unsigned int GPUInterface::GetAvailableMemory() {
#if CUDA_VERSION >= 3020
size_t availableMem = 0;
size_t totalMem = 0;
SAFE_CUPP(cuMemGetInfo(&availableMem, &totalMem));
#else
unsigned int availableMem = 0;
unsigned int totalMem = 0;
SAFE_CUPP(cuMemGetInfo(&availableMem, &totalMem));
#endif
return availableMem;
}
int main() {
int ngpu;
CUdevice cuDevice;
CUcontext cuContext;
cuInit(0);
cuDeviceGetCount(&ngpu);
//printf("ngpu = %d\n", ngpu);
size_t *totals, *frees ;
totals = (size_t *) calloc (ngpu, sizeof(size_t));
frees = (size_t *) calloc (ngpu, sizeof(size_t));
int tid;
omp_set_num_threads(ngpu);
#pragma omp parallel private(tid, cuDevice, cuContext) shared(frees, totals)
{
tid = omp_get_thread_num();
//printf("nthreads = %d, tid = %d\n", omp_get_num_threads(), tid);
cuDeviceGet(&cuDevice, tid);
cuCtxCreate(&cuContext, tid, cuDevice);
cuMemGetInfo((size_t*)&frees[tid], (size_t*)&totals[tid]);
}
printf ("\ttotal\t\tfree\t\tused\n");
for(int i=0; i<ngpu; i++) {
printf("GPU %d\t%lu\t%lu\t%lu\n", i, (size_t)totals[i], (size_t)frees[i], (size_t)totals[i]-(size_t)frees[i]);
}
return 0;
}
size_t initContext(JNIEnv * env, jint max_blocks_per_proc, jint max_threads_per_block)
{
size_t to_space_size;
int status;
int deviceCount = 0;
size_t f_mem;
size_t t_mem;
jint num_blocks;
status = cuDeviceGetCount(&deviceCount);
CHECK_STATUS_RTN(env,"error in cuDeviceGetCount",status, 0);
getBestDevice(env);
status = cuCtxCreate(&cuContext, CU_CTX_MAP_HOST, cuDevice);
CHECK_STATUS_RTN(env,"error in cuCtxCreate",status, 0)
status = cuMemGetInfo (&f_mem, &t_mem);
CHECK_STATUS_RTN(env,"error in cuMemGetInfo",status, 0)
to_space_size = f_mem;
//space for 100 types in the scene
classMemSize = sizeof(jint)*100;
num_blocks = numMultiProcessors * max_threads_per_block * max_blocks_per_proc;
gc_space_size = 1024;
to_space_size -= (num_blocks * sizeof(jlong));
to_space_size -= (num_blocks * sizeof(jlong));
to_space_size -= gc_space_size;
to_space_size -= classMemSize;
return to_space_size;
}
candidate*
immaculate_conception (CUZMEM_CONTEXT ctx)
{
unsigned long long DNA;
unsigned int loc, gpu_mem_free, gpu_mem_total, gpu_mem_req;
unsigned int creating = 1;
cuzmem_plan* entry = ctx->plan;
candidate* c = (candidate*)malloc (sizeof(candidate));
cuMemGetInfo (&gpu_mem_free, &gpu_mem_total);
while (creating) {
c->DNA = rand();
c->DNA = c->DNA << 32;
c->DNA = c->DNA + rand();
c->DNA &= generate_mask(ctx->num_knobs);
// gpu memory utilization
gpu_mem_req = 0;
entry = ctx->plan;
while (entry != NULL) {
if (entry->gold_member) {
loc = (c->DNA >> entry->id) & 0x0001;
gpu_mem_req += entry->size * loc;
}
entry = entry->next;
}
// check constraint
if (gpu_mem_req > gpu_mem_free * MIN_GPU_MEM) {
creating = 0;
}
}
int main(int argc, char* argv[])
{
cuInit(0);
int devs = 0;
cuDeviceGetCount(&devs);
assert(devs > 0);
CUdevice dev;
CUresult status;
CUcontext ctx = 0;
cuDeviceGet(&dev, 0);
cuCtxCreate(&ctx, 0, dev);
{
size_t f = 0, t = 0;
CUresult r = cuMemGetInfo(&f, &t);
fprintf( stderr, "Do cuMemGetInfo: %d, %zu/%zu\n", r, f, t );
}
__init("\n");
printf("\nPress any key to exit...");
char c;
scanf("%c", &c);
return 0;
}
/* ========================================================================== */
int sci_gpuDeviceMemInfo(char *fname)
{
#ifdef WITH_CUDA
if(isGpuInit())
{
if (useCuda())
{
size_t free = 0, total = 0;
cuMemGetInfo(&free,&total);
double freeMem = (double)free;
createScalarDouble(pvApiCtx, Rhs + 1, freeMem);
}
else
{
double zero = 0.;
createScalarDouble(pvApiCtx, Rhs + 1, zero);
sciprint("not implemented with OpenCL.\n");
}
LhsVar(1) = Rhs + 1;
PutLhsVar();
}
else
{
Scierror(999,"%s","gpu is not initialised. Please launch gpuInit() before use this function.\n");
}
#else
sciprint("not implemented with OpenCL.\n");
#endif
return 0;
}
size_t swanMemAvailable( void ) {
size_t free, total;
try_init();
cuMemGetInfo( &free, &total );
return free;
}
void checkCUDAmemory(char* t) {
//cudaDeviceSynchronize();
size_t free, total;
cuMemGetInfo(&free, &total);
fprintf(stderr,"%s mem %ld total %ld\n", t, free / 1024 / 1024, total / 1024 / 1024);
}
/**
* Returns the memory usage statistics.
*
* @param usedMem receives the current used memory.
* @param totalMem receives the total memory of the device.
