mv tensor repo

This commit is contained in:
2023-11-29 22:46:44 +01:00
parent 55852146cb
commit 09c402a4ba
7 changed files with 4 additions and 1 deletions
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/*#include <cuda.h>
#include <cuda_runtime.h>
#include "cuda.h"
#include "cuda_runtime.h"
*/
#include "d_tensCuda.h"
//#include "index.h"
#include <stdio.h>
////////////////////////////////////////////////////////
//1D grid of 1D blocks
__device__
int d_getGlobalIdx_1D_1D() {
return blockIdx.x * blockDim.x + threadIdx.x;
}
//1D grid of 2D blocks
__device__
int d_getGlobalIdx_1D_2D() {
return blockIdx.x * blockDim.x * blockDim.y
+ threadIdx.y * blockDim.x + threadIdx.x;
}
//1D grid of 3D blocks
__device__
int d_getGlobalIdx_1D_3D() {
return blockIdx.x * blockDim.x * blockDim.y * blockDim.z
+ threadIdx.z * blockDim.y * blockDim.x
+ threadIdx.y * blockDim.x + threadIdx.x;
}
//2D grid of 1D blocks
__device__ int d_getGlobalIdx_2D_1D() {
int blockId
= blockIdx.y * gridDim.x + blockIdx.x;
int threadId = blockId * blockDim.x + threadIdx.x;
return threadId;
}
//2D grid of 2D blocks
__device__
int d_getGlobalIdx_2D_2D() {
int blockId = blockIdx.x + blockIdx.y * gridDim.x;
int threadId = blockId * (blockDim.x * blockDim.y)
+ (threadIdx.y * blockDim.x) + threadIdx.x;
return threadId;
}
//2D grid of 3D blocks
__device__
int d_getGlobalIdx_2D_3D() {
int blockId = blockIdx.x + blockIdx.y * gridDim.x;
int threadId = blockId * (blockDim.x * blockDim.y * blockDim.z)
+ (threadIdx.z * (blockDim.x * blockDim.y))
+ (threadIdx.y * blockDim.x) + threadIdx.x;
return threadId;
}
//3D grid of 1D blocks
__device__
int d_getGlobalIdx_3D_1D() {
int blockId = blockIdx.x + blockIdx.y * gridDim.x
+ gridDim.x * gridDim.y * blockIdx.z;
int threadId = blockId * blockDim.x + threadIdx.x;
return threadId;
}
//3D grid of 2D blocks
__device__
int d_getGlobalIdx_3D_2D() {
int blockId = blockIdx.x + blockIdx.y * gridDim.x
+ gridDim.x * gridDim.y * blockIdx.z;
int threadId = blockId * (blockDim.x * blockDim.y)
+ (threadIdx.y * blockDim.x) + threadIdx.x;
return threadId;
}
//3D grid of 3D blocks
__device__
int d_getGlobalIdx_3D_3D() {
int blockId = blockIdx.x + blockIdx.y * gridDim.x
+ gridDim.x * gridDim.y * blockIdx.z;
int threadId = blockId * (blockDim.x * blockDim.y * blockDim.z)
+ (threadIdx.z * (blockDim.x * blockDim.y))
+ (threadIdx.y * blockDim.x) + threadIdx.x;
return threadId;
}
///////////////////////////////////////////////////////////////////////////
__device__ void d_LinearToCoordEnd(int* ret, size_t lin, int* dim, int rank, size_t size) {
size_t sm = lin;
size_t pp = size;
for (int i = rank - 1;i > 0; --i) {
pp /= dim[i];
ret[i] = sm / pp;
sm %= pp;
}
ret[0] = sm;
}
__device__ size_t d_CoordToLinearEnd(int* coo, int* dim, int rank) {
size_t pp = 1;
size_t sm = 0;
for (int i = 0; i < rank; ++i) {
sm += (coo[i] * pp);
pp *= dim[i];
}
return sm;
}
__device__ size_t d_CoordToLinear(int* coo, int* dim, int rank) {
size_t pp = 1;
size_t sm = 0;
for (int i = rank - 1; i >= 0; --i) {
sm += (coo[i] * pp);
pp *= dim[i];
}
return sm;
}
__device__ void d_LinearToCoord(int* ret, size_t lin, int* dim, int rank, size_t size) {
size_t sm = lin;
size_t pp = size;
for (int i = 0; i < rank - 1; ++i) {
pp /= dim[i];
ret[i] = sm / pp;
sm %= pp;
}
ret[rank - 1] = sm;
}
