std::pair< std::vector<context>, std::vector<command_queue> >
queue_list(DevFilter &&filter, unsigned queue_flags = 0)
{
cuda_check( do_init() );
std::vector<context> ctx;
std::vector<command_queue> queue;
int ndev;
cuda_check( cuDeviceGetCount(&ndev) );
for(int d = 0; d < ndev; ++d) {
try {
CUdevice dev;
cuda_check( cuDeviceGet(&dev, d) );
if (!filter(dev)) continue;
context c(dev);
command_queue q(c, dev, queue_flags);
ctx.push_back(c);
queue.push_back(q);
} catch(const error&) { }
}
return std::make_pair(ctx, queue);
}
void Mesh::NEListToArray() {
std::vector< std::set<size_t> >::const_iterator vec_it;
std::set<size_t>::const_iterator set_it;
size_t offset = 0;
size_t index = 0;
for(vec_it = NEList.begin(); vec_it != NEList.end(); vec_it++)
offset += vec_it->size();
NEListArray_size = offset;
cuda_check(cudaHostAlloc((void **)&NEListIndex_pinned, sizeof(size_t) * (NNodes+1), cudaHostAllocPortable));
cuda_check(cudaHostAlloc((void **)&NEListArray_pinned, sizeof(size_t) * NEListArray_size, cudaHostAllocPortable));
offset = 0;
for(vec_it = NEList.begin(); vec_it != NEList.end(); vec_it++)
{
NEListIndex_pinned[index++] = offset;
for(set_it = vec_it->begin(); set_it != vec_it->end(); set_it++)
NEListArray_pinned[offset++] = *set_it;
}
assert(index == NEList.size());
NEListIndex_pinned[index] = offset;
}
/// Returns device compute capability as a tuple of major and minor version numbers.
std::tuple<int, int> compute_capability() const {
int major, minor;
cuda_check( cuDeviceGetAttribute(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, d) );
cuda_check( cuDeviceGetAttribute(&minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, d) );
return std::make_tuple(major, minor);
}
void Random<GPU>::uniform (float *data, int size, const float a, const float b) const
{ const int N = size;
cuda_check (curandGenerateUniform (dnnctx[did_]->curand_, data, N));
if (a != 0.f || b != 1.f)
XPU_KERNEL_LAUNCH (tensor_scale, cuda_get_blocks(N), CUDA_NUM_THREADS, 0, dnnctx[did_]->stream_,
N, data, a, b);
}
svm_vector(const backend::command_queue &q, size_t n) : n(n), q(q), p(NULL) {
q.context().set_current();
CUdeviceptr dptr;
cuda_check( cuMemAllocManaged(&dptr, n * sizeof(T), CU_MEM_ATTACH_GLOBAL) );
p = reinterpret_cast<T*>(static_cast<size_t>(dptr));
}
spmat_hyb(
const command_queue &queue,
int n, int m,
const row_t *row_begin,
const col_t *col_begin,
const val_t *val_begin
)
: handle( cusparse_handle(queue) ),
desc ( create_description(), detail::deleter() ),
mat ( create_matrix(), detail::deleter() )
{
cuda_check( cusparseSetMatType(desc.get(), CUSPARSE_MATRIX_TYPE_GENERAL) );
cuda_check( cusparseSetMatIndexBase(desc.get(), CUSPARSE_INDEX_BASE_ZERO) );
fill_matrix(queue, n, m, row_begin, col_begin, val_begin);
}
static CUstream create(const vex::backend::context &ctx, unsigned flags = 0) {
ctx.set_current();
CUstream s;
cuda_check( cuStreamCreate(&s, flags) );
return s;
}
std::vector<device> device_list(DevFilter&& filter) {
cuda_check( do_init() );
std::vector<device> device;
int ndev;
cuda_check( cuDeviceGetCount(&ndev) );
for(int d = 0; d < ndev; ++d) {
try {
CUdevice dev;
cuda_check( cuDeviceGet(&dev, d) );
if (!filter(dev)) continue;
device.push_back(dev);
} catch(const error&) { }
}
return device;
}
/// Allocates memory buffer on the device associated with the given queue.
