un,h_u,sizeof(double)*(NX*NY),cudaMemcpyHostToDevice));
// GPU kernel launch parameters
dim3 dimBlock(BLOCK_SIZE_X, BLOCK_SIZE_Y, BLOCK_SIZE_Z);
dim3 dimGrid (DIVIDE_INTO(NX, BLOCK_SIZE_X), DIVIDE_INTO(NY, BLOCK_SIZE_Y), DIVIDE_INTO(NZ, BLOCK_SIZE_Z));
// Request computer current time
time_t t = clock();
// Solver Loop
for (int step=0; step < NO_STEPS; step+=2) {
if (step%10000==0) printf("Step %d of %d\n",step,(int)NO_STEPS);
// Compute Laplace
Call_Laplace(dimGrid,dimBlock,d_u,d_un);
// Call_Laplace_Texture(dimGrid,dimBlock,d_u,d_un);
}
if (DEBUG) printf("CUDA error (Jacobi_Method) %s\n",cudaGetErrorString(cudaPeekAtLastError()));
// Measure and Report computation time
t = clock()-t; printf("Computing time (%f seconds).\n",((float)t)/CLOCKS_PER_SEC);
// Copy data from device to host
checkCuda(cudaMemcpy(h_u,d_u,sizeof(double)*(NX*NY*NZ),cudaMemcpyDeviceToHost));
// uncomment to print solution to terminal
if (DEBUG) Print2D(h_u);
// Write solution to file
Save_Results(h_u);
// Free device memory
checkCuda(cudaFree(d_u));
checkCuda(cudaFree(d_un));
// Reset device
checkCuda(cudaDeviceReset());
// Free memory on host and device
free(h_u);
return 0;
}
void cuda_random(float *x_gpu, size_t n)
{
static curandGenerator_t gen;
static int init = 0;
if(!init){
curandCreateGenerator(&gen, CURAND_RNG_PSEUDO_DEFAULT);
curandSetPseudoRandomGeneratorSeed(gen, time(0));
init = 1;
}
curandGenerateUniform(gen, x_gpu, n);
check_error(cudaPeekAtLastError());
}
void cuda_random(float *x_gpu, size_t n) {
static curandGenerator_t gen[16];
static int init[16] = { 0 };
int i = cuda_get_device();
if (!init[i]) {
curandCreateGenerator(&gen[i], CURAND_RNG_PSEUDO_DEFAULT);
curandSetPseudoRandomGeneratorSeed(gen[i], time(0));
init[i] = 1;
}
curandGenerateUniform(gen[i], x_gpu, n);
check_error(cudaPeekAtLastError());
}
void cudaCheck(const int line, const std::string& function, const std::string& file)
{
try
{
#ifdef USE_CUDA
const auto errorCode = cudaPeekAtLastError();
if(errorCode != cudaSuccess)
error("Cuda check failed (" + std::to_string(errorCode) + " vs. " + std::to_string(cudaSuccess) + "): "
+ cudaGetErrorString(errorCode), line, function, file);
#else
UNUSED(line);
UNUSED(function);
UNUSED(file);
error("OpenPose must be compiled with the `USE_CUDA` macro definition in order to use this"
" functionality.", __LINE__, __FUNCTION__, __FILE__);
#endif
}
catch (const std::exception& e)
{
error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
}
extern inline void _cudaCheckError(const char *file, const int line) {
#ifndef NDEBUG
cudaDeviceSynchronize();
#endif
cudaError_t ret = cudaPeekAtLastError();
if (ret != cudaSuccess) {
fprintf(stderr, "cudaCheckError() failed at %s:%i: %s\n", file, line,
cudaGetErrorString(cudaGetLastError()));
#ifndef NDEBUG
switch (ret) {
case cudaErrorMissingConfiguration:
fprintf(stderr, "Error type: cudaErrorMissingConfiguration\n");
fprintf(stderr, "Missing configuration error.\n");
break;
case cudaErrorMemoryAllocation:
fprintf(stderr, "Error type: cudaErrorMemoryAllocation\n");
fprintf(stderr, "Memory allocation error.\n");
break;
case cudaErrorInitializationError:
fprintf(stderr, "Error type: cudaErrorInitializationError\n");
fprintf(stderr, "Initialization error.\n");
break;
case cudaErrorLaunchFailure:
fprintf(stderr, "Error type: cudaErrorLaunchFailure\n");
fprintf(stderr, "Launch failure.\n");
break;
case cudaErrorPriorLaunchFailure:
fprintf(stderr, "Error type: cudaErrorPriorLaunchFailure\n");
fprintf(stderr, "Prior launch failure.\n");
break;
case cudaErrorLaunchTimeout:
fprintf(stderr, "Error type: cudaErrorLaunchTimeout\n");
fprintf(stderr, "Launch timeout error.\n");
break;