/*__device__ void d_LinearToSplitSubrankLimSz(size_t& part0, size_t& part1, size_t lin, int* dim, int rank, int rankA, size_t size, size_t sizeA) {
size_t sm = lin;
size_t pp = size;
size_t s = 0;
size_t p = sizeA;
int ret;// = new int[rank];
for (int i = 0; i < rank; ++i) {
pp /= dim[i];
ret = sm / pp;
p /= dim[i];
s += ret * p;
sm %= pp;
if (i == rankA - 1) {
part0 = s;
s = 0;
p = size / sizeA;
}
}
part1 = s;
}*/
__device__ void d_LinearToSplitSubrankLimSz(size_t& part0, size_t& part1, size_t lin, int* dim, int rank, int rankA, size_t size, size_t sizeA) {
size_t sm = lin;
size_t pp = size;
size_t s = 0;
size_t p = sizeA;
int ret;// = new int[rank];
int i;
for (i = 0; i < rankA; ++i) {
pp /= dim[i];
ret = sm / pp;
p /= dim[i];
s += ret * p;
sm %= pp;
}
part0 = s;
s = 0;
p = size / sizeA;//sizeB
for (; i < rank; ++i) {
pp /= dim[i];
ret = sm / pp;
p /= dim[i];
s += ret * p;
sm %= pp;
}
part1 = s;
}
__device__ void d_LinearToSplitSubrankLimSzEnd(size_t& part0, size_t& part1, size_t lin, int* dim, int rank, int rankA, size_t size, size_t sizeA) {
size_t sm = lin;
size_t pp = size;
size_t s = 0;
size_t p = sizeA;
int ret;// = new int[rank];
for (int i = rank - 1; i >= 0; --i) {
pp /= dim[i];
ret = sm / pp;
p /= dim[i];
s += ret * p;
sm %= pp;
if (i == rankA) {
part1 = s;
s = 0;
p = size / sizeA;
}
}
part0 = s;
}
__device__ void d_subArray(int* dst, int* src, int debDst, int finDst, int debSrc) {
for (int i = debDst; i < finDst; i++) {
dst[i] = src[i + debSrc];
}
}
template<typename T>
__global__ void d_prodTensor(T* C, int* dimC, int rankC, size_t size, T* A, int* dimA, int rankA, size_t sizeA, T* B, int* dimB, int rankB) {
size_t lin0, lin1;
size_t i = threadIdx.x + blockIdx.x * blockDim.x;
if (i < size) {
d_LinearToSplitSubrankLimSz(lin0, lin1, i, dimC, rankC, rankA, size, sizeA);
C[i] = A[lin0] * B[lin1];
}
}
template __global__ void d_prodTensor<float>(float* C, int* dimC, int rankC, size_t size, float* A, int* dimA, int rankA, size_t sizeA, float* B, int* dimB, int rankB);
template<typename T>
__global__ void d_prodTensorEnd(T* C, int* dimC, int rankC, size_t size, T* A, int* dimA, int rankA, size_t sizeA, T* B, int* dimB, int rankB) {
size_t lin0, lin1;
size_t i = threadIdx.x + blockIdx.x * blockDim.x;
if (i < size) {
d_LinearToSplitSubrankLimSzEnd(lin0, lin1, i, dimC, rankC, rankA, size, sizeA);
C[i] = A[lin0] * B[lin1];
}
}
template __global__ void d_prodTensorEnd<float>(float* C, int* dimC, int rankC, size_t size, float* A, int* dimA, int rankA, size_t sizeA, float* B, int* dimB, int rankB);
__device__ void d_minReverse(int* dim, int& rank, const int* dim0, int rank0, const int* dim1, int rank1, bool& rev) {
if (rank0 > rank1) {
rank = rank1;
for (int i = 0; i < rank1; ++i) dim[i] = dim1[i];
rev = true;
}
else if (rank0 < rank1) {
rank = rank0;
for (int i = 0; i < rank1; ++i) dim[i] = dim0[i];
rev = false;
}
else {// rank0 == rank1
rank = rank0;
for (int i = 0; i < rank0; i++) {
if (dim[i] > dim1[rank1 - 1 - i]) dim[i] = dim1[rank1 - 1 - i];
else dim[i] = dim0[i];
}
rev = false;
}
}
__device__ void d_reverseArray(int* arr, int sz) {
int* tmp;
//tmp = (int*)malloc(sz * sizeof(int));
tmp = new int[sz];
if (tmp == NULL) {
size_t limit = 0;
cudaDeviceGetLimit(&limit, cudaLimitStackSize);
printf("cudaLimitStackSize: %u | %d (%d) %d | \n", (unsigned)limit, blockIdx.x, blockDim.x, threadIdx.x);
