int main() {
double dr = 1.0 / (double) R;
double dt = 0.0001;
double mu = 0.5 * dt / (dr*dr);
int i = 0;
double U[(R+1)*(R+1)];
double b[(R+1)*(R+1)];
double du[R];
double dc[R+1];
double dl[R];
printf("mu = %.5lf\n", mu);
setInitialCondition(U, (R+1), (R+1), dr);
setA(du, dc, dl, (R+1), (R+1), mu);
dumpMatrix(U, (R+1), (R+1), dr, 0);
while (i++ < 5) {
diffuse(U, b, (R+1), (R+1), du, dc, dl, mu);
dumpMatrix(U, (R+1), (R+1), dr, i);
}
}
int LinearAffineEq::buildLookupTableAndCheck(mat_GF2 & Ta, bsetElem cst, smap & mapA){
for(unsigned int i=0; i<size; i++){
mat_GF2 e = colVector(i);
mat_GF2 v = Ta * e;
GF2X res = colVector_GF2X(v, 0);
bsetElem resE = getLong(res) + cst;
// check mapping, if it is correct (consistent table data with new computed data)
if (mapA.count(i)>0){
if (mapA[i] != resE) {
if (verbosity){
cout << "Mapping inconsistent for i=" << i
<< "; mapA[i] = " << mapA[i]
<< "; resE = " << resE << endl;
cout << "colVector: " << endl;
dumpMatrix(e);
cout << " Ta*e " << endl;
dumpMatrix(v);
cout << "res: " << res << endl;
}
return -4;
}
} else {
mapA.insert(smapElem(i, resE));
}
}
return 0;
}
void AliasingManager::dumpAll() {
typedef map<VarDecl*, int>::iterator it_p;
typedef map<MatrixKind, boolean_matrix>::iterator it_m;
// Output all pointers within map
for (it_p b = m_indexesMap.begin(), e = m_indexesMap.end(); b != e; ++b) {
outs() << "\t" << b->second<< " => "<< b->first->getNameAsString()<< "\n";
}
// Output aliases matrix
for (it_m b = m_matricesMap.begin(), e = m_matricesMap.end(); b != e; ++b) {
// Switch matrix' kind
switch (b->first) {
case MK_PointsToMatrix:
outs() << "# Points-to & Pointed-by Matrix:\n";
break;
case MK_SymetricalMatrix:
outs() << "# Symetrical Matrix:\n";
break;
case MK_ClosedMatrix:
outs() << "# Aliases Matrix:\n";
break;
}
dumpMatrix(b->second);
outs() << "----------------------------------------\n";
}
}
static void record_fillgradient(struct _gfxdevice*dev, gfxline_t*line, gfxgradient_t*gradient, gfxgradienttype_t type, gfxmatrix_t*matrix)
{
internal_t*i = (internal_t*)dev->internal;
msg("<trace> record: %08x FILLGRADIENT %08x\n", dev, gradient);
writer_writeU8(&i->w, OP_FILLGRADIENT);
writer_writeU8(&i->w, type);
dumpGradient(&i->w, &i->state, gradient);
dumpMatrix(&i->w, &i->state, matrix);
dumpLine(&i->w, &i->state, line);
}
static void record_fillbitmap(struct _gfxdevice*dev, gfxline_t*line, gfximage_t*img, gfxmatrix_t*matrix, gfxcxform_t*cxform)
{
internal_t*i = (internal_t*)dev->internal;
msg("<trace> record: %08x FILLBITMAP\n", dev);
writer_writeU8(&i->w, OP_FILLBITMAP);
dumpImage(&i->w, &i->state, img);
dumpMatrix(&i->w, &i->state, matrix);
dumpLine(&i->w, &i->state, line);
dumpCXForm(&i->w, &i->state, cxform);
}
static void record_drawchar(struct _gfxdevice*dev, gfxfont_t*font, int glyphnr, gfxcolor_t*color, gfxmatrix_t*matrix)
{
internal_t*i = (internal_t*)dev->internal;
if(font && !gfxfontlist_hasfont(i->fontlist, font)) {
record_addfont(dev, font);
}
msg("<trace> record: %08x DRAWCHAR %d\n", glyphnr, dev);
const char*font_id = (font&&font->id)?font->id:"*NULL*";
