add simple test, and mv permutation test, update README
This commit is contained in:
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#include <cstdio>
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#include <cstdlib>
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#include <stdexcept>
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#include <vector>
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#include <algorithm>
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//#include "/home/fanasina/progr_/ptens0neD/tensor/tens0neD/tens0neD.h"
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#include "tensor/tens0neD/tens0neD.h"
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//#include "include/tens0neD.h"
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//#include "cudatensor.h"
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//#include "/home/fanasina/progr_/ptens0neD/permutation/permutation.h"
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#include "permutation/permutation.h"
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template<typename T>
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void transform(Tensor<T>& Dst, const Tensor<T>& Src, int* perm, int sz) {
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transform(Dst.Dim, Src.Dim, perm, sz);
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dimension dsrc = Src.Dim;
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dimension ddst = Dst.Dim;
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int coor[dsrc.rank];
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int dcoor[ddst.rank], ldst;
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for (int i = 0; i < Src.Dim.size; i++) {
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dsrc.LinearToCoord(coor, i);
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for (int j = 0; j < dsrc.rank; j++) dcoor[j] = coor[perm[j]];
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ldst = ddst.CoordToLinear(dcoor);
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Dst.elements[ldst] = Src.elements[i];
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}
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}
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template void transform<float>(Tensor<float>& Dst, const Tensor<float>& Src, int* perm, int sz);
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template void transform<double>(Tensor<double>& Dst, const Tensor<double>& Src, int* perm, int sz);
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template<typename T>
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Tensor<T>& Tensor<T>::operator=(const Tensor<T>& M) {
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Dim = M.Dim;
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for (int i = 0; i < Dim.size; ++i) elements[i] = M.elements[i];
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return *this;
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}
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template<typename T>
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Tensor<T>& Tensor<T>::operator*=(const T& val) {
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//for (int i = 0; i < rank.size; ++i) elements[i] *= val;
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return *this;
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}
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template<typename T>
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Tensor<T>& operator*(const Tensor<T>& M0, const Tensor<T>& M1) {
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struct dimension d; add(d, M0.Dim, M1.Dim);
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Tensor<T> Mret(d);
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for (int i = 0; i < M0.Dim.size; ++i) Mret.elements[i] = M0.elements[i];
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Mret.Dim += M0.Dim;
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return Mret;
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}
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void subArray(int* dst, int* src, int debDst, int finDst, int debSrc) {
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for (int i = debDst; i < finDst; i++) {
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dst[i] = src[i + debSrc];
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}
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}
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void concatArray(int* dst, int* src0, int* src1, int debDst, int debSrc0, int finSrc0, int debSrc1, int finSrc1) {
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int i = debDst;
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for (int j = debSrc0; j < finSrc0; j++) {
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dst[i++] = src0[j];
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}
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for (int j = debSrc1; j < finSrc1; j++) {
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dst[i++] = src1[j];
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}
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}
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template<typename T>
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void Tensor<T>::initVal(T val) {
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int* coord = new int[Dim.rank];