cudaDeviceGetLimit(&limit, cudaLimitPrintfFifoSize);
printf("cudaLimitPrintfFifoSize: %u | %d (%d) %d | \n", (unsigned)limit, blockIdx.x, blockDim.x, threadIdx.x);
cudaDeviceGetLimit(&limit, cudaLimitMallocHeapSize);
printf("cudaLimitMallocHeapSize: %u | %d (%d) %d | \n", (unsigned)limit, blockIdx.x, blockDim.x, threadIdx.x);
printf("error Allocation in tmp = (int*)malloc(sz * sizeof(int)); | | ");
}int i = 0;
for (; i < sz / 2; i++) {
tmp[i] = arr[i];
arr[i] = arr[sz - 1 - i];
}
for (; i < sz; i++) {
arr[i] = tmp[sz - 1 - i];
}
//free(tmp);
delete[]tmp;
}
__device__ int d_min(int a, int b) {
if (a < b) return a;
return b;
}
__device__ void d_concatArray(int* dst, int* src0, int* src1, int debDst, int debSrc0, int finSrc0, int debSrc1, int finSrc1) {
int i = debDst;
for (int j = debSrc0; j < finSrc0; j++) {
dst[i++] = src0[j];
}
for (int j = debSrc1; j < finSrc1; j++) {
dst[i++] = src1[j];
}
}
__device__ void d_ConcatLinearToSplitSubrankLimSz(size_t& part0, size_t& part1, size_t lin, int* dim, int rank, int rankA, int rankB, size_t size, size_t sizeA, size_t sizeB, int* dM, int dMrank, size_t dMsize, int ind) {
size_t sm = lin;
size_t pp = size;
size_t s = 0;
size_t p = sizeA;
//size_t sz_dA = sizeA / dMsize;
int rankdA = rankA - dMrank;
int ret;
int i;
for (i = 0; i < rankdA; ++i) {
pp /= dim[i];
ret = sm / pp;
p /= dim[i];
s += ret * p;
sm %= pp;
}
size_t s1 = 0;
size_t pb = sizeB / dMsize;
for (; i < rank; ++i) {
pp /= dim[i];
ret = sm / pp;
pb /= dim[i];
s1 += ret * pb;
sm %= pp;
}
size_t smd = ind;
size_t ppb = dMsize;
//size_t pb = size / sz_dA;
pb = sizeB;
p = dMsize;
for (int j = 0;j < dMrank;j++) {
ppb /= dM[j];
ret = smd / ppb;
p /= dM[j];
s += ret * p;
pb /= dM[j];
s1 += ret * pb;
smd %= ppb;
}
//pp = size / sz_dA;
part0 = s;
part1 = s1;
}
__device__ void d_SplitLineardToSubrank(size_t& part0, size_t& part1, size_t lin, int* dim, int rank, int rankA, int rankB, size_t size, size_t sizeA, size_t sizeB, int* dM, int dMrank, size_t dMsize) {
size_t sm = lin;
size_t pp = size;
size_t s = 0;
size_t p = sizeA;
//size_t sz_dA = sizeA / dMsize;
int rankdA = rankA - dMrank;
int ret;
int i;
for (i = 0; i < rankdA; ++i) {
pp /= dim[i];
ret = sm / pp;
p /= dim[i];
s += ret * p;
sm %= pp;
}
size_t s1 = 0;
size_t pb = sizeB / dMsize;
for (; i < rank; ++i) {
pp /= dim[i];
ret = sm / pp;
pb /= dim[i];
s1 += ret * pb;
sm %= pp;
}
part0 = s;
part1 = s1;
}
__device__ void d_UnionConcatLinearSplitedSubrank(size_t& part0, size_t& part1, size_t p0, size_t p1, size_t size, size_t sizeB, int* dM, int dMrank, size_t dMsize, int ind) {
size_t s = p0;
size_t s1 = p1;
int ret;
size_t smd = ind;
size_t ppb = dMsize;
//size_t pb = size / sz_dA;
size_t pb = sizeB;
size_t p = dMsize;
for (int j = 0;j < dMrank;j++) {
ppb /= dM[j];
ret = smd / ppb;
p /= dM[j];
s += ret * p;
pb /= dM[j];
s1 += ret * pb;
smd %= ppb;
}
//pp = size / sz_dA;
part0 = s;
part1 = s1;
}
template<typename T>
__global__ void d_TensorContractnReverseProd(T* C, int* dimC, int rankC, size_t sizeC, T* A, int rankA, size_t sizeA, T* B, int rankB, size_t sizeB, int* dM, int dMrank, size_t dMsize) {
size_t p0, p1;
size_t lin0, lin1;
//size_t i = threadIdx.x + blockIdx.x * blockDim.x;
size_t i = d_getGlobalIdx_1D_1D();
if (i < sizeC) {