*/
void getMemoryUsage(size_t* usedMem, size_t* totalMem) {
size_t myFreeMem;
size_t myTotalMem;
cudaFree(0); // Ensures the CUDA context creation. Otherwise cuMemGetInfo (driver API) will return zero.
cuMemGetInfo(&myFreeMem, &myTotalMem);
if (usedMem != NULL) {
*usedMem = myTotalMem-myFreeMem;
}
if (totalMem != NULL) {
*totalMem = myTotalMem;
}
}
S64 CudaModule::getMemoryUsed(void)
{
staticInit();
if (!s_available) {
return 0;
}
size_t free = 0;
size_t total = 0;
cuMemGetInfo(&free, &total);
return total - free;
}
int main(int argc, char *argv[])
{
char c;
CUcontext ctx;
CUdevice dev = 0;
void *toSpace;
int status, free, total;
CUdeviceptr ptr = (CUdeviceptr)NULL;
int size;
if(argc != 2){
fprintf(stderr,"Usage: mem_alloc.exe [MEMORY TO ALLOCATE IN MB]\n");
exit(1);
}
printf("All status results should be 0, if not an error has occured.\nIf 2 is reported an out of memory error has occured for\nwhich you should decrease the memory input\n");
size = atoi(argv[1]);
printf("\nTrying to allocate %iMB of memory on host and GPU\n",size);
if(size <= 0){
fprintf(stderr,"\nERROR: Memory must be greater than 0\n");
exit(1);
}
status = cuInit(0);
printf("Init status: %i\n",status);
status = cuCtxCreate(&ctx, 0, dev);
printf("Context creation status: %i\n",status);
cuMemGetInfo(&free, &total);
printf("Get memory info status: %i\n",status);
printf("\n%.1f/%.1f (Free/Total) MB\n", free/1024.0/1024.0, total/1024.0/1024.0);
status = cuMemHostAlloc(&toSpace, size*1024*1024, 0);
printf("Host allocation status: %i %s\n",status, (status==CUDA_SUCCESS) ? "SUCCESS" : "FAILED");
status = cuMemAlloc(&ptr, size*1024*1024);
printf("GPU allocation status: %i %s\n",status, (status==CUDA_SUCCESS) ? "SUCCESS" : "FAILED");
printf("\nPress any key to exit...");
scanf("%c", &c);
status = cuCtxDestroy(ctx);
printf("Context destroy status: %i\n",status);
return 0;
}
/*===========================================================================*/
void Device::update()
{
kvs::cuda::DriverAPI::Context context( *this );
#if defined( cuMemGetInfo )
/* In this case, the function 'cuMemGetInfo' is defined to 'cuMemGetInfo_v2'
* as "#define cuMemGetInfo cuMemGetInfo_v2". And then, the function
* 'cuMemGetInfo_v2' is defined as follows:
* CUresult cuMemGetInfo_v2( size_t * free, size_t * total )
*/
KVS_CU_CALL( cuMemGetInfo( &m_free_memory, &m_total_memory ) );
#else
/* The function 'cuMemGetInfo' is defined as follows:
* CUresult cuMemGetInfo( unsigned int * free, unsigned int * total )
* Therefore, the temporary parameters defined as unsigned int are used
* to obtain the memory information.
*/
unsigned int free_memory = 0;
unsigned int total_memory = 0;
KVS_CU_CALL( cuMemGetInfo( &free_memory, &total_memory ) );
m_free_memory = static_cast<size_t>( free_memory );
m_total_memory = static_cast<size_t>( total_memory );
#endif
}
SEXP
R_auto_cuMemGetInfo()
{
SEXP r_ans = R_NilValue;
size_t free;
size_t total;
CUresult ans;
ans = cuMemGetInfo(& free, & total);
if(ans)
return(R_cudaErrorInfo(ans));
PROTECT(r_ans = NEW_LIST(2));
SEXP r_names;
PROTECT(r_names = NEW_CHARACTER(2));
SET_VECTOR_ELT(r_ans, 0, ScalarReal(free));
SET_VECTOR_ELT(r_ans, 1, ScalarReal(total));
SET_STRING_ELT(r_names, 0, mkChar("free"));
SET_STRING_ELT(r_names, 1, mkChar("total"));
SET_NAMES(r_ans, r_names);
UNPROTECT(2);
return(r_ans);
}
static int cuda_property(void *c, gpudata *buf, gpukernel *k, int prop_id,
void *res) {
cuda_context *ctx = NULL;
if (c != NULL) {
ctx = (cuda_context *)c;
ASSERT_CTX(ctx);
} else if (buf != NULL) {
ASSERT_BUF(buf);
ctx = buf->ctx;
} else if (k != NULL) {
ASSERT_KER(k);
ctx = k->ctx;
}
/* I know that 512 and 1024 are magic numbers.