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T pp, mult = 0.5;
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for (int i = 0; i < Dim.size; i++) {
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Dim.LinearToCoord(coord, i);
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elements[i] = val;
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pp = mult;
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for (int j = 0; j < Dim.rank; j++) {
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elements[i] += (coord[j] + 1) * pp;
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pp *= mult;
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}
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}
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}
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template
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void Tensor<float>::initVal(float val);
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template
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void Tensor<double>::initVal(double val);
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template<typename T>
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void Tensor<T>::print() {
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Dim.print();
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int* coord = new int[Dim.rank];
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int begin = 0, end = Dim.rank - 1;
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//int beginInv = Dim.rank - 1, endInv = 0;
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int (*iter)(int) = incr;
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//int (*iterInv)(int) = decr;
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bool (*cond)(int, int) = isLessEqThan;
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//bool (*condInv)(int, int) = isGreatEqThan;
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if (Dim.endian == false) {
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begin = Dim.rank - 1; end = 0;
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//beginInv = 0; endInv = Dim.rank - 1;
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iter = decr; cond = isGreatEqThan;
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//iterInv = incr; condInv = isLessEqThan;
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}
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for (int i = 0; i < Dim.size; i++) {
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Dim.LinearToCoord(coord, i);
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//if (coord[Dim.rank - 1] == 0) {
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if (coord[begin] == 0) {
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for (int j = begin; cond(j, end); j = iter(j)) {
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//for (int j = Dim.rank - 1; j >= 0; j--) {
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if (coord[j] == 0) {
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printf("(");
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}
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else break;
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}
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}
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//printf(" ");for (int j = 0; j < Dim.rank; j++) printf("[%d]", coord[j]); printf(" ");
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//printf(" "); for (int j = beginInv; condInv(j, endInv); j = iterInv(j)) printf("[%d]", coord[j]); printf(" ");
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//printf(" "); for (int k = beginInv; condInv(k, endInv); k = iterInv(k)) { printf("[%d]", coord[k]); } printf(" ");
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printf(" %.6f ", elements[i]);
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//if (coord[Dim.rank - 1] == Dim.dim[Dim.rank - 1] - 1) {
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if (coord[begin] == Dim.dim[begin] - 1) {
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for (int j = begin; cond(j, end); j = iter(j)) {
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//for (int j = Dim.rank - 1; j >= 0; j--) {
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if (coord[j] == Dim.dim[j] - 1) {
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printf(")");
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}
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else break;
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}
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}
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}
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printf("\n");
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}
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template
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void Tensor<float>::print();
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template
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void Tensor<double>::print();
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template<typename T>
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void tensorProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1) {
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add(M.Dim, M0.Dim, M1.Dim);
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M.initTensor();
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int* coord = new int[M.Dim.rank];