d_SplitLineardToSubrank(p0, p1, i, dimC, rankC, rankA, rankB, sizeC, sizeA, sizeB, dM, dMrank, dMsize);
C[i] = 0;
for (size_t k = 0; k < dMsize; k++) {
d_UnionConcatLinearSplitedSubrank(lin0, lin1, p0, p1, sizeC, sizeB, dM, dMrank, dMsize, k);
//d_ConcatLinearToSplitSubrankLimSz(lin0, lin1, i, dimC, rankC, rankA, rankB, sizeC, sizeA, sizeB, dM, dMrank, dMsize, k);
C[i] += A[lin0] * B[lin1];
}
}
}
template
__global__ void d_TensorContractnReverseProd<float>(float* C, int* dimC, int rankC, size_t size, float* A, int rankA, size_t sizeA, float* B, int rankB, size_t sizeB, int* dM, int dMrank, size_t dMsize);
__device__ void d_LinearTransformCoord(size_t& dst, size_t src, int* inversePerm, size_t sizeA, int rankDst, int rankSrc, int* dDst, int* dSrc) {
size_t sm = src;
size_t pp = sizeA;
size_t s = 0;
size_t p = 1;
int ret;// = new int[rank];
int i, j;
for (i = 0; i < rankSrc; ++i) {
pp /= dSrc[i];
ret = sm / pp;
p = 1;
for (j = inversePerm[i] + 1; j < rankDst;j++) {
p *= dDst[j];
}
s += ret * p;
sm %= pp;
}
dst = s;
if (s > sizeA) printf("I have a problem in LinearTransformCoord: s:%ld siez:%ld \n", s, sizeA);
}
template<typename T>
__global__ void d_PermLinearTransformCoord(T* C, int* dimC, int rankC, size_t sizeC, T* A, int* dimA, int rankA, size_t sizeA, int* invPerm) {
//size_t i = threadIdx.x + blockIdx.x * blockDim.x;
size_t i = d_getGlobalIdx_1D_1D();
if (i < sizeC) {
//printf("<i:%*ld ", 3, i);
size_t img = 0;
//printf("<i:%*ld, img:%*ld\n", 3, i, 3, img);
d_LinearTransformCoord(img, i, invPerm, sizeA, rankC, rankA, dimC, dimA);
//img = d_LinearTransformCoord(i, invPerm, sizeC, dimC, dimA, rankC);
if (img < sizeC)
C[img] = A[i];
else {
printf("something wrong in device: i:%ld , s:%ld\n", i, img);
}
}
}
template
__global__ void d_PermLinearTransformCoord<float>(float* C, int* dimC, int rankC, size_t size, float* A, int* dimA, int rankA, size_t sizeA, int* invPerm);
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#ifndef __D_CUDA_TENSOR_H__
#define __D_CUDA_TENSOR_H__
#include "cuda.h"
#include "cuda_runtime.h"
//#include "cuda_device_runtime_api.h"
//#include "/home/fanasina/progr_/ptens0neD/tensor/tensCuda/d_tensCuda.h"
#include "tensor/tensCuda/d_tensCuda.h"
//#1D grid of 1D blocks
__device__ int d_getGlobalIdx_1D_1D();
//#1D grid of 2D blocks
__device__ int d_getGlobalIdx_1D_2D();
//#1D grid of 3D blocks
__device__ int d_getGlobalIdx_1D_3D();
//#1D grid of 1D blocks
__device__ int d_getGlobalIdx_2D_1D();
//#1D grid of 2D blocks
__device__ int d_getGlobalIdx_2D_2D();
//2D grid of 3D blocks
__device__ int d_getGlobalIdx_2D_3D();
//#1D grid of 1D blocks
__device__ int d_getGlobalIdx_3D_1D();
//#1D grid of 2D blocks
__device__ int d_getGlobalIdx_3D_2D();
//#1D grid of 3D blocks
__device__ int d_getGlobalIdx_3D_3D();
extern cudaError_t cudaDeviceGetLimit(size_t* pValue, enum cudaLimit limit);
__device__ void d_LinearToCoordEnd(int* ret, size_t lin, int* dim, int rank, size_t size);
__device__ size_t d_CoordToLinearEnd(int* coo, int* dim, int rank);
__device__ size_t d_CoordToLinear(int* coo, int* dim, int rank);
__device__ void d_LinearToCoord(int* ret, size_t lin, int* dim, int rank, size_t size);
__device__ void d_subArray(int* dst, int* src, int debDst, int finDst, int debSrc);
__device__ void d_minReverse(int* dim, int& rank, const int* dim0, int rank0, const int* dim1, int rank1, bool& rev);
__device__ void d_reverseArray(int* arr, int sz);
__device__ int d_min(int a, int b);
__device__ void d_concatArray(int* dst, int* src0, int* src1, int debDst, int debSrc0, int finSrc0, int debSrc1, int finSrc1);
template<typename T>