case cudaErrorLaunchOutOfResources:
fprintf(stderr, "Error type: cudaErrorLaunchOutOfResources\n");
fprintf(stderr, "Launch out of resources error.\n");
break;
case cudaErrorInvalidDeviceFunction:
fprintf(stderr, "Error type: cudaErrorInvalidDeviceFunction\n");
fprintf(stderr, "Invalid device function.\n");
break;
case cudaErrorInvalidConfiguration:
fprintf(stderr, "Error type: cudaErrorInvalidConfiguration\n");
fprintf(stderr, "Invalid configuration.\n");
break;
case cudaErrorInvalidDevice:
fprintf(stderr, "Error type: cudaErrorInvalidDevice\n");
fprintf(stderr, "Invalid device.\n");
break;
case cudaErrorInvalidValue:
fprintf(stderr, "Error type: cudaErrorInvalidValue\n");
fprintf(stderr, "Invalid value.\n");
break;
case cudaErrorInvalidPitchValue:
fprintf(stderr, "Error type: cudaErrorInvalidPitchValue\n");
fprintf(stderr, "Invalid pitch value.\n");
break;
case cudaErrorInvalidSymbol:
fprintf(stderr, "Error type: cudaErrorInvalidSymbol\n");
fprintf(stderr, "Invalid symbol.\n");
break;
case cudaErrorMapBufferObjectFailed:
fprintf(stderr, "Error type: cudaErrorMapBufferObjectFailed\n");
fprintf(stderr, "Map buffer object failed.\n");
break;
case cudaErrorUnmapBufferObjectFailed:
fprintf(stderr, "Error type: cudaErrorUnmapBufferObjectFailed\n");
fprintf(stderr, "Unmap buffer object failed.\n");
break;
case cudaErrorInvalidHostPointer:
fprintf(stderr, "Error type: cudaErrorInvalidHostPointer\n");
fprintf(stderr, "Invalid host pointer.\n");
break;
case cudaErrorInvalidDevicePointer:
fprintf(stderr, "Error type: cudaErrorInvalidDevicePointer\n");
fprintf(stderr, "Invalid device pointer.\n");
break;
case cudaErrorInvalidTexture:
fprintf(stderr, "Error type: cudaErrorInvalidTexture\n");
fprintf(stderr, "Invalid device pointer.\n");
break;
case cudaErrorInvalidTextureBinding:
fprintf(stderr, "Error type: cudaErrorInvalidTextureBinding\n");
fprintf(stderr, "Invalid texture binding.\n");
break;
case cudaErrorInvalidChannelDescriptor:
fprintf(stderr, "Error type: cudaErrorInvalidChannelDescriptor\n");
fprintf(stderr, "Invalid channel descriptor.\n");
break;
case cudaErrorInvalidMemcpyDirection:
fprintf(stderr, "Error type: cudaErrorInvalidMemcpyDirection\n");
fprintf(stderr, "Invalid memcpy direction.\n");
break;
case cudaErrorAddressOfConstant:
fprintf(stderr, "Error type: cudaErrorAddressOfConstant\n");
fprintf(stderr, "Address of constant error.\n");
break;
case cudaErrorTextureFetchFailed:
fprintf(stderr, "Error type: cudaErrorTextureFetchFailed\n");
fprintf(stderr, "Texture fetch failed.\n");
break;
case cudaErrorTextureNotBound:
fprintf(stderr, "Error type: cudaErrorTextureNotBound\n");
fprintf(stderr, "Texture not bound error.\n");
break;
case cudaErrorSynchronizationError:
fprintf(stderr, "Error type: cudaErrorSynchronizationError\n");
fprintf(stderr, "Synchronization error.\n");
break;
case cudaErrorInvalidFilterSetting:
fprintf(stderr, "Error type: cudaErrorInvalidFilterSetting\n");
fprintf(stderr, "Invalid filter setting.\n");
break;
case cudaErrorInvalidNormSetting:
fprintf(stderr, "Error type: cudaErrorInvalidNormSetting\n");
fprintf(stderr, "Invalid norm setting.\n");
break;
case cudaErrorCudartUnloading:
fprintf(stderr, "Error type: cudaErrorCudartUnloading\n");
fprintf(stderr, "CUDA runtime unloading.\n");
break;
case cudaErrorUnknown:
fprintf(stderr, "Error type: cudaErrorUnknown\n");
fprintf(stderr, "Unknown error condition.\n");
break;
case cudaErrorNotYetImplemented:
fprintf(stderr, "Error type: cudaErrorNotYetImplemented\n");
fprintf(stderr, "Function not yet implemented.\n");
break;
case cudaErrorMemoryValueTooLarge:
fprintf(stderr, "Error type: cudaErrorMemoryValueTooLarge\n");