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int* coord0 = new int[M0.Dim.rank], lin0;
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int* coord1 = new int[M1.Dim.rank], lin1;
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for (int i = 0; i < M.Dim.size; i++) {
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M.Dim.LinearToCoord(coord, i);
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subArray(coord0, coord, 0, M0.Dim.rank, 0);
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subArray(coord1, coord, 0, M1.Dim.rank, M0.Dim.rank);
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lin0 = (M0.Dim).CoordToLinear(coord0);
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lin1 = (M1.Dim).CoordToLinear(coord1);
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M.elements[i] = M0.elements[lin0] * M1.elements[lin1];
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}
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}
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template
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void tensorProd<double>(Tensor<double>& M, const Tensor<double>& M1, const Tensor<double>& M0);
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template
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void tensorProd<float>(Tensor<float>& M, const Tensor<float>& M1, const Tensor<float>& M0);
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bool checkMatchProdTensor(const dimension& d0, const dimension& d1, int nestingDepth) {
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if (d0.rank <= nestingDepth || d1.rank <= nestingDepth) return false;
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for (int i = 0; i < nestingDepth;i++) {
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if (d1.dim[i] != d0.dim[d0.rank - nestingDepth + i]) return false;
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}
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return true;
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}
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bool checkMatchProdTensorReverse(const dimension& d0, const dimension& d1, int nestingDepth) {
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if (d0.rank <= nestingDepth || d1.rank <= nestingDepth) return false;
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for (int i = 0; i < nestingDepth;i++) {
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if (d1.dim[i] != d0.dim[d0.rank - 1 - i]) return false;
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}
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return true;
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}
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void extractDimNestingDepth(dimension& dM, const dimension& d0, const dimension& d1, int nestingDepth) {
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int len0 = d0.rank - nestingDepth;
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int len1 = d1.rank - nestingDepth;
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int* tsub0 = new int[len0];
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int* tsub1 = new int[len1];
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int* tDk1 = new int[nestingDepth];
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int* tDk0 = new int[nestingDepth];
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subArray(tsub0, d0.dim, 0, len0, 0);
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subArray(tsub1, d1.dim, 0, len1, nestingDepth);
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subArray(tDk1, d1.dim, 0, nestingDepth, 0);
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subArray(tDk0, d0.dim, 0, nestingDepth, len0);
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dimension dSub0(len0, tsub0);
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dimension dSub1(len1, tsub1);
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dimension dM1(nestingDepth, tDk1);
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dimension dM0(nestingDepth, tDk0);
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min(dM, dM0, dM1);
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//max(dM, dM0, dM1);
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}
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// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xl = y0,x{l+1}=y1, x{n}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
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// M[x0,x1,x3..xl x{l+1}...xn] X M[xn,x{n-1},x{n-2}...xl y{l+1} ..ym] = M[x0,x1..xly{l+1}...y{n+m-2l}] (deep = l > 0)
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//M[[i][j]]=sum_{[k]}M0[[i][k]]*M[[k][j]]
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template<typename T>
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void tensorContractnProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth) {
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if (!checkMatchProdTensor(M0.Dim, M1.Dim, nestingDepth)) {
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printf("Deep = %d\n", nestingDepth);
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//throw std::check_ProdTensor(" Failed imbrication order in Multiplication matrix ");
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//throw std::invalid_argument(" Failed imbrication order in Multiplication matrix ");
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}