There is an indication in buffer.h, though. */
if (prop_id < 512) {
if (ctx == NULL)
return GA_VALUE_ERROR;
} else if (prop_id < 1024) {
if (buf == NULL)
return GA_VALUE_ERROR;
} else {
if (k == NULL)
return GA_VALUE_ERROR;
}
switch (prop_id) {
char *s;
CUdevice id;
int i;
size_t sz;
case GA_CTX_PROP_DEVNAME:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
/* 256 is what the CUDA API uses so it's good enough for me */
s = malloc(256);
if (s == NULL) {
cuda_exit(ctx);
return GA_MEMORY_ERROR;
}
ctx->err = cuDeviceGetName(s, 256, id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((char **)res) = s;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_MAXLSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((size_t *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_LMEMSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((size_t *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_NUMPROCS:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((unsigned int *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_MAXGSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((size_t *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_BLAS_OPS:
#ifdef WITH_CUDA_CUBLAS
*((gpuarray_blas_ops **)res) = &cublas_ops;
return GA_NO_ERROR;
#else
*((void **)res) = NULL;
return GA_DEVSUP_ERROR;
#endif
case GA_CTX_PROP_BIN_ID:
*((const char **)res) = ctx->bin_id;
return GA_NO_ERROR;
case GA_CTX_PROP_ERRBUF:
*((gpudata **)res) = ctx->errbuf;
return GA_NO_ERROR;
case GA_CTX_PROP_TOTAL_GMEM:
cuda_enter(ctx);
ctx->err = cuMemGetInfo(&sz, (size_t *)res);
cuda_exit(ctx);
return ctx->err == CUDA_SUCCESS ? GA_NO_ERROR : GA_IMPL_ERROR;
case GA_CTX_PROP_FREE_GMEM:
cuda_enter(ctx);
ctx->err = cuMemGetInfo((size_t *)res, &sz);
cuda_exit(ctx);
return ctx->err == CUDA_SUCCESS ? GA_NO_ERROR : GA_IMPL_ERROR;
case GA_BUFFER_PROP_REFCNT:
*((unsigned int *)res) = buf->refcnt;
return GA_NO_ERROR;
case GA_BUFFER_PROP_SIZE:
*((size_t *)res) = buf->sz;
return GA_NO_ERROR;
case GA_BUFFER_PROP_CTX:
case GA_KERNEL_PROP_CTX:
*((void **)res) = (void *)ctx;
return GA_NO_ERROR;
case GA_KERNEL_PROP_MAXLSIZE:
cuda_enter(ctx);
ctx->err = cuFuncGetAttribute(&i,
CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK,
k->k);
cuda_exit(ctx);
if (ctx->err != CUDA_SUCCESS)
return GA_IMPL_ERROR;
*((size_t *)res) = i;
return GA_NO_ERROR;
case GA_KERNEL_PROP_PREFLSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_WARP_SIZE, id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
cuda_exit(ctx);
*((size_t *)res) = i;
return GA_NO_ERROR;
case GA_KERNEL_PROP_NUMARGS:
*((unsigned int *)res) = k->argcount;
return GA_NO_ERROR;
case GA_KERNEL_PROP_TYPES:
*((const int **)res) = k->types;
return GA_NO_ERROR;
default:
return GA_INVALID_ERROR;
}
}
void WaterPlaneCUDA::configure(Vector upperLeft, Vector lowerRight, float dampFactor, float resolution)
{
cudaSetDevice(cutGetMaxGflopsDeviceId());
cudaGLSetGLDevice(cutGetMaxGflopsDeviceId());
timeSinceLast = timePassed = 0;
unsigned int free, total;
int gpuCount, i;
CUresult res;
CUdevice dev;
CUcontext ctx;
cuInit(0);
cuDeviceGetCount(&gpuCount);
printf("Detected %d GPU\n",gpuCount);
for (i=0; i<gpuCount; i++)
{
cuDeviceGet(&dev,i);
cuCtxCreate(&ctx, 0, dev);
res = cuMemGetInfo(&free, &total);
if(res != CUDA_SUCCESS)
printf("!!!! cuMemGetInfo failed! (status = %x)", res);
printf("^^^^ Device: %d\n",i);
printf("^^^^ Free : %lu bytes (%lu KB) (%lu MB)\n", free, inKB(free), inMB(free));
printf("^^^^ Total: %lu bytes (%lu KB) (%lu MB)\n", total, inKB(total), inMB(total));
printf("^^^^ %f%% free, %f%% used\n", 100.0*free/(double)total, 100.0*(total - free)/(double)total);
cuCtxDetach(ctx);
}
this->stepSize = 1.0f/resolution;
this->resolutionFactor = resolution;
//reale Z - Achse ist x - Achse der WaterPlaneCUDA
this->sizeX = (unsigned int) abs(upperLeft.z - lowerRight.z);
//reale X -Achse ist y- Achse der WaterPlaneCUDA
this->sizeY = (unsigned int) abs(upperLeft.x - lowerRight.x);
//Anzahl der Netzpunkte in X -Richtung
this->pointsX = (unsigned int)(sizeX * resolution);
//Anzahl der Netzpunkte in Y -Richtung
pointsY = (unsigned int)(sizeY * resolution);
uLeft = upperLeft;
lRight = lowerRight;
//Der "Meeresspiegel"
baseHeight = lRight.y;
//Das Höhenfeld der WaterPlaneCUDA
waveMap = NULL;
initBuffer();
gpu_newVertices = new float3[pointsX*pointsY];
gpu_oldVertices = new float3[pointsX*pointsY];
gpu_normals = new float3[pointsX*pointsY];
for (int i=0;i<pointsX*pointsY;i++) {
gpu_newVertices[i]=make_float3(0,0,0);
gpu_oldVertices[i]=make_float3(0,0,0);
gpu_normals[i]=make_float3(0,1.0,0);
}
cutilSafeCall(cudaMalloc((void**)&gpu_newVertices,pointsX*pointsY*sizeof(float3)));
cutilSafeCall(cudaMalloc((void**)&gpu_oldVertices,pointsX*pointsY*sizeof(float3)));
cutilSafeCall(cudaMalloc((void**)&gpu_normals,pointsX*pointsY*sizeof(float3)));
drawMesh();
}
void
pocl_cuda_init (cl_device_id device, const char *parameters)
{
CUresult result;
result = cuInit (0);
CUDA_CHECK (result, "cuInit");
if (device->data)
return;
pocl_cuda_device_data_t *data = malloc (sizeof (pocl_cuda_device_data_t));
result = cuDeviceGet (&data->device, 0);
CUDA_CHECK (result, "cuDeviceGet");
// Get specific device name
device->long_name = device->short_name = malloc (256 * sizeof (char));
cuDeviceGetName (device->long_name, 256, data->device);