fprintf(stderr, "Memory value too large.\n");
break;
case cudaErrorInvalidResourceHandle:
fprintf(stderr, "Error type: cudaErrorInvalidResourceHandle\n");
fprintf(stderr, "Invalid resource handle.\n");
break;
case cudaErrorNotReady:
fprintf(stderr, "Error type: cudaErrorNotReady\n");
fprintf(stderr, "Not ready error.\n");
break;
case cudaErrorInsufficientDriver:
fprintf(stderr, "Error type: cudaErrorInsufficientDriver\n");
fprintf(stderr, "CUDA runtime is newer than driver.\n");
break;
case cudaErrorSetOnActiveProcess:
fprintf(stderr, "Error type: cudaErrorSetOnActiveProcess\n");
fprintf(stderr, "Set on active process error.\n");
break;
case cudaErrorNoDevice:
fprintf(stderr, "Error type: cudaErrorNoDevice\n");
fprintf(stderr, "No available CUDA device.\n");
break;
}
#endif
cudaDeviceReset();
exit(EXIT_FAILURE);
}
}
void checkCudaError(int line) {
checkCudaError(line, cudaPeekAtLastError());
}
/**
* This function does what it says on the tin.
*/
void OptiXRenderer::performRender(long long int photons, int argc_mpi, char* argv_mpi[], int width, int height, float film_location) {
// Keep track of time
timeval tic;
// Create OptiX context
optix::Context context = optix::Context::create();
context->setRayTypeCount( 1 );
// Debug, this will make everything SLOOOOOW
context->setPrintEnabled(false);
// Set some CUDA flags
cudaSetDeviceFlags(cudaDeviceMapHost | cudaDeviceLmemResizeToMax);
// Set used devices
int tmp[] = { 0, 1 };
std::vector<int> v( tmp, tmp+2 );
context->setDevices(v.begin(), v.end());
// Report device usage
int num_devices = context->getEnabledDeviceCount();
printf("Using %d devices:\n", num_devices);
std::vector<int> enabled_devices = context->getEnabledDevices();
for(int i=0;i<num_devices;i++) {
printf(" Device #%d [%s]\n", enabled_devices[i], context->getDeviceName(enabled_devices[i]).c_str());
}
// Set some OptiX variables
context->setStackSize(4096);
// Report OptiX infomation
int stack_size_in_bytes = context->getStackSize();
printf("Optix stack size is %d bytes (~%d KB).\n.", stack_size_in_bytes, stack_size_in_bytes/1024);
// Declare some variables
int threads = 500000; //20000000;
unsigned int iterations_on_device = 1;
// Set some scene-wide variables
context["photon_ray_type"]->setUint( 0u );
context["scene_bounce_limit"]->setUint( 10u );
context["scene_epsilon"]->setFloat( 1.e-4f );
context["iterations"]->setUint(iterations_on_device);
context["follow_photon"]->setInt(66752);
// Convert our existing scene into an OptiX one
convertToOptiXScene(context, width, height, film_location);
// Report infomation
printf("Rendering with:\n");
printf(" %lld photons.\n", photons);
printf(" %d threads.\n", threads);
printf(" %d iterations per thread.\n", iterations_on_device);
int launches = (photons/threads)/iterations_on_device;
if(launches*threads*iterations_on_device<photons) {
launches++;
printf(" NOTE: You have asked for %lld photons, we are providing %lld photons instead.\n", photons, launches*threads*iterations_on_device);
}
printf(" %d optix launches.\n", launches);
// Create buffer for random numbers
optix::Buffer random_buffer = context->createBufferForCUDA( RT_BUFFER_INPUT_OUTPUT | RT_BUFFER_GPU_LOCAL, RT_FORMAT_USER, threads );
random_buffer->setElementSize(sizeof(curandState));
curandState* states_ptr[num_devices];
// Intalise
for(int i=0;i<num_devices;i++) {
int device_id = enabled_devices[i];
long memory_in_bytes = threads * sizeof(curandState);
long memory_in_megabytes = memory_in_bytes/(1024*1024);
printf("Allocating %ld bytes (~%ld MB) of memory on device #%d for random states...\n", memory_in_bytes, memory_in_megabytes, device_id);
gettimeofday(&tic, NULL);
cudaSetDevice(device_id);
