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Implement zeroing of tensors through memcpy and cuMemcpy

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This commit is contained in:
Alejandro Gallo 2023-01-26 01:49:55 +01:00
parent 4e2d1143e5
commit 93cba3c3ab
4 changed files with 24 additions and 60 deletions
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9
include/atrip/Operations.hpp
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@ -24,15 +24,6 @@ namespace acc {
// cuda kernels
template <typename F>
__MAYBE_GLOBAL__
void zeroing(F* a, size_t n) {
F zero = {0};
for (size_t i = 0; i < n; i++) {
a[i] = zero;
}
}
////
template <typename F>
__MAYBE_DEVICE__ __MAYBE_HOST__ __INLINE__

4
src/atrip/Atrip.cxx
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@ -160,9 +160,9 @@ Atrip::Output Atrip::run(Atrip::Input<F> const& in) {
LOG(0,"Atrip") << "ooo blocks: "
<< Atrip::kernelDimensions.ooo.blocks << "\n";
<< Atrip::kernelDimensions.ooo.blocks << "\n";
LOG(0,"Atrip") << "ooo threads per block: "
<< Atrip::kernelDimensions.ooo.threads << "\n";
<< Atrip::kernelDimensions.ooo.threads << "\n";
#endif
// allocate the three scratches, see piecuch

5
src/atrip/Complex.cxx
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@ -21,11 +21,6 @@ namespace atrip {
template <> double maybeConjugate(const double a) { return a; }
template <> Complex maybeConjugate(const Complex a) { return std::conj(a); }
#if defined(HAVE_CUDA)
#endif
namespace traits {
template <typename F> bool isComplex() { return false; }
template <> bool isComplex<double>() { return false; }

66
src/atrip/Equations.cxx
View File

@ -13,6 +13,8 @@
// limitations under the License.
// [[file:~/cuda/atrip/atrip.org::*Prolog][Prolog:2]]
#include <cstring>
#include<atrip/Equations.hpp>
#include<atrip/CUDA.hpp>
@ -580,13 +582,8 @@ void getEnergySame
)
#define MAYBE_CONJ(_conj, _buffer) \
do { \
acc::maybeConjugate<<< \
\
Atrip::kernelDimensions.ooo.blocks, \
\
Atrip::kernelDimensions.ooo.threads \
\
>>>((DataFieldType<F>*)_conj, \
acc::maybeConjugate<<<1, 1 \
>>>((DataFieldType<F>*)_conj, \
(DataFieldType<F>*)_buffer, \
NoNoNo); \
} while (0)
@ -648,50 +645,31 @@ void getEnergySame
F one{1.0}, m_one{-1.0}, zero{0.0};
const size_t NoNoNo = No*NoNo;
// Zeroing vectors
#ifdef HAVE_CUDA
// DataFieldType<F>* _t_buffer;
// DataFieldType<F>* _vhhh;
// WITH_CHRONO("double:cuda:alloc",
// _CHECK_CUDA_SUCCESS("Allocating _t_buffer",
// cuMemAlloc((CUdeviceptr*)&_t_buffer,
// NoNoNo * sizeof(DataFieldType<F>)));
// _CHECK_CUDA_SUCCESS("Allocating _vhhh",
// cuMemAlloc((CUdeviceptr*)&_vhhh,
// NoNoNo * sizeof(DataFieldType<F>)));
// )
#if !defined(ATRIP_ONLY_DGEMM)
// we still have to zero this
const size_t
bs = Atrip::kernelDimensions.ooo.blocks,
ths = Atrip::kernelDimensions.ooo.threads;
acc::zeroing<<<bs, ths>>>((DataFieldType<F>*)_t_buffer, NoNoNo);
acc::zeroing<<<bs, ths>>>((DataFieldType<F>*)_vhhh, NoNoNo);
{
const size_t elements = NoNoNo * sizeof(DataFieldType<F>)/4;
WITH_CHRONO("double:zeroing",
_CHECK_CUDA_SUCCESS("Zeroing Tijk",
cuMemsetD32_v2((CUdeviceptr)Tijk, 0x00, elements));
_CHECK_CUDA_SUCCESS("Zeroing t buffer",
cuMemsetD32_v2((CUdeviceptr)_t_buffer, 0x00, elements));
_CHECK_CUDA_SUCCESS("Zeroing vhhh buffer",
cuMemsetD32_v2((CUdeviceptr)_vhhh, 0x00, elements));
)
}
#endif
#else
DataFieldType<F>* _t_buffer = (DataFieldType<F>*)malloc(NoNoNo * sizeof(F));
DataFieldType<F>* _vhhh = (DataFieldType<F>*)malloc(NoNoNo * sizeof(F));
DataFieldType<F> zero_h{0.0};
for (size_t i=0; i < NoNoNo; i++) {
_t_buffer[i] = zero_h;
_vhhh[i] = zero_h;
}
#endif
// Set Tijk to zero
#if defined(HAVE_CUDA) && !defined(ATRIP_ONLY_DGEMM)
WITH_CHRONO("double:reorder",
acc::zeroing<<<bs, ths>>>((DataFieldType<F>*)Tijk,
NoNoNo);
)
#endif
#if !defined(HAVE_CUDA)
WITH_CHRONO("double:reorder",
for (size_t k = 0; k < NoNoNo; k++) {
Tijk[k] = DataFieldType<F>{0.0};
})
#endif /* !defined(HAVE_CUDA) */
std::memset((void*)_t_buffer, 0x00, NoNoNo * sizeof(DataFieldType<F>));
std::memset((void*)_vhhh, 0x00, NoNoNo * sizeof(DataFieldType<F>));
std::memset((void*)Tijk, 0x00, NoNoNo * sizeof(DataFieldType<F>));
#endif /* HAVE_CUDA */
#if defined(ATRIP_ONLY_DGEMM)