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int len0 = M0.Dim.rank - nestingDepth;
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int len1 = M1.Dim.rank - nestingDepth;
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int* tsub0 = new int[len0];
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int* tsub1 = new int[len1];
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int* tDk1 = new int[nestingDepth];
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int* tDk0 = new int[nestingDepth];
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subArray(tsub0, M0.Dim.dim, 0, len0, 0);
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subArray(tsub1, M1.Dim.dim, 0, len1, nestingDepth);
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subArray(tDk1, M1.Dim.dim, 0, nestingDepth, 0);
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subArray(tDk0, M0.Dim.dim, 0, nestingDepth, len0);
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dimension dSub0(len0, tsub0);
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dimension dSub1(len1, tsub1);
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dimension dM1(nestingDepth, tDk1);
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dimension dM0(nestingDepth, tDk0);
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dimension dM;
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min(dM, dM0, dM1);
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//max(dM, dM0, dM1);
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add(M.Dim, dSub0, dSub1);
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M.initTensor();
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int* coord = new int[M.Dim.rank];
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int* coord0 = new int[len0], lin0;
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int* coord1 = new int[len1], lin1;
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int* coordM0 = new int[M0.Dim.rank];
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int* coordM1 = new int[M1.Dim.rank];
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int* Koord = new int[nestingDepth];
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for (int i = 0; i < M.Dim.size; i++) {
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M.Dim.LinearToCoord(coord, i);
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subArray(coord0, coord, 0, len0, 0);
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subArray(coord1, coord, 0, len1, len0);
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M.elements[i] = 0;
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for (int k = 0; k < dM.size; k++) {
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dM.LinearToCoord(Koord, k);
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concatArray(coordM0, coord0, Koord, 0, 0, len0, 0, nestingDepth);
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concatArray(coordM1, Koord, coord1, 0, 0, nestingDepth, 0, len1);
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lin0 = (M0.Dim).CoordToLinear(coordM0);
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lin1 = (M1.Dim).CoordToLinear(coordM1);
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M.elements[i] += M0.elements[lin0] * M1.elements[lin1];
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}
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}
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}
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template
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void tensorContractnProd<float>(Tensor<float>& M, const Tensor<float>& M0, const Tensor<float>& M1, int nestingDepth);
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template
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void tensorContractnProd<double>(Tensor<double>& M, const Tensor<double>& M0, const Tensor<double>& M1, int nestingDepth);
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void reverseDim(dimension& d, const dimension& d0) {
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d.rank = d0.rank;
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d.size = d0.size;
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if (d.dim != NULL) free(d.dim);
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d.dim = (int*)malloc(d.rank * sizeof(int));
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for (int i = 0; i < d.rank; i++) d.dim[i] = d0.dim[d.rank - i - 1];
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}
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template<typename T>
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void reverseTensor(Tensor<T>& M, const Tensor<T>& M0) {
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reverseDim(M.Dim, M0.Dim);
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size_t id;
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int coor[M0.Dim.rank];
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for (size_t i = 0; i < M.Dim.size; i++) {
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M0.Dim.LinearToCoord(coor, i);
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reverseArray(coor, M0.Dim.rank);
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id = M.Dim.CoordToLinear(coor);
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M.elements[id] = M0.elements[i];
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}
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}