cudaMalloc((void **)&states_ptr[i], memory_in_bytes);
done(tic);
CUDAWrapper executer;
executer.curand_setup(threads, (void **)&states_ptr[i], time(NULL), i);
}
// Set as buffer on context
context["states"]->set(random_buffer);
// Wait
printf("Waiting for random states to initalise...\n");
gettimeofday(&tic, NULL);
for(int i=0;i<num_devices;i++) {
cudaSetDevice(enabled_devices[i]);
sync_all_threads();
}
done(tic);
// Bind to the OptiX buffer
// We do this here because it cases a syncronise apparently
for(int i=0;i<num_devices;i++) {
random_buffer->setDevicePointer(enabled_devices[i], (CUdeviceptr) states_ptr[i]);
}
// Create Image buffer
optix::Buffer buffer = context->createBufferForCUDA( RT_BUFFER_INPUT_OUTPUT | RT_BUFFER_GPU_LOCAL, RT_FORMAT_FLOAT4, width, height );
optix::float4* imgs_ptr[num_devices];
//cudaSetDevice(0);
//cudaMalloc((void **)&states_ptr_0, threads * sizeof(curandState));
for(int i=0;i<num_devices;i++) {
int device_id = enabled_devices[i];
long memory_in_bytes = width * height * sizeof(optix::float4);
long memory_in_megabytes = memory_in_bytes/(1024*1024);
printf("Allocating %ld bytes (~%ld MB) of memory on device #%d for image result...\n", memory_in_bytes, memory_in_megabytes, device_id);
gettimeofday(&tic, NULL);
cudaSetDevice(device_id);
cudaMalloc((void **)&imgs_ptr[i], memory_in_bytes);
done(tic);
CUDAWrapper executer;
executer.img_setup((void **)&imgs_ptr[i], width, height);
}
// Set as buffer on context
context["output_buffer"]->set(buffer);
// Wait for everytyhing to execute
printf("Waiting for Image data to initalise...\n");
gettimeofday(&tic, NULL);
for(int i=0;i<num_devices;i++) {
cudaSetDevice(enabled_devices[i]);
sync_all_threads();
}
done(tic);
// Bind to the OptiX buffer
// We do this here because it cases a syncronise apparently
for(int i=0;i<num_devices;i++) {
buffer->setDevicePointer(enabled_devices[i], (CUdeviceptr) imgs_ptr[i]);
}
// Construct MPI
int size, rank = 0;
#ifndef PHOTON_MPI
(void)size;
(void)argc_mpi;
(void)argv_mpi;
#endif
#ifdef PHOTON_MPI
MPI::Init( argc_mpi, argv_mpi );
//MPI_Get_processor_name(hostname,&strlen);
rank = MPI::COMM_WORLD.Get_rank();
size = MPI::COMM_WORLD.Get_size();
printf("Hello, world; from process %d of %d\n", rank, size);
// Adjust number of photons for MPI
long long int long_size = (long long int) size;
photons = photons/long_size;
if(rank==0) printf("MPI adjusted to %lld photons per thread", photons);
#endif /* MPI */
// Validate
try{
context->validate();
}catch(Exception& e){
printf("Validate error!\n");
printf(" CUDA says : %s\n", cudaGetErrorString(cudaPeekAtLastError()));
printf(" OptiX says : %s\n", e.getErrorString().c_str() );
return;
}
// Compile context
try{
context->compile();
}catch(Exception& e){
printf("Compile error!\n");
printf(" CUDA says : %s\n", cudaGetErrorString(cudaPeekAtLastError()));
printf(" OptiX says : %s\n", e.getErrorString().c_str() );
return;
}
// Render
int current_launch = 0;
try{
printf("Begin render...\n");
gettimeofday(&tic, NULL);
for(current_launch=0;current_launch<launches;current_launch++) {
printf(" ... %f percent\n", 100*((current_launch*1.0f*threads)/photons));
context->launch(0 , threads );
}
done(tic);
}catch(Exception& e){
printf("Launch error on launch #%d!\n", current_launch);
printf(" CUDA says : %s\n", cudaGetErrorString(cudaPeekAtLastError()));
printf(" OptiX says : %s\n", e.getErrorString().c_str() );
return;
}
#ifndef PHOTON_MPI
#endif /* If not MPI */
#ifdef PHOTON_MPI
// Create MPI handles
accImg = new Image(img->getWidth(), img->getHeight());
MPI::Win window_r;
MPI::Win window_g;
MPI::Win window_b;
// Construct an MPI Window to copy some data into, one for each colour.