// Get other device properties
cuDeviceGetAttribute ((int *)&device->max_work_group_size,
CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK,
data->device);
cuDeviceGetAttribute ((int *)(device->max_work_item_sizes + 0),
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, data->device);
cuDeviceGetAttribute ((int *)(device->max_work_item_sizes + 1),
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, data->device);
cuDeviceGetAttribute ((int *)(device->max_work_item_sizes + 2),
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, data->device);
cuDeviceGetAttribute (
(int *)&device->local_mem_size,
CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR, data->device);
cuDeviceGetAttribute ((int *)&device->max_compute_units,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
data->device);
cuDeviceGetAttribute ((int *)&device->max_clock_frequency,
CU_DEVICE_ATTRIBUTE_CLOCK_RATE, data->device);
cuDeviceGetAttribute ((int *)&device->error_correction_support,
CU_DEVICE_ATTRIBUTE_ECC_ENABLED, data->device);
cuDeviceGetAttribute ((int *)&device->host_unified_memory,
CU_DEVICE_ATTRIBUTE_INTEGRATED, data->device);
cuDeviceGetAttribute ((int *)&device->max_constant_buffer_size,
CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY,
data->device);
device->preferred_vector_width_char = 1;
device->preferred_vector_width_short = 1;
device->preferred_vector_width_int = 1;
device->preferred_vector_width_long = 1;
device->preferred_vector_width_float = 1;
device->preferred_vector_width_double = 1;
device->preferred_vector_width_half = 0;
device->native_vector_width_char = 1;
device->native_vector_width_short = 1;
device->native_vector_width_int = 1;
device->native_vector_width_long = 1;
device->native_vector_width_float = 1;
device->native_vector_width_double = 1;
device->native_vector_width_half = 0;
device->single_fp_config = CL_FP_ROUND_TO_NEAREST | CL_FP_ROUND_TO_ZERO
| CL_FP_ROUND_TO_INF | CL_FP_FMA | CL_FP_INF_NAN
| CL_FP_DENORM;
device->double_fp_config = CL_FP_ROUND_TO_NEAREST | CL_FP_ROUND_TO_ZERO
| CL_FP_ROUND_TO_INF | CL_FP_FMA | CL_FP_INF_NAN
| CL_FP_DENORM;
device->local_mem_type = CL_LOCAL;
device->host_unified_memory = 0;
// Get GPU architecture name
int sm_maj, sm_min;
cuDeviceGetAttribute (&sm_maj, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR,
data->device);
cuDeviceGetAttribute (&sm_min, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR,
data->device);
char *gpu_arch = malloc (16 * sizeof (char));
snprintf (gpu_arch, 16, "sm_%d%d", sm_maj, sm_min);
device->llvm_cpu = pocl_get_string_option ("POCL_CUDA_GPU_ARCH", gpu_arch);
POCL_MSG_PRINT_INFO ("[CUDA] GPU architecture = %s\n", device->llvm_cpu);
// Create context
result = cuCtxCreate (&data->context, CU_CTX_MAP_HOST, data->device);
CUDA_CHECK (result, "cuCtxCreate");
// Get global memory size
size_t memfree, memtotal;
result = cuMemGetInfo (&memfree, &memtotal);
device->max_mem_alloc_size = max (memtotal / 4, 128 * 1024 * 1024);
device->global_mem_size = memtotal;
device->data = data;
}
/*
* Class: edu_syr_pcpratts_rootbeer_runtime2_cuda_CudaRuntime2
* Method: setup
* Signature: ()V
*/
JNIEXPORT void JNICALL Java_edu_syr_pcpratts_rootbeer_runtime2_cuda_CudaRuntime2_setup
(JNIEnv *env, jobject this_ref, jint max_blocks_per_proc, jint max_threads_per_block, jint free_space)
{
int status;
jint num_blocks;
int deviceCount = 0;
size_t f_mem;
size_t t_mem;
size_t to_space_size;
//size_t free_space = 1530L*1024L*1024L;
textureMemSize = 1;
status = cuInit(0);
if (CUDA_SUCCESS != status)
{
printf("error in cuInit\n");
}
status = cuDeviceGetCount(&deviceCount);
if (CUDA_SUCCESS != status)
{
printf("error in cuDeviceGet\n");
}
getBestDevice();
status = cuCtxCreate(&cuContext, CU_CTX_MAP_HOST, cuDevice);
if (CUDA_SUCCESS != status)
{
printf("error in cuCtxCreate %d\n", status);
}
// ddb - not using this as this returns the total memory not the free memory
//to_space_size = memSize();
cuMemGetInfo(&f_mem, &t_mem);
to_space_size = f_mem;
num_blocks = numMultiProcessors * max_threads_per_block * max_blocks_per_proc;
#if DEBUG
printf("Memory: %i(MB)/%i(MB) (Free/Total)\n",f_mem/1024/1024, t_mem/1024/1024);
printf("num_blocks = %i\n",num_blocks);
printf("numMultiProcessors = %i\n",numMultiProcessors);
printf("max_threads_per_block = %i\n",max_threads_per_block);
printf("max_blocks_per_proc = %i\n",max_blocks_per_proc);
fflush(stdout);
#endif
gc_space_size = 1024;
to_space_size -= (num_blocks * sizeof(jlong));
to_space_size -= (num_blocks * sizeof(jlong));
to_space_size -= gc_space_size;
to_space_size -= free_space;
//to_space_size -= textureMemSize;
bufferSize = to_space_size;
status = cuMemHostAlloc(&toSpace, to_space_size, 0);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "toSpace memory allocation failed", status);
return;
}
status = cuMemAlloc(&gpuToSpace, to_space_size);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "gpuToSpace memory allocation failed", status);
return;
}
/*
status = cuMemHostAlloc(&textureMemory, textureMemSize, 0);
if (CUDA_SUCCESS != status)
{
printf("error in cuMemHostAlloc textureMemory %d\n", status);
}
status = cuMemAlloc(&gpuTexture, textureMemSize);
if (CUDA_SUCCESS != status)
{
printf("error in cuMemAlloc gpuTexture %d\n", status);
}
*/