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// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xn = y0,x{n-1}=y1, x{n-l}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
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// M[x0,x1,x3..xl x{l+1}..xn] X M[xn,x{n-1},..x{l+1}xl y{l+1}..ym] = M[x0,x1..xly{l+1}...y{n+m-2l}] (deep = l > 0)
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//M[[i][j]]=sum_{[k]}M0[[i][k]]*M[[k][j]]
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template<typename T>
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void tensorContractnReverseProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth) {
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if (!checkMatchProdTensorReverse(M0.Dim, M1.Dim, nestingDepth)) {
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printf("Failed in Deep = %d\n", nestingDepth);
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//throw std::check_ProdTensor(" Failed imbrication order in Multiplication matrix ");
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//throw std::invalid_argument(" Failed imbrication order in Multiplication matrix ");
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}
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int len0 = M0.Dim.rank - nestingDepth;
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int len1 = M1.Dim.rank - nestingDepth;
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int* tsub0 = new int[len0];
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int* tsub1 = new int[len1];
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int* tDk1 = new int[nestingDepth];
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int* tDk0 = new int[nestingDepth];
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subArray(tsub0, M0.Dim.dim, 0, len0, 0);
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subArray(tsub1, M1.Dim.dim, 0, len1, nestingDepth);
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subArray(tDk1, M1.Dim.dim, 0, nestingDepth, 0);
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subArray(tDk0, M0.Dim.dim, 0, nestingDepth, len0);
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dimension dSub0(len0, tsub0);
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dimension dSub1(len1, tsub1);
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dimension dM1(nestingDepth, tDk1);
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dimension dM0(nestingDepth, tDk0);
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dimension dM;
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bool rev;
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minReverse(dM, dM0, dM1, rev);
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if (rev) reverseArray(dM.dim, dM.rank);
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//max(dM, dM0, dM1);
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add(M.Dim, dSub0, dSub1);
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M.initTensor();
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int* coord = new int[M.Dim.rank];
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int* coord0 = new int[len0], lin0;
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int* coord1 = new int[len1], lin1;
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int* coordM0 = new int[M0.Dim.rank];
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int* coordM1 = new int[M1.Dim.rank];
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int* Koord = new int[nestingDepth];
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for (int i = 0; i < M.Dim.size; i++) {
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M.Dim.LinearToCoord(coord, i);
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subArray(coord0, coord, 0, len0, 0);
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subArray(coord1, coord, 0, len1, len0);
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M.elements[i] = 0;
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for (int k = 0; k < dM.size; k++) {
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dM.LinearToCoord(Koord, k);
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concatArray(coordM0, coord0, Koord, 0, 0, len0, 0, nestingDepth);
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reverseArray(Koord, nestingDepth);
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concatArray(coordM1, Koord, coord1, 0, 0, nestingDepth, 0, len1);
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lin0 = (M0.Dim).CoordToLinear(coordM0);
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lin1 = (M1.Dim).CoordToLinear(coordM1);
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M.elements[i] += M0.elements[lin0] * M1.elements[lin1];
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}
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}
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}
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template
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void tensorContractnReverseProd<float>(Tensor<float>& M, const Tensor<float>& M0, const Tensor<float>& M1, int nestingDepth);
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template
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void tensorContractnReverseProd<double>(Tensor<double>& M, const Tensor<double>& M0, const Tensor<double>& M1, int nestingDepth);
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template<typename T>
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void permuteTensorDef(Tensor<T>& M, const Tensor<T>& M0, permutation p) {