__global__ void d_prodTensor(T* C, int* dimC, int rankC, size_t size, T* A, int* dimA, int rankA, size_t sizeA, T* B, int* dimB, int rankB);
template<typename T>
__global__ void d_prodTensorEnd(T* C, int* dimC, int rankC, size_t size, T* A, int* dimA, int rankA, size_t sizeA, T* B, int* dimB, int rankB);
template<typename T>
__global__ void d_TensorContractnReverseProd(T* C, int* dimC, int rankC, size_t size, T* A, int rankA, size_t sizeA, T* B, int rankB, size_t sizeB, int* dM, int dMrank, size_t dMsize);
template<typename T>
__global__ void d_PermLinearTransformCoord(T* C, int* dimC, int rankC, size_t sizeC, T* A, int* dimA, int rankA, size_t sizeA, int* invPerm);
#endif
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#include <cstdio>
#include <cstdlib>
#include <stdexcept>
#include <vector>
#include <algorithm>
//#include "/home/fanasina/progr_/ptens0neD/tensor/tens0neD/tens0neD.h"
//#include "/home/fanasina/progr_/ptens0neD/tensor/tensCuda/tensCuda.h"
#include "tensor/tensCuda/tensCuda.h"
template<typename T>
void cudaTensorProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1) {
add(M.Dim, M0.Dim, M1.Dim);
M.initTensor();
int* d_imM, * d_imM0, * d_imM1;
cudaError_t errCu = cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM1, M1.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM1, M1.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM1, M1.Dim.dim, M1.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM1, M1.Dim.dim, M1.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
T* e, * e0, * e1;
errCu = cudaMalloc((void**)&e, M.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e, M.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e1, M1.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e1, M1.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e1, M1.elements, M1.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e1, M1.elements, M1.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
int BLOCKSIZE = 256;//1024;
int DIMBLOCKS = (M.Dim.size + BLOCKSIZE - 1) / BLOCKSIZE;
//int DIMBLOCKS = (M.Dim.size) / BLOCKSIZE;
d_prodTensor<T> << < DIMBLOCKS, BLOCKSIZE >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, d_imM0, M0.Dim.rank, M0.Dim.size, e1, d_imM1, M1.Dim.rank);
errCu = cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e1);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e1) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM1);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM1) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
}
//template void cudaTensorProd<double>(Tensor<double>& M, const Tensor<double>& M1, const Tensor<double>& M0);
template void cudaTensorProd<float>(Tensor<float>& M, const Tensor<float>& M1, const Tensor<float>& M0);
template<typename T>
void cudaTensorProdEnd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1) {
add(M.Dim, M0.Dim, M1.Dim);
M.initTensor();
int* d_imM, * d_imM0, * d_imM1;