gfxmatrix_t*l = &i->state.last_matrix[OP_DRAWCHAR];
U8 flags = 0;
if(!font)
flags |= FLAG_ZERO_FONT;
char same_font = i->state.last_string[OP_DRAWCHAR] && !strcmp(i->state.last_string[OP_DRAWCHAR], font_id);
char same_matrix = (l->m00 == matrix->m00) && (l->m01 == matrix->m01) && (l->m10 == matrix->m10) && (l->m11 == matrix->m11);
char same_color = !memcmp(color, &i->state.last_color[OP_DRAWCHAR], sizeof(gfxcolor_t));
/* FIXME
if(same_font && same_matrix && same_color)
flags |= FLAG_SAME_AS_LAST;
*/
writer_writeU8(&i->w, OP_DRAWCHAR|flags);
writer_writeU32(&i->w, glyphnr);
#ifdef STATS
i->state.size_chars += 5;
#endif
if(!(flags&FLAG_SAME_AS_LAST)) {
if(!(flags&FLAG_ZERO_FONT))
writer_writeString(&i->w, font_id);
dumpColor(&i->w, &i->state, color);
dumpMatrix(&i->w, &i->state, matrix);
if(i->state.last_string[OP_DRAWCHAR])
free(i->state.last_string[OP_DRAWCHAR]);
i->state.last_string[OP_DRAWCHAR] = strdup(font_id);
i->state.last_color[OP_DRAWCHAR] = *color;
i->state.last_matrix[OP_DRAWCHAR] = *matrix;
} else {
dumpXY(&i->w, &i->state, matrix);
}
}
osg::Matrix OSGConverter::requestToModelPose(const SendRequest& req) {
double pitch = 0;
double roll = 0;
double yaw = 0;
double x = 0;
double y = 0;
double z = 0;
CAST_PARAM(req.params, pitch, "pitch", double);
CAST_PARAM(req.params, roll, "roll", double);
CAST_PARAM(req.params, yaw, "yaw", double);
CAST_PARAM(req.params, x, "x", double);
CAST_PARAM(req.params, y, "y", double);
CAST_PARAM(req.params, z, "z", double);
osg::Matrix m = eulerToMatrix(pitch, roll, yaw) * osg::Matrix::translate(-1 * x, -1 * y, -1 * z);
#if 0
dumpMatrix(m);
#endif
return m;
}
int TxMatrixOptimizationDataCU::ingestLocalMatrix(SparseMatrix& A) {
std::vector<local_int_t> i(A.localNumberOfRows + 1, 0);
// Slight overallocation for these arrays
std::vector<local_int_t> j;
j.reserve(A.localNumberOfNonzeros);
std::vector<double> a;
a.reserve(A.localNumberOfNonzeros);
scatterFromHalo.setNumRows(A.localNumberOfRows);
scatterFromHalo.setNumCols(A.localNumberOfColumns);
scatterFromHalo.clear();
// We're splitting the matrix into diagonal and off-diagonal block to
// enable overlapping of computation and communication.
i[0] = 0;
for (local_int_t m = 0; m < A.localNumberOfRows; ++m) {
local_int_t nonzerosInRow = 0;
for (local_int_t n = 0; n < A.nonzerosInRow[m]; ++n) {
local_int_t col = A.mtxIndL[m][n];
if (col < A.localNumberOfRows) {
j.push_back(col);
a.push_back(A.matrixValues[m][n]);
++nonzerosInRow;
} else {
scatterFromHalo.addEntry(m, col, A.matrixValues[m][n]);
}
}
i[m + 1] = i[m] + nonzerosInRow;
}
// Setup SpMV data on Device
cudaError_t err = cudaSuccess;
int* i_d;
err = cudaMalloc((void**)&i_d, i.size() * sizeof(i[0]));
CHKCUDAERR(err);
err = cudaMemcpy(i_d, &i[0], i.size() * sizeof(i[0]), cudaMemcpyHostToDevice);
CHKCUDAERR(err);
int* j_d;
err = cudaMalloc((void**)&j_d, j.size() * sizeof(j[0]));
CHKCUDAERR(err);
err = cudaMemcpy(j_d, &j[0], j.size() * sizeof(j[0]), cudaMemcpyHostToDevice);
CHKCUDAERR(err);
double* a_d;
err = cudaMalloc((void**)&a_d, a.size() * sizeof(a[0]));
CHKCUDAERR(err);