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if (p.size == M0.Dim.rank) {
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M.Dim.rank = M0.Dim.rank;
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M.Dim.size = M0.Dim.size;
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M.Dim.initDim();
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M.initTensor();
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//permuteArray(M.Dim.dim, M0.Dim.dim, p);
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//for (int i = 0; i < p.size; i++) { M.Dim.dim[i] = M0.Dim.dim[p.perm[i]]; }
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p.permute(M.Dim.dim, M0.Dim.dim);
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size_t img;
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int coor[p.size];
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int rooc[p.size];
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for (size_t i = 0; i < M.Dim.size;i++) {
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M0.Dim.LinearToCoord(coor, i);
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p.permute(rooc, coor);
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img = M.Dim.CoordToLinear(rooc);
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if (img >= M.Dim.size) printf(" i: %ld vs img:%ld size: %ld\n", i, img, M.Dim.size);
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M.elements[img] = M0.elements[i];
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}
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}
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}
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template
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void permuteTensorDef(Tensor<float>& M, const Tensor<float>& M0, permutation p);
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||||
|
||||
template<typename T>
|
||||
bool scanPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<T>& Msecond, const Tensor<T>& Mfirst, int contractNest) {
|
||||
if (contractNest < Msecond.Dim.rank && contractNest < Mfirst.Dim.rank) {
|
||||
std::vector<int> founded;
|
||||
int begin = Mfirst.Dim.rank - contractNest, tmp;
|
||||
for (int i = 0; i < Msecond.Dim.rank;i++) perm[i] = i;
|
||||
for (int i = begin; i < Mfirst.Dim.rank; i++) {
|
||||
for (int j = 0; j < Msecond.Dim.rank;j++) {
|
||||
if (std::find(founded.begin(), founded.end(), perm[j]) == founded.end()) {// not found
|
||||
if (Msecond.Dim.dim[perm[j]] == Mfirst.Dim.dim[i]) {
|
||||
founded.push_back(perm[j]);
|
||||
tmp = perm[i - begin];
|
||||
perm[i - begin] = perm[j];
|
||||
perm[j] = tmp;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return (founded.size() == contractNest);
|
||||
}
|
||||
return false;
|
||||
}
|
||||
template
|
||||
bool scanPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<float>& Msecond, const Tensor<float>& Mfirst, int contractNest);
|
||||
|
||||
|
||||
template<typename T>
|
||||
bool scanInvPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<T>& Msecond, const Tensor<T>& Mfirst, int contractNest) {
|
||||
if (contractNest < Msecond.Dim.rank && contractNest < Mfirst.Dim.rank) {
|
||||
std::vector<int> founded;
|
||||
int begin = Mfirst.Dim.rank - contractNest, tmp;
|
||||
for (int i = 0; i < Msecond.Dim.rank;i++) perm[i] = i;
|
||||
for (int i = begin; i < Mfirst.Dim.rank; i++) {
|
||||
for (int j = 0; j < Msecond.Dim.rank;j++) {
|
||||
if (std::find(founded.begin(), founded.end(), j) == founded.end()) {// not found
|
||||
if (Msecond.Dim.dim[j] == Mfirst.Dim.dim[perm[i - begin]]) {
|
||||
founded.push_back(j);
|
||||
tmp = perm[i - begin];
|
||||
perm[i - begin] = j;
|
||||
perm[j] = tmp;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return (founded.size() == contractNest);
|
||||
}
|
||||
return false;
|
||||
}
|
||||
template
|
||||
bool scanInvPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<float>& Msecond, const Tensor<float>& Mfirst, int contractNest);
|
||||
|
||||
|
||||
void LinearTransformCoord(size_t& dst, size_t src, int* inversePerm, size_t Msize, dimension dDst, dimension dSrc) {
|
||||
size_t sm = src;
|
||||
size_t pp = Msize;
|
||||
size_t s = 0;
|
||||
size_t p = 1;
|
||||
int ret;// = new int[rank];
|
||||
int i;
|
||||
for (i = 0; i < dSrc.rank; ++i) {
|
||||
pp /= dSrc.dim[i];
|
||||
ret = sm / pp;
|
||||
p = 1;
|
||||
for (int j = inversePerm[i] + 1; j < dDst.rank;j++) {
|
||||
p *= dDst.dim[j];
|
||||
}
|
||||
s += ret * p;
|
||||
|
||||
sm %= pp;
|
||||
|
||||
}
|
||||
dst = s;
|
||||
if (s > Msize) printf("I have a problem in LinearTransformCoord: s:%ld siez:%ld \n", s, Msize);
|
||||
|
||||
}
|
||||
|
||||
|
||||
template<typename T>
|
||||
void permuteTensor(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();
|
||||
|
||||
if (p.size == M0.Dim.rank) p.permute(M.Dim.dim, M0.Dim.dim);
|
||||
else {
|
||||
printf("something wrong perm, not the same size as M0.Dim.rank\n");
|
||||
exit(1);
|
||||
}
|
||||
size_t img = 0;
|
||||
printf("in permuteTensor:\n");
|
||||
M0.Dim.print();
|
||||
M.Dim.print();
|
||||
setInit se(M.Dim.rank, 0);
|
||||
int invP[M.Dim.rank];
|
||||
inverseArray(invP, p.perm, M.Dim.rank);
|
||||
for (size_t i = 0; i < M.Dim.size;i++) {
|
||||
//LinearTransformCoord(img, i, p.perm, M.Dim.size, M.Dim, M0.Dim);
|
||||
LinearTransformCoord(img, i, invP, M.Dim.size, M.Dim, M0.Dim);
|
||||
M.elements[img] = M0.elements[i];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template