int size_in_bytes = sizeof(float)*img->getWidth()*img->getHeight();
window_r = MPI::Win::Create(accImg->imageR, size_in_bytes, sizeof(float), MPI_INFO_NULL, MPI_COMM_WORLD);
window_g = MPI::Win::Create(accImg->imageG, size_in_bytes, sizeof(float), MPI_INFO_NULL, MPI_COMM_WORLD);
window_b = MPI::Win::Create(accImg->imageB, size_in_bytes, sizeof(float), MPI_INFO_NULL, MPI_COMM_WORLD);
// Perform transfer
window_r.Fence(0);
window_g.Fence(0);
window_b.Fence(0);
window_r.Accumulate(
img->imageR,
img->getWidth()*img->getHeight(),
MPI_FLOAT,
0,
0,
img->getWidth()*img->getHeight(),
MPI_FLOAT,
MPI_SUM
);
window_g.Accumulate(
img->imageG,
img->getWidth()*img->getHeight(),
MPI_FLOAT,
0,
0,
img->getWidth()*img->getHeight(),
MPI_FLOAT,
MPI_SUM
);
window_b.Accumulate(
img->imageB,
img->getWidth()*img->getHeight(),
MPI_FLOAT,
0,
0,
img->getWidth()*img->getHeight(),
MPI_FLOAT,
MPI_SUM
);
window_r.Fence(0);
window_g.Fence(0);
window_b.Fence(0);
window_r.Free();
#endif /* MPI */
// Output the image
if(rank==0) {
// Construct filename
char sbuffer[100];
sprintf(sbuffer, "photons-%d.ppm", 0);
// This is the collected image data on the host
optix::float4* img_host_ptr = (optix::float4*) malloc(width*height*sizeof(optix::float4));
// If we have more than one device we have to accumulate everything back into one buffer
if(num_devices == 1) {
img_host_ptr = (optix::float4*) malloc(width*height*sizeof(optix::float4));
cudaMemcpy(img_host_ptr, imgs_ptr[0], width*height*sizeof(optix::float4), cudaMemcpyDeviceToHost);
} else {
printf("We are using %d GPUs, accumulating result...", num_devices);
gettimeofday(&tic, NULL);
// Create an accumulate buffer on GPU #0#
// int device_id = enabled_devices[0];
// cudaSetDevice(device_id);
// optix::float4* accumulate_dev_ptr;
// cudaMalloc((void **)&accumulate_dev_ptr, width*height*sizeof(optix::float4));
// // put the array of memory ptrs on device 0
// optix::float4** ptrs_dev_ptr;
// cudaMalloc((void **)&ptrs_dev_ptr, num_devices*sizeof(optix::float4*));
// // Copy data over
// cudaMemcpy(ptrs_dev_ptr, imgs_ptr, num_devices*sizeof(optix::float4*), cudaMemcpyHostToDevice);
// CUDAWrapper executer;
// executer.img_accumulate((void ***)&ptrs_dev_ptr, (void **)&accumulate_dev_ptr, num_devices, width, height);
// cudaMemcpy(img_host_ptr, accumulate_dev_ptr, width*height*sizeof(optix::float4), cudaMemcpyDeviceToHost);
// Copy everything to host and accumulate here
optix::float4* host_buffers[num_devices];
for(int i=0;i<num_devices;i++) {
host_buffers[i] = (optix::float4*) malloc(width*height*sizeof(optix::float4));
cudaMemcpy(host_buffers[i], imgs_ptr[i], width*height*sizeof(optix::float4), cudaMemcpyDeviceToHost);
}
// Acumulate
for(int i=0;i<width*height;i++) {
img_host_ptr[i] = make_float4(0, 0, 0, 0);
for(int j=0;j<num_devices;j++) {
img_host_ptr[i].x += host_buffers[j][i].x;
img_host_ptr[i].y += host_buffers[j][i].y;
img_host_ptr[i].z += host_buffers[j][i].z;
img_host_ptr[i].w += host_buffers[j][i].w;
}
}
for(int i=0;i<num_devices;i++) {
free(host_buffers[i]);
}
done(tic);
}
printf("Saving Image to %s...\n", sbuffer);
gettimeofday(&tic, NULL);
saveToPPMFile(sbuffer, img_host_ptr, width, height);
free(img_host_ptr);
done(tic);
}
#ifdef PHOTON_MPI
// Teardown MPI
MPI::Finalize();
#endif /* MPI */
}
/*===========================================================================*/
cudaError_t PeekAtLastError()
{
return cudaPeekAtLastError();
}
void _cudaCheck(const char* file, int line)
{
_cudaAssert(cudaPeekAtLastError(), file, line);
}
void cuda_check_last_error()
{
check_cuda_error( cudaPeekAtLastError());
}