status = cuMemHostAlloc(&handlesMemory, num_blocks * sizeof(jlong), CU_MEMHOSTALLOC_WRITECOMBINED);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "handlesMemory memory allocation failed", status);
return;
}
status = cuMemAlloc(&gpuHandlesMemory, num_blocks * sizeof(jlong));
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "gpuHandlesMemory memory allocation failed", status);
return;
}
status = cuMemHostAlloc(&exceptionsMemory, num_blocks * sizeof(jlong), 0);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "exceptionsMemory memory allocation failed", status);
return;
}
status = cuMemAlloc(&gpuExceptionsMemory, num_blocks * sizeof(jlong));
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "gpuExceptionsMemory memory allocation failed", status);
return;
}
status = cuMemAlloc(&gcInfoSpace, gc_space_size);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "gcInfoSpace memory allocation failed", status);
return;
}
status = cuMemAlloc(&gpuHeapEndPtr, 8);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "gpuHeapEndPtr memory allocation failed", status);
return;
}
status = cuMemAlloc(&gpuBufferSize, 8);
if (CUDA_SUCCESS != status) {
throw_cuda_errror_exception(env, "gpuBufferSize memory allocation failed", status);
return;
}
thisRefClass = (*env)->GetObjectClass(env, this_ref);
setLongField(env, this_ref, "m_ToSpaceAddr", (jlong) toSpace);
setLongField(env, this_ref, "m_GpuToSpaceAddr", (jlong) gpuToSpace);
setLongField(env, this_ref, "m_TextureAddr", (jlong) textureMemory);
setLongField(env, this_ref, "m_GpuTextureAddr", (jlong) gpuTexture);
setLongField(env, this_ref, "m_HandlesAddr", (jlong) handlesMemory);
setLongField(env, this_ref, "m_GpuHandlesAddr", (jlong) gpuHandlesMemory);
setLongField(env, this_ref, "m_ExceptionsHandlesAddr", (jlong) exceptionsMemory);
setLongField(env, this_ref, "m_GpuExceptionsHandlesAddr", (jlong) gpuExceptionsMemory);
setLongField(env, this_ref, "m_ToSpaceSize", (jlong) bufferSize);
setLongField(env, this_ref, "m_MaxGridDim", (jlong) maxGridDim);
setLongField(env, this_ref, "m_NumMultiProcessors", (jlong) numMultiProcessors);
}
value spoc_getCudaDevice(value i)
{
CAMLparam1(i);
CAMLlocal4(general_info, cuda_info, specific_info, gc_info);
CAMLlocal3(device, maxT, maxG);
int nb_devices;
CUdevprop dev_infos;
CUdevice dev;
CUcontext ctx;
CUstream queue[2];
spoc_cu_context *spoc_ctx;
//CUcontext gl_ctx;
char infoStr[1024];
int infoInt;
size_t infoUInt;
int major, minor;
enum cudaError_enum cuda_error;
cuDeviceGetCount (&nb_devices);
if ((Int_val(i)) > nb_devices)
raise_constant(*caml_named_value("no_cuda_device")) ;
CUDA_CHECK_CALL(cuDeviceGet(&dev, Int_val(i)));
CUDA_CHECK_CALL(cuDeviceGetProperties(&dev_infos, dev));
general_info = caml_alloc (9, 0);
CUDA_CHECK_CALL(cuDeviceGetName(infoStr, sizeof(infoStr), dev));
Store_field(general_info,0, copy_string(infoStr));//
CUDA_CHECK_CALL(cuDeviceTotalMem(&infoUInt, dev));
Store_field(general_info,1, Val_int(infoUInt));//
Store_field(general_info,2, Val_int(dev_infos.sharedMemPerBlock));//
Store_field(general_info,3, Val_int(dev_infos.clockRate));//
Store_field(general_info,4, Val_int(dev_infos.totalConstantMemory));//
CUDA_CHECK_CALL(cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, dev));
Store_field(general_info,5, Val_int(infoInt));//
CUDA_CHECK_CALL(cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_ECC_ENABLED, dev));
Store_field(general_info,6, Val_bool(infoInt));//
Store_field(general_info,7, i);
CUDA_CHECK_CALL(cuCtxCreate (&ctx,
CU_CTX_SCHED_BLOCKING_SYNC | CU_CTX_MAP_HOST,
dev));
spoc_ctx = malloc(sizeof(spoc_cl_context));
spoc_ctx->ctx = ctx;
CUDA_CHECK_CALL(cuStreamCreate(&queue[0], 0));
CUDA_CHECK_CALL(cuStreamCreate(&queue[1], 0));
spoc_ctx->queue[0] = queue[0];
spoc_ctx->queue[1] = queue[1];
Store_field(general_info,8, (value)spoc_ctx);
CUDA_CHECK_CALL(cuCtxSetCurrent(ctx));
cuda_info = caml_alloc(1, 0); //0 -> Cuda
specific_info = caml_alloc(18, 0);
cuDeviceComputeCapability(&major, &minor, dev);
Store_field(specific_info,0, Val_int(major));//
Store_field(specific_info,1, Val_int(minor));//
Store_field(specific_info,2, Val_int(dev_infos.regsPerBlock));//
Store_field(specific_info,3, Val_int(dev_infos.SIMDWidth));//
Store_field(specific_info,4, Val_int(dev_infos.memPitch));//
Store_field(specific_info,5, Val_int(dev_infos.maxThreadsPerBlock));//
maxT = caml_alloc(3, 0);
Store_field(maxT,0, Val_int(dev_infos.maxThreadsDim[0]));//
Store_field(maxT,1, Val_int(dev_infos.maxThreadsDim[1]));//
Store_field(maxT,2, Val_int(dev_infos.maxThreadsDim[2]));//
Store_field(specific_info,6, maxT);
maxG = caml_alloc(3, 0);
Store_field(maxG,0, Val_int(dev_infos.maxGridSize[0]));//
Store_field(maxG,1, Val_int(dev_infos.maxGridSize[1]));//
Store_field(maxG,2, Val_int(dev_infos.maxGridSize[2]));//
Store_field(specific_info,7, maxG);
Store_field(specific_info,8, Val_int(dev_infos.textureAlign));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, dev);
Store_field(specific_info,9, Val_bool(infoInt));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, dev);
Store_field(specific_info,10, Val_bool(infoInt));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_INTEGRATED, dev);
Store_field(specific_info,11, Val_bool(infoInt));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, dev);
Store_field(specific_info,12, Val_bool(infoInt));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_COMPUTE_MODE, dev);