|
||||
void permuteTensor(Tensor<float>& M, const Tensor<float>& M0, permutation p);
|
||||
|
||||
@@ -0,0 +1,114 @@
|
||||
#ifndef __TENS_0NE_D_H__
|
||||
#define __TENS_0NE_D_H__
|
||||
|
||||
#include <cstdio>
|
||||
#include <cstdlib>
|
||||
|
||||
#include <stdexcept>
|
||||
|
||||
//#include "tensor.h"
|
||||
//#include "cudatensor.h"
|
||||
//#include "/home/fanasina/progr_/ptens0neD/dimension/dimension.h"
|
||||
//#include "/home/fanasina/progr_/ptens0neD/permutation/permutation.h"
|
||||
//#include "/home/fanasina/progr_/ptens0neD/tensor/tensCuda/tensCuda.h"
|
||||
|
||||
#include "dimension/dimension.h"
|
||||
#include "permutation/permutation.h"
|
||||
#include "tensor/tensCuda/tensCuda.h"
|
||||
|
||||
template<typename T>
|
||||
struct Tensor {
|
||||
struct dimension Dim;
|
||||
T* elements;
|
||||
Tensor(struct dimension dm = dimension(1)) {
|
||||
Dim = dm;
|
||||
//elements = new T[Dim.size];
|
||||
elements = (T*)malloc(Dim.size * sizeof(T));
|
||||
}
|
||||
void initTensor() {
|
||||
//delete[]elements;
|
||||
//elements = new T[Dim.size];
|
||||
if (elements != NULL)
|
||||
free(elements);
|
||||
elements = (T*)malloc(Dim.size * sizeof(T));
|
||||
}
|
||||
void initVal(T val); // { for (int i = 0; i < Dim.size; i++) elements[i] = val + 0.001f * i; }
|
||||
void print();
|
||||
Tensor& operator=(const Tensor& M);
|
||||
Tensor& operator*=(const T& val);
|
||||
template<typename Ty>
|
||||
friend Tensor<Ty>& operator*(const Tensor<Ty>& M0, const Tensor<Ty>& M1);
|
||||
|
||||
// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xl = y0,x{l+1}=y1, x{n}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
|
||||
// M[x0,x1,x3..xl x{l+1}...xn] X M[xn,x{n-1},x{n-2}...xl y{l+1} ..ym] = M[x0,x1..xly{l+1}...y{n+m-2l}] (deep = l > 0)
|
||||
template<typename Ty>
|
||||
friend void tensorContractnProd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1, int nestingDepth);
|
||||
|
||||
// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xn = y0,x{n-1}=y1, x{n-l}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
|
||||
// M[x0,x1,x3..xl x{l+1}..xn] X M[xn,x{n-1},..x{l+1}xl y{l+1}..ym] = M[x0,x1..xly{l+1}...y{n+m-2l}] (deep = l > 0)
|
||||
template<typename Ty>
|
||||
friend void tensorContractnReverseProd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1, int nestingDepth);
|
||||
|
||||
template<typename Ty>
|
||||
friend void cudaTensorContractNestProd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1, int nestingDepth, bool strict);
|
||||
|
||||
/*template<typename Ty>
|
||||
friend void cudaTensorContractnProd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1, int nestingDepth);
|
||||
*/
|
||||
|
||||
template<typename Ty>
|
||||
friend void tensorProd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1);
|
||||
|
||||
template<typename Ty>
|
||||
friend void cudaTensorProd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1);
|
||||
|
||||
template<typename Ty>
|
||||
friend void cudaTensorProdEnd(Tensor<Ty>& M, const Tensor<Ty>& M0, const Tensor<Ty>& M1);
|
||||
|
||||
template<typename Ty>
|
||||
friend void permuteTensor(Tensor<Ty>& M, const Tensor<Ty>& M0, permutation p);
|
||||
template<typename Ty>
|
||||
friend void permuteTensorDef(Tensor<Ty>& M, const Tensor<Ty>& M0, permutation p);
|
||||
template<typename Tp>
|
||||
friend bool scanPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<Tp>& Msecond, const Tensor<Tp>& Mfirst, int contractNest);
|
||||
|
||||
//template<typename Ty>
|
||||
//friend void cudapermuteTensor(Tensor<Ty>& M, const Tensor<Ty>& M0, permutation p);
|
||||
|
||||
};
|
||||
|
||||
template<typename T>
|
||||
void transform(Tensor<T>& Dst, const Tensor<T>& Src, int* perm, int sz);
|
||||
|
||||
|
||||
template<typename T>
|
||||
Tensor<T>& operator*(const Tensor<T>& M0, const Tensor<T>& M1);
|
||||
|
||||
|
||||
void subArray(int* dst, int* src, int debDst, int finDst, int debSrc);
|
||||
|
||||
void concatArray(int* dst, int* src0, int* src1, int debDst, int debSrc0, int finSrc0, int debSrc1, int finSrc1);
|
||||
|
||||
void reverseArray(int* arr, int sz);
|
||||
|
||||
template<typename T>
|
||||
void tensorProd(Tensor<T>& M, const Tensor<T>& M1, const Tensor<T>& M0);
|
||||
|
||||
bool checkMatchProdTensor(const dimension& d0, const dimension& d1, int nestingDepth);
|
||||
|
||||
void extractDimNestingDepth(dimension& dM, const dimension& d0, const dimension& d1, int nestingDepth);
|
||||
|
||||
// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xn = y0,x{n-1}=y1, x{n-l}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
|
||||
|
||||
//M[[i][j]]=sum_{[k]}M0[[i][k]]*M[[k][j]]
|
||||
template<typename T>
|
||||
void tensorContractnProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth);
|
||||
|
||||
// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xn = y0,x{n-1}=y1, x{n-l}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
|
||||
|
||||
//M[[i][j]]=sum_{[k]}M0[[i][k]]*M[[k][j]]
|
||||
template<typename T>
|
||||
void tensorContractnReverseProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth);
|
||||
|
||||
#endif
|
||||
|
||||
@@ -0,0 +1,493 @@
|
||||
/*#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);
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
#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
|
||||
@@ -0,0 +1,574 @@
|
||||
#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);
|
||||
|
||||
@@ -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
|
||||
|
||||
Reference in New Issue
Block a user