cudaError_t errCu = cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM1, M1.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM1, M1.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM1, M1.Dim.dim, M1.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM1, M1.Dim.dim, M1.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
T* e, * e0, * e1;
errCu = cudaMalloc((void**)&e, M.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e, M.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e1, M1.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e1, M1.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e1, M1.elements, M1.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e1, M1.elements, M1.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
size_t BLOCKSIZE = 1024;
size_t DIMBLOCKS = (M.Dim.size + BLOCKSIZE - 1) / BLOCKSIZE;
d_prodTensorEnd<T> << < DIMBLOCKS, BLOCKSIZE >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, d_imM0, M0.Dim.rank, M0.Dim.size, e1, d_imM1, M1.Dim.rank);
cudaDeviceSynchronize();
errCu = cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e1);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e1) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM1);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM1) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
}
//template void cudaTensorProd<double>(Tensor<double>& M, const Tensor<double>& M1, const Tensor<double>& M0);
template void cudaTensorProdEnd<float>(Tensor<float>& M, const Tensor<float>& M1, const Tensor<float>& M0);
template<typename T>
void cudapermuteTensor(Tensor<T>& M, const Tensor<T>& M0, permutation p) {
if (p.size == M0.Dim.rank) {
M.Dim.rank = M0.Dim.rank;
M.Dim.size = M0.Dim.size;
M.Dim.initDim();
M.initTensor();
p.permute(M.Dim.dim, M0.Dim.dim);
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start);
int* d_imM, * d_imM0;
cudaError_t errCu = cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
T* e, * e0;
errCu = cudaMalloc((void**)&e, M.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e, M.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
size_t BLOCKSIZE = 256; //1024;//512;
size_t DIMBLOCKS = (M.Dim.size + BLOCKSIZE - 1) / BLOCKSIZE;
dim3 blckSZ, gridSZ;
blckSZ.x = BLOCKSIZE;
gridSZ.x = DIMBLOCKS;
int* invP, * d_invP;
invP = (int*)malloc(M.Dim.rank * sizeof(int));
inverseArray(invP, p.perm, M.Dim.rank);
errCu = cudaMalloc((void**)&d_invP, M.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_invP, M.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_invP, invP, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_invP, invP, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
//printf("size: %ld\n", M.Dim.size);
//d_prodTensorEnd<T> << < DIMBLOCKS, BLOCKSIZE >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, d_imM0, M0.Dim.rank, e1, d_imM1, M1.Dim.rank);
//d_TensorContractnReverseProd<T> << < DIMBLOCKS, BLOCKSIZE >> > (e, d_imM, M.Dim.rank, M.Dim.size, d_imdM, dM.rank, dM.size, e0, d_imM0, M0.Dim.rank, e1, d_imM1, M1.Dim.rank, nestingDepth);
//d_TensorContractnReverseProd<T> << < gridSZ, blckSZ, 0, 0 >> > (e, d_imM, M.Dim.rank, M.Dim.size, d_imdM, dM.rank, dM.size, e0, d_imM0, M0.Dim.rank, e1, d_imM1, M1.Dim.rank, nestingDepth);
d_PermLinearTransformCoord<T> << < gridSZ, blckSZ, 0, 0 >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, d_imM0, M0.Dim.rank, M0.Dim.size, d_invP);