device_vector(const command_queue &q, size_t n) : n(n) {
if (n) {
q.context().set_current();
CUdeviceptr ptr;
cuda_check( cuMemAlloc(&ptr, n * sizeof(T)) );
buffer.reset(reinterpret_cast<char*>(static_cast<size_t>(ptr)), detail::deleter() );
}
}
inline cusparseHandle_t cusparse_handle(const command_queue &q) {
typedef std::shared_ptr<std::remove_pointer<cusparseHandle_t>::type> smart_handle;
typedef vex::detail::object_cache<vex::detail::index_by_context, smart_handle> cache_type;
static cache_type cache;
auto h = cache.find(q);
if (h == cache.end()) {
select_context(q);
cusparseHandle_t handle;
cuda_check( cusparseCreate(&handle) );
cuda_check( cusparseSetStream(handle, q.raw()) );
h = cache.insert(q, smart_handle(handle, detail::deleter()));
}
return h->second.get();
}
/// Copies data from host memory to device.
void write(const command_queue &q, size_t offset, size_t size, const T *host,
bool blocking = false) const
{
(void)blocking;
if (size) {
q.context().set_current();
cuda_check( cuMemcpyHtoD(raw() + offset * sizeof(T), host, size * sizeof(T)) );
}
}
/// Copies data from device to host memory.
void read(const command_queue &q, size_t offset, size_t size, T *host,
bool blocking = false) const
{
(void)blocking;
if (size) {
q.context().set_current();
cuda_check( cuMemcpyDtoH(host, raw() + offset * sizeof(T), size * sizeof(T)) );
}
}
/// Constructor. Extracts a backend::kernel instance from backend::program.
kernel(const command_queue &queue,
const program &P,
const std::string &name,
std::function<size_t(size_t)> smem
)
: ctx(queue.context()), P(P), smem(0)
{
cuda_check( cuModuleGetFunction(&K, P.raw(), name.c_str()) );
config(queue, smem);
}
/// Constructor. Creates a backend::kernel instance from source.
kernel(const command_queue &queue,
const std::string &src, const std::string &name,
std::function<size_t(size_t)> smem,
const std::string &options = ""
)
: ctx(queue.context()), P(build_sources(queue, src, options)), smem(0)
{
cuda_check( cuModuleGetFunction(&K, P.raw(), name.c_str()) );
config(queue, smem);
}
void Mesh::pin_data() {
NNListToArray();
NEListToArray();
size_t ENList_bytes = sizeof(size_t) * ENList.size();
size_t coords_bytes = sizeof(float) * coords.size();
size_t metric_bytes = sizeof(float) * metric.size();
size_t normal_bytes = sizeof(float) * normals.size();
cuda_check(cudaHostAlloc((void **)&ENList_pinned, ENList_bytes, cudaHostAllocPortable));
cuda_check(cudaHostAlloc((void **)&coords_pinned, coords_bytes, cudaHostAllocPortable));
cuda_check(cudaHostAlloc((void **)&metric_pinned, metric_bytes, cudaHostAllocPortable));
cuda_check(cudaHostAlloc((void **)&normals_pinned, normal_bytes, cudaHostAllocPortable));
memcpy(ENList_pinned, &ENList[0], ENList_bytes);
memcpy(coords_pinned, &coords[0], coords_bytes);
memcpy(metric_pinned, &metric[0], metric_bytes);
memcpy(normals_pinned, &normals[0], normal_bytes);
}
spmat_crs(
const command_queue &queue,
int n, int m,
const row_t *row_begin,
const col_t *col_begin,
const val_t *val_begin
)
: n(n), m(m), nnz(static_cast<unsigned>(row_begin[n] - row_begin[0])),
handle( cusparse_handle(queue) ),
desc ( create_description(), detail::deleter() ),
row(queue, n+1, row_begin),
col(queue, nnz, col_begin + row_begin[0]),
val(queue, nnz, val_begin + row_begin[0])
{
if (row_begin[0] != 0)
vector<int>(queue, row) -= row_begin[0];
cuda_check( cusparseSetMatType(desc.get(), CUSPARSE_MATRIX_TYPE_GENERAL) );
cuda_check( cusparseSetMatIndexBase(desc.get(), CUSPARSE_INDEX_BASE_ZERO) );
}
/// Constructor. Extracts a backend::kernel instance from backend::program.