Store_field(specific_info,13, Val_int(infoInt));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, dev);
Store_field(specific_info,14, Val_bool(infoInt));//
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_PCI_BUS_ID, dev);
Store_field(specific_info,15, Val_int(infoInt));
cuDeviceGetAttribute(&infoInt, CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID, dev);
Store_field(specific_info,16, Val_int(infoInt));
cuDriverGetVersion(&infoInt);
Store_field(specific_info, 17, Val_int(infoInt));
Store_field(cuda_info, 0, specific_info);
device = caml_alloc(4, 0);
Store_field(device, 0, general_info);
Store_field(device, 1, cuda_info);
{spoc_cuda_gc_info* gcInfo = (spoc_cuda_gc_info*)malloc(sizeof(spoc_cuda_gc_info));
CUDA_CHECK_CALL(cuMemGetInfo(&infoUInt, NULL));
infoUInt -= (32*1024*1024);
Store_field(device, 2, (value)gcInfo);
{cuda_event_list* events = NULL;
Store_field(device, 3, (value)events);
CAMLreturn(device);}}
}
JNIEXPORT jobject JNICALL Java_org_trifort_rootbeer_runtime_CUDARuntime_loadGpuDevices
(JNIEnv * env, jobject this_ref)
{
int i;
int status;
int num_devices;
CUdevice device;
CUcontext context;
jclass array_list_class;
jmethodID array_list_init;
jmethodID array_list_add;
jobject ret;
jclass gpu_device_class;
jmethodID gpu_device_init;
jobject gpu_device;
int major_version;
int minor_version;
char device_name[4096];
size_t free_mem;
size_t total_mem;
int registers_per_block;
int warp_size;
int pitch;
int threads_per_block;
int shared_mem_per_block;
int clock_rate;
int mem_clock_rate;
int const_mem;
int integrated;
int threads_per_multiprocessor;
int multiprocessor_count;
int max_block_dim_x;
int max_block_dim_y;
int max_block_dim_z;
int max_grid_dim_x;
int max_grid_dim_y;
int max_grid_dim_z;
array_list_class = (*env)->FindClass(env, "java/util/ArrayList");
array_list_init = (*env)->GetMethodID(env, array_list_class, "<init>", "()V");
array_list_add = (*env)->GetMethodID(env, array_list_class, "add", "(Ljava/lang/Object;)Z");
ret = (*env)->NewObject(env, array_list_class, array_list_init);
gpu_device_class = (*env)->FindClass(env, "org/trifort/rootbeer/runtime/GpuDevice");
gpu_device_init = (*env)->GetStaticMethodID(env, gpu_device_class, "newCudaDevice",
"(IIILjava/lang/String;JJIIIIIIIIZIIIIIIII)Lorg/trifort/rootbeer/runtime/GpuDevice;");
status = cuInit(0);
if(status != CUDA_SUCCESS){
return ret;
}
cuDeviceGetCount(&num_devices);
for(i = 0; i < num_devices; ++i){
status = cuDeviceGet(&device, i);
if(status != CUDA_SUCCESS){
continue;
}
cuDeviceComputeCapability(&major_version, &minor_version, device);
cuDeviceGetName(device_name, 4096, device);
cuCtxCreate(&context, CU_CTX_MAP_HOST, device);
cuMemGetInfo(&free_mem, &total_mem);
cuCtxDestroy(context);
cuDeviceGetAttribute(®isters_per_block, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK, device);
cuDeviceGetAttribute(&warp_size, CU_DEVICE_ATTRIBUTE_WARP_SIZE, device);
cuDeviceGetAttribute(&pitch, CU_DEVICE_ATTRIBUTE_MAX_PITCH, device);
cuDeviceGetAttribute(&threads_per_block, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, device);
cuDeviceGetAttribute(&shared_mem_per_block, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK, device);
cuDeviceGetAttribute(&clock_rate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, device);
cuDeviceGetAttribute(&mem_clock_rate, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, device);
cuDeviceGetAttribute(&const_mem, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY, device);
cuDeviceGetAttribute(&integrated, CU_DEVICE_ATTRIBUTE_INTEGRATED, device);
cuDeviceGetAttribute(&threads_per_multiprocessor, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, device);
cuDeviceGetAttribute(&multiprocessor_count, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, device);
cuDeviceGetAttribute(&max_block_dim_x, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, device);
cuDeviceGetAttribute(&max_block_dim_y, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, device);
cuDeviceGetAttribute(&max_block_dim_z, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, device);
cuDeviceGetAttribute(&max_grid_dim_x, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, device);
cuDeviceGetAttribute(&max_grid_dim_y, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y, device);
cuDeviceGetAttribute(&max_grid_dim_z, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z, device);
gpu_device = (*env)->CallObjectMethod(env, gpu_device_class, gpu_device_init,
i, major_version, minor_version, (*env)->NewStringUTF(env, device_name),
(jlong) free_mem, (jlong) total_mem, registers_per_block, warp_size, pitch, threads_per_block,
shared_mem_per_block, clock_rate, mem_clock_rate, const_mem, integrated,
threads_per_multiprocessor, multiprocessor_count, max_block_dim_x,
max_block_dim_y, max_block_dim_z, max_grid_dim_x, max_grid_dim_y,
max_grid_dim_z);
(*env)->CallBooleanMethod(env, ret, array_list_add, gpu_device);
}
return ret;
}
/**
* initialization after the GL context is set
*/
void GLCUPixelBuffer::init(int w, int h)
{
width = w+BLOCKSZ-(w%BLOCKSZ);
height = h+BLOCKSZ-(h%BLOCKSZ);
Q_ASSERT(pixelBuffer==0);
int size_tex_data = sizeof(GLubyte) * width * height * 4;
/*
* there will be in and out here,
* take care to the usage pattern.