//d_PermLinearTransformCoord<T> << < gridSZ, blckSZ, 0, 0 >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, d_imM0, M0.Dim.rank, M0.Dim.size, p.perm);
//cudaDeviceSynchronize();
errCu = cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
cudaEventRecord(stop);
cudaEventSynchronize(stop);
float milliseconds = 0;
cudaEventElapsedTime(&milliseconds, start, stop);
printf("ellaps time cuda permute tensor: %f ms\n", milliseconds);
}
}
template
void cudapermuteTensor(Tensor<float>& M, const Tensor<float>& M0, permutation p);
// strict match contract ! if no strict, we take the minimum
template<typename T>
void cudaTensorContractNestProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M11, int nestingDepth, bool strict) {
int perm[M11.Dim.rank];
struct Tensor<T> M1;
if (scanPermuteMatchContractTensorfromSrcToDst(perm, M11, M0, nestingDepth)) {
for (int i = 0; i < M11.Dim.rank; i++) printf(" %d[%d] ", i, perm[i]); printf(": last perm \n");
struct permutation p(M11.Dim.rank, perm);
permuteTensor(M1, M11, p);
M1.Dim.print();
}
else {
printf("Failed in Deep = %d\n", nestingDepth);
//throw std::check_ProdTensor(" Failed imbrication order in Multiplication matrix ");
throw std::invalid_argument(" Failed imbrication order in Multiplication matrix ");
exit(1);
}
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start);
int len0 = M0.Dim.rank - nestingDepth;
int len1 = M1.Dim.rank - nestingDepth;
int* tsub0 = new int[len0];
int* tsub1 = new int[len1];
int* tDk1 = new int[nestingDepth];
int* tDk0 = new int[nestingDepth];
subArray(tsub0, M0.Dim.dim, 0, len0, 0);
subArray(tsub1, M1.Dim.dim, 0, len1, nestingDepth);
subArray(tDk1, M1.Dim.dim, 0, nestingDepth, 0);
subArray(tDk0, M0.Dim.dim, 0, nestingDepth, len0);
dimension dSub0(len0, tsub0);
dimension dSub1(len1, tsub1);
dimension dM1(nestingDepth, tDk1);
dimension dM0(nestingDepth, tDk0);
dimension dM(dM0);
//bool rev;
//minReverse(dM, dM0, dM1, rev);
//if (rev) reverseArray(dM.dim, dM.rank);
//max(dM, dM0, dM1);
add(M.Dim, dSub0, dSub1);
M.initTensor();
int* d_imM, * d_imM0, * d_imM1, * d_imdM;
cudaError_t errCu = cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM, M.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imdM, dM.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imdM, dM.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM0, M0.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&d_imM1, M1.Dim.rank * sizeof(int));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&d_imM1, M1.Dim.rank * sizeof(int)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM, M.Dim.dim, M.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imdM, dM.dim, dM.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imdM, dM.dim, dM.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM0, M0.Dim.dim, M0.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(d_imM1, M1.Dim.dim, M1.Dim.rank * sizeof(int), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(d_imM1, M1.Dim.dim, M1.Dim.rank * sizeof(int), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
T* e, * e0, * e1;
errCu = cudaMalloc((void**)&e, M.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e, M.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e0, M0.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMalloc((void**)&e1, M1.Dim.size * sizeof(T));