kernel(const command_queue &queue,
const program &P,
const std::string &name,
size_t smem_per_thread = 0
)
: ctx(queue.context()), P(P), smem(0)
{
cuda_check( cuModuleGetFunction(&K, P.raw(), name.c_str()) );
config(queue,
[smem_per_thread](size_t wgs){ return wgs * smem_per_thread; });
}
void mul(const device_vector<double> &x, device_vector<double> &y,
double alpha = 1, bool append = false) const
{
double beta = append ? 1.0 : 0.0;
cuda_check(
cusparseDhybmv(handle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, desc.get(), mat.get(),
x.raw_ptr(), &beta, y.raw_ptr()
)
);
}
void mul(const device_vector<float> &x, device_vector<float> &y,
float alpha = 1, bool append = false) const
{
float beta = append ? 1.0f : 0.0f;
cuda_check(
cusparseShybmv(handle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, desc.get(), mat.get(),
x.raw_ptr(), &beta, y.raw_ptr()
)
);
}
/// Constructor. Creates a backend::kernel instance from source.
kernel(const command_queue &queue,
const std::string &src,
const std::string &name,
size_t smem_per_thread = 0,
const std::string &options = ""
)
: ctx(queue.context()), P(build_sources(queue, src, options)), smem(0)
{
cuda_check( cuModuleGetFunction(&K, P.raw(), name.c_str()) );
config(queue,
[smem_per_thread](size_t wgs){ return wgs * smem_per_thread; });
}
void fill_matrix(const command_queue &q,
int n, int m, const row_t *row, const col_t *col, const double *val)
{
device_vector<int> r(q, n + 1, row);
device_vector<int> c(q, row[n], col + row[0]);
device_vector<double> v(q, row[n], val + row[0]);
if (row[0] != 0) vector<int>(q, r) -= row[0];
cuda_check(
cusparseDcsr2hyb(handle, n, m, desc.get(),
v.raw_ptr(), r.raw_ptr(), c.raw_ptr(), mat.get(), 0,
CUSPARSE_HYB_PARTITION_AUTO
)
);
}
/// Enqueue the kernel to the specified command queue.
void operator()(const command_queue &q) {
prm_addr.clear();
for(auto p = prm_pos.begin(); p != prm_pos.end(); ++p)
prm_addr.push_back(stack.data() + *p);
cuda_check(
cuLaunchKernel(
K,
static_cast<unsigned>(g_size.x), static_cast<unsigned>(g_size.y), static_cast<unsigned>(g_size.z),
static_cast<unsigned>(w_size.x), static_cast<unsigned>(w_size.y), static_cast<unsigned>(w_size.z),
static_cast<unsigned>(smem),
q.raw(),
prm_addr.data(),
0
)
);
reset();
}
device_vector(const command_queue &q, size_t n,
const H *host = 0, mem_flags flags = MEM_READ_WRITE)
: n(n)
{
(void)flags;
if (n) {
q.context().set_current();
CUdeviceptr ptr;
cuda_check( cuMemAlloc(&ptr, n * sizeof(T)) );
buffer.reset(reinterpret_cast<char*>(static_cast<size_t>(ptr)), detail::deleter() );
if (host) {
if (std::is_same<T, H>::value)
write(q, 0, n, reinterpret_cast<const T*>(host), true);
else
write(q, 0, n, std::vector<T>(host, host + n).data(), true);
}
}
}
void Random<GPU>::gaussian (float *data, int size, const float mu, const float sigma) const
{ CHECK (sigma > 0.f);
cuda_check (curandGenerateNormal (dnnctx[did_]->curand_, data, size, mu, sigma));
}
void Random<GPU>::set_seed (int seed)
{ cuda_check (curandSetPseudoRandomGeneratorSeed (dnnctx[did_]->curand_, seed));
}
void DataBuffer<DT>::page_unlk ()
{ cuda_check (cudaHostUnregister ( data_.dptr));
cuda_check (cudaHostUnregister ( pred_.dptr));
cuda_check (cudaHostUnregister (label_.dptr));
}
void DataBuffer<DT>::page_lock ()
{ cuda_check (cudaHostRegister ( data_.dptr, data_.size_d(), cudaHostRegisterPortable));
cuda_check (cudaHostRegister ( pred_.dptr, pred_.size_d(), cudaHostRegisterPortable));
cuda_check (cudaHostRegister (label_.dptr, label_.size_d(), cudaHostRegisterPortable));
}
static void dispose(cusparseHybMat_t handle) {
cuda_check( cusparseDestroyHybMat(handle) );
}
static void dispose(cusparseMatDescr_t handle) {
cuda_check( cusparseDestroyMatDescr(handle) );
}
static void dispose(cusparseHandle_t handle) {
cuda_check( cusparseDestroy(handle) );
}