* the blockop we will ll be pointing at
* will show the desired level of op on the framebuffer
* side note : working on ultra high resolution,
* will require a downsampling before rendering
*/
size_t free, total;
CUDCHK(cuMemGetInfo(&free,&total)) ;
qDebug() << "GPU memory : free="<<free<< " /"<< total;
pixelBuffer = new QGLBuffer(QGLBuffer::PixelUnpackBuffer);
pixelBuffer->setUsagePattern(QGLBuffer::StreamDraw);
pixelBuffer->create();
pixelBuffer->bind();
pixelBuffer->allocate(size_tex_data);
pixelBuffer->release();
// cudaGLRegisterBufferObject( pixelBuffer->bufferId() ) ); // deprecated as of cuda 3.0
CUDCHK ( cuGraphicsGLRegisterBuffer(&cudaResource, pixelBuffer->bufferId(),
CU_GRAPHICS_REGISTER_FLAGS_NONE
//CU_GRAPHICS_REGISTER_FLAGS_WRITE_DISCARD
) );
//cudaGraphicsRegisterFlagsWriteDiscard) );
/*
* create textures
* delete texture object if necessary
* for reallocating tex mem, e.g. at different size
*/
deleteTexture();
textureID = new GLuint[1]; // Generate a texture id
glGenTextures(1, textureID);
glBindTexture( GL_TEXTURE_2D, textureID[0]);
// Allocate the texture memory. The last parameter is NULL since we only
// want to allocate memory, not initialize it
glTexImage2D( GL_TEXTURE_2D, 0, GL_RGBA8, width, height, 0,
GL_BGRA,GL_UNSIGNED_BYTE, NULL);
// Must set the filter mode, GL_LINEAR enables interpolation when scaling
/*glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);*/
/* Note: GL_TEXTURE_RECTANGLE_ARB may be used instead of
GL_TEXTURE_2D for improved performance if linear interpolation is
not desired. Replace GL_LINEAR with GL_NEAREST in the
glTexParameteri() call
*/
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
glBindTexture(GL_TEXTURE_2D, 0);
//CUDCHK(cuMemGetInfo(&free,&total)) ;
//qDebug() << "memory : free="<<free<< " /"<< total;
}
void initDevice(JNIEnv * env, jobject this_ref, jint max_blocks_per_proc, jint max_threads_per_block, jlong free_space)
{
int status;
jint num_blocks;
int deviceCount = 0;
size_t f_mem;
size_t t_mem;
size_t to_space_size;
textureMemSize = 1;
status = cuDeviceGetCount(&deviceCount);
CHECK_STATUS(env,"error in cuDeviceGetCount",status)
getBestDevice(env);
status = cuCtxCreate(&cuContext, CU_CTX_MAP_HOST, cuDevice);
CHECK_STATUS(env,"error in cuCtxCreate",status)
status = cuMemGetInfo (&f_mem, &t_mem);
CHECK_STATUS(env,"error in cuMemGetInfo",status)
to_space_size = f_mem;
num_blocks = numMultiProcessors * max_threads_per_block * max_blocks_per_proc;
#if DEBUG
printf("Memory: %i(MB)/%i(MB) (Free/Total)\n",f_mem/1024/1024, t_mem/1024/1024);
printf("num_blocks = %i\n",num_blocks);
printf("numMultiProcessors = %i\n",numMultiProcessors);
printf("max_threads_per_block = %i\n",max_threads_per_block);
printf("max_blocks_per_proc = %i\n",max_blocks_per_proc);
fflush(stdout);
#endif
//space for 100 types in the scene
classMemSize = sizeof(jint)*100;
gc_space_size = 1024;
to_space_size -= (num_blocks * sizeof(jlong));
to_space_size -= (num_blocks * sizeof(jlong));
to_space_size -= gc_space_size;
to_space_size -= free_space;
to_space_size -= classMemSize;
//to_space_size -= textureMemSize;
bufferSize = to_space_size;
status = cuMemHostAlloc(&toSpace, to_space_size, 0);
CHECK_STATUS(env,"toSpace memory allocation failed",status)
status = cuMemAlloc(&gpuToSpace, to_space_size);
CHECK_STATUS(env,"gpuToSpace memory allocation failed",status)
status = cuMemAlloc(&gpuClassMemory, classMemSize);
CHECK_STATUS(env,"gpuClassMemory memory allocation failed",status)
/*
status = cuMemHostAlloc(&textureMemory, textureMemSize, 0);
if (CUDA_SUCCESS != status)
{
printf("error in cuMemHostAlloc textureMemory %d\n", status);
}
status = cuMemAlloc(&gpuTexture, textureMemSize);
if (CUDA_SUCCESS != status)
{
printf("error in cuMemAlloc gpuTexture %d\n", status);
}
*/
status = cuMemHostAlloc(&handlesMemory, num_blocks * sizeof(jlong), CU_MEMHOSTALLOC_WRITECOMBINED);
CHECK_STATUS(env,"handlesMemory memory allocation failed",status)
status = cuMemAlloc(&gpuHandlesMemory, num_blocks * sizeof(jlong));
CHECK_STATUS(env,"gpuHandlesMemory memory allocation failed",status)
status = cuMemHostAlloc(&exceptionsMemory, num_blocks * sizeof(jlong), 0);
CHECK_STATUS(env,"exceptionsMemory memory allocation failed",status)
status = cuMemAlloc(&gpuExceptionsMemory, num_blocks * sizeof(jlong));
CHECK_STATUS(env,"gpuExceptionsMemory memory allocation failed",status)
status = cuMemAlloc(&gcInfoSpace, gc_space_size);
CHECK_STATUS(env,"gcInfoSpace memory allocation failed",status)
status = cuMemAlloc(&gpuHeapEndPtr, 8);
CHECK_STATUS(env,"gpuHeapEndPtr memory allocation failed",status)
status = cuMemAlloc(&gpuBufferSize, 8);
CHECK_STATUS(env,"gpuBufferSize memory allocation failed",status)
thisRefClass = (*env)->GetObjectClass(env, this_ref);
setLongField(env, this_ref, "m_ToSpaceAddr", (jlong) toSpace);
setLongField(env, this_ref, "m_GpuToSpaceAddr", (jlong) gpuToSpace);
setLongField(env, this_ref, "m_TextureAddr", (jlong) textureMemory);
setLongField(env, this_ref, "m_GpuTextureAddr", (jlong) gpuTexture);
setLongField(env, this_ref, "m_HandlesAddr", (jlong) handlesMemory);
setLongField(env, this_ref, "m_GpuHandlesAddr", (jlong) gpuHandlesMemory);
setLongField(env, this_ref, "m_ExceptionsHandlesAddr", (jlong) exceptionsMemory);
setLongField(env, this_ref, "m_GpuExceptionsHandlesAddr", (jlong) gpuExceptionsMemory);
setLongField(env, this_ref, "m_ToSpaceSize", (jlong) bufferSize);
setLongField(env, this_ref, "m_MaxGridDim", (jlong) maxGridDim);