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMalloc((void**)&e1, M1.Dim.size * sizeof(T)) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e0, M0.elements, M0.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaMemcpy(e1, M1.elements, M1.Dim.size * sizeof(T), cudaMemcpyHostToDevice);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(e1, M1.elements, M1.Dim.size * sizeof(T), cudaMemcpyHostToDevice) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
size_t BLOCKSIZE = 256; //1024;//512;
size_t DIMBLOCKS = (M.Dim.size + BLOCKSIZE - 1) / BLOCKSIZE;
dim3 blckSZ, gridSZ;
blckSZ.x = BLOCKSIZE;
gridSZ.x = DIMBLOCKS;
//d_prodTensorEnd<T> << < DIMBLOCKS, BLOCKSIZE >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, d_imM0, M0.Dim.rank, e1, d_imM1, M1.Dim.rank);
//d_TensorContractnReverseProd<T> << < DIMBLOCKS, BLOCKSIZE >> > (e, d_imM, M.Dim.rank, M.Dim.size, d_imdM, dM.rank, dM.size, e0, d_imM0, M0.Dim.rank, e1, d_imM1, M1.Dim.rank, nestingDepth);
//d_TensorContractnReverseProd<T> << < gridSZ, blckSZ, 0, 0 >> > (e, d_imM, M.Dim.rank, M.Dim.size, d_imdM, dM.rank, dM.size, e0, d_imM0, M0.Dim.rank, e1, d_imM1, M1.Dim.rank, nestingDepth);
d_TensorContractnReverseProd<T> << < gridSZ, blckSZ, 0, 0 >> > (e, d_imM, M.Dim.rank, M.Dim.size, e0, M0.Dim.rank, M0.Dim.size, e1, M1.Dim.rank, M1.Dim.size, d_imdM, dM.rank, dM.size);
//cudaDeviceSynchronize();
errCu = cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaMemcpy(M.elements, e, M.Dim.size * sizeof(T), cudaMemcpyDeviceToHost) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(e1);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(e1) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM0);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM0) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
errCu = cudaFree(d_imM1);
if (cudaSuccess != errCu) {
printf("device fnc failed cudaFree(d_imM1) \n ErrorCuda: %d : %s\n", errCu, cudaGetErrorString(errCu));
exit(errCu);
}
cudaEventRecord(stop);
cudaEventSynchronize(stop);
float milliseconds = 0;
cudaEventElapsedTime(&milliseconds, start, stop);
printf("ellaps time cuda prod contract prod: %f ms\n", milliseconds);
}
template
void cudaTensorContractNestProd<float>(Tensor<float>& M, const Tensor<float>& M0, const Tensor<float>& M1, int nestingDepth, bool strict);
//template void cudaTensorContractnReverseProd<double>(Tensor<double>& M, const Tensor<double>& M0, const Tensor<double>& M1, int nestingDepth);
+31
View File
@@ -0,0 +1,31 @@
#ifndef __TENS_CUDA_H__
#define __TENS_CUDA_H__
#include <cstdio>
#include <cstdlib>
#include <stdexcept>
//#include "/home/fanasina/progr_/ptens0neD/tensor/tens0neD/tens0neD.h"
#include "tensor/tens0neD/tens0neD.h"
//#include "/home/fanasina/progr_/ptens0neD/tensor/tensCuda/d_tensCuda.h"
#include "tensor/tensCuda/d_tensCuda.h"
//#include "dimension/dimension.h"
template<typename T>
struct Tensor;
template<typename T>
void cudaTensorContractNestProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth, bool strict = true);
template<typename T>
void cudaTensorProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1);
template<typename T>
void cudaTensorProdEnd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1);
template<typename T>
void cudapermuteTensor(Tensor<T>& M, const Tensor<T>& M0, permutation p);
#endif