setLongField(env, this_ref, "m_NumMultiProcessors", (jlong) numMultiProcessors);
}
/*
* Class: edu_syr_pcpratts_rootbeer_runtime2_cuda_CudaRuntime2
* Method: printDeviceInfo
* Signature: ()V
*/
JNIEXPORT void JNICALL Java_edu_syr_pcpratts_rootbeer_runtime2_cuda_CudaRuntime2_printDeviceInfo
(JNIEnv *env, jclass cls)
{
int i, a=0, b=0, status;
int num_devices = 0;
char str[1024];
size_t free_mem, total_mem;
status = cuInit(0);
CHECK_STATUS(env,"error in cuInit",status)
cuDeviceGetCount(&num_devices);
printf("%d cuda gpus found\n", num_devices);
for (i = 0; i < num_devices; ++i)
{
CUdevice dev;
status = cuDeviceGet(&dev, i);
CHECK_STATUS(env,"error in cuDeviceGet",status)
status = cuCtxCreate(&cuContext, CU_CTX_MAP_HOST, dev);
CHECK_STATUS(env,"error in cuCtxCreate",status)
printf("\nGPU:%d\n", i);
if(cuDeviceComputeCapability(&a, &b, dev) == CUDA_SUCCESS)
printf("Version: %i.%i\n", a, b);
if(cuDeviceGetName(str,1024,dev) == CUDA_SUCCESS)
printf("Name: %s\n", str);
if(cuMemGetInfo(&free_mem, &total_mem) == CUDA_SUCCESS){
#if (defined linux || defined __APPLE_CC__)
printf("Total global memory: %zu/%zu (Free/Total) MBytes\n", free_mem/1024/1024, total_mem/1024/1024);
#else
printf("Total global memory: %Iu/%Iu (Free/Total) MBytes\n", free_mem/1024/1024, total_mem/1024/1024);
#endif
}
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK,dev) == CUDA_SUCCESS)
printf("Total registers per block: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_WARP_SIZE,dev) == CUDA_SUCCESS)
printf("Warp size: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_PITCH,dev) == CUDA_SUCCESS)
printf("Maximum memory pitch: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK,dev) == CUDA_SUCCESS)
printf("Maximum threads per block: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK,dev) == CUDA_SUCCESS)
printf("Total shared memory per block %.2f KB\n", a/1024.0);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_CLOCK_RATE,dev) == CUDA_SUCCESS)
printf("Clock rate: %.2f MHz\n", a/1000000.0);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE,dev) == CUDA_SUCCESS)
printf("Memory Clock rate: %.2f\n", a/1000000.0);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY,dev) == CUDA_SUCCESS)
printf("Total constant memory: %.2f MB\n", a/1024.0/1024.0);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_INTEGRATED,dev) == CUDA_SUCCESS)
printf("Integrated: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR,dev) == CUDA_SUCCESS)
printf("Max threads per multiprocessor:%i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,dev) == CUDA_SUCCESS)
printf("Number of multiprocessors: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X,dev) == CUDA_SUCCESS)
printf("Maximum dimension x of block: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y,dev) == CUDA_SUCCESS)
printf("Maximum dimension y of block: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z,dev) == CUDA_SUCCESS)
printf("Maximum dimension z of block: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X,dev) == CUDA_SUCCESS)
printf("Maximum dimension x of grid: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y,dev) == CUDA_SUCCESS)
printf("Maximum dimension y of grid: %i\n", a);
if(cuDeviceGetAttribute(&a, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z,dev) == CUDA_SUCCESS)
printf("Maximum dimension z of grid: %i\n", a);
cuCtxDestroy(cuContext);
}
}
IMT_MRGui::IMT_MRGui(QWidget *parent) :
QMainWindow(parent),
ui(new Ui::IMT_MRGui)
{
// Initialize the first GPU
GPU0_.allocateGPU(0);
GPU0_.printInformation(std::cout);
size_t free;
size_t total;
cuMemGetInfo(&free, &total);
std::cout << "free memory: " << free / 1024 / 1024 << "mb, total memory: " << total / 1024 / 1024 << "mb" << std::endl;
ui->setupUi(this);
read_siemens = 0;
fftobj_ = new agile::FFT<TType>();
kspacefovobj_ = new agile::KSpaceFOV<TType>();
open_irgnpara_window = new IRGN_para(); // Be sure to destroy you window somewhere
open_irgnpara_window->hide();
_pathsetting = new PathSetting(); // Be sure to destroy you window somewhere
_pathsetting->hide();
_specialsetting = new SpecialSetting(); // Be sure to destroy you window somewhere
_specialsetting->hide();
setStatusBar();
setTitleText("");
future = new QFuture<void>;
watcher = new QFutureWatcher<void>;
_cycleread_thread = new CycleRead;
_cycleread_thread->set_max_acq_time(_specialsetting->get_autoload_timeout());
_infotext="";
QObject::connect(this,SIGNAL(sendInfo(QString, bool)),this,SLOT(set_Info(QString, bool)));
QObject::connect(this,SIGNAL(sendWarning(QString)),this,SLOT(set_Warning(QString)));
QObject::connect(this,SIGNAL(sendSaveFile(QString,QString)),this,SLOT(set_SaveFile(QString,QString)),Qt::BlockingQueuedConnection);
QObject::connect(_cycleread_thread, SIGNAL(send_filenames(QStringList, QStringList)),
this, SLOT(startauto(QStringList, QStringList)));
_act_index = 0;
_automatic_on = false;
_write_file_index=0;
ui->cb_savingtype->setCurrentIndex(2);
ui->pb_automatic->setText("Auto Off");
_postprocess = new agile::PostProcess<TType, TType_real>();
QLabel* imageLabel = new QLabel(this);
imageLabel->setBackgroundRole(QPalette::Base);
imageLabel->setSizePolicy(QSizePolicy::Ignored, QSizePolicy::Ignored);
imageLabel->setScaledContents(true);
QImage image(":/images/wappen.png");
imageLabel->setPixmap(QPixmap::fromImage(image));
imageLabel->resize(imageLabel->pixmap()->size());
imageLabel->setGeometry((this->width() - imageLabel->sizeHint().width()), 40, imageLabel->sizeHint().width(), imageLabel->sizeHint().height());
imageLabel->show();
}