err = cudaMemcpy(a_d, &a[0], a.size() * sizeof(a[0]), cudaMemcpyHostToDevice);
CHKCUDAERR(err);
cusparseStatus_t cerr = CUSPARSE_STATUS_SUCCESS;
cerr = cusparseCreateMatDescr(&matDescr);
CHKCUSPARSEERR(cerr);
cerr = cusparseSetMatIndexBase(matDescr, CUSPARSE_INDEX_BASE_ZERO);
CHKCUSPARSEERR(cerr);
cerr = cusparseSetMatType(matDescr, CUSPARSE_MATRIX_TYPE_GENERAL);
CHKCUSPARSEERR(cerr);
cerr = cusparseCreateHybMat(&localMatrix);
CHKCUSPARSEERR(cerr);
cerr = cusparseDcsr2hyb(handle, A.localNumberOfRows, A.localNumberOfColumns,
matDescr, a_d, i_d, j_d, localMatrix, 27,
CUSPARSE_HYB_PARTITION_USER);
CHKCUSPARSEERR(cerr);
#ifndef HPCG_NOMPI
err = cudaMalloc((void**)&elementsToSend,
A.totalToBeSent * sizeof(*elementsToSend));
CHKCUDAERR(err);
err = cudaMemcpy(elementsToSend, A.elementsToSend,
A.totalToBeSent * sizeof(*elementsToSend),
cudaMemcpyHostToDevice);
CHKCUDAERR(err);
err = cudaMalloc((void**)&sendBuffer_d, A.totalToBeSent * sizeof(double));
CHKCUDAERR(err);
#endif
// Set up the GS data.
gelusStatus_t gerr = GELUS_STATUS_SUCCESS;
gelusSolveDescription_t solveDescr;
gerr = gelusCreateSolveDescr(&solveDescr);
CHKGELUSERR(gerr);
gerr = gelusSetSolveOperation(solveDescr, GELUS_OPERATION_NON_TRANSPOSE);
CHKGELUSERR(gerr);
gerr = gelusSetSolveFillMode(solveDescr, GELUS_FILL_MODE_FULL);
CHKGELUSERR(gerr);
gerr = gelusSetSolveStorageFormat(solveDescr, GELUS_STORAGE_FORMAT_HYB);
CHKGELUSERR(gerr);
gerr = gelusSetOptimizationLevel(solveDescr, GELUS_OPTIMIZATION_LEVEL_THREE);
CHKGELUSERR(gerr);
gerr = cugelusCreateSorIterationData(&gsContext);
CHKGELUSERR(gerr);
#ifdef HPCG_DEBUG
std::cout << A.localNumberOfRows << std::endl;
std::cout << A.localNumberOfColumns << std::endl;
std::cout << A.localNumberOfNonzeros << std::endl;
int myrank;
MPI_Comm_rank(MPI_COMM_WORLD, &myrank);
if (myrank == 0) {
dumpMatrix(std::cout, i, j, a);
}
#endif
gerr = cugelusDcsrsor_iteration_analysis(
A.localNumberOfRows, solveDescr, GELUS_SOR_SYMMETRIC, 1.0,
&i[0], &j[0], &a[0], gsContext);
gerr = gelusDestroySolveDescr(solveDescr);
CHKGELUSERR(gerr);
if (A.mgData) {
err =
cudaMalloc((void**)&f2c, A.mgData->rc->localLength * sizeof(local_int_t));
CHKCUDAERR(err);
err = cudaMemcpy(f2c, A.mgData->f2cOperator,
A.mgData->rc->localLength * sizeof(local_int_t),
cudaMemcpyHostToDevice);
CHKCUDAERR(err);
}
err = cudaMalloc((void**)&workvector, A.localNumberOfRows * sizeof(double));
CHKCUDAERR(err);
return (int)cerr | (int)gerr | (int)err;
}
int LinearAffineEq::checkInvertibleLinear(const bset & Ua, const bset & Ub,
smap & mapA, smap & mapB,
bsetElem * S1, bsetElem * S1inv,
bsetElem * S2, bsetElem * S2inv,
mat_GF2 & Ta, mat_GF2 & Tb,
mat_GF2 & Tbinv, smap & mapBinv,
bool AisA){
// Extract linearly independent vectors, to determine mapping.
// We need matrix consisting of Avect to be invertible in order to determine
// matrix representation of transformation.
bset Avect = extractLinearlyIndependent(mapA);
if (verbosity) {
cout << "Size of linearly independent vectors: " << Avect.size() << endl;
LinearAffineEq::dumpSet(Avect);
}
// Derive matrix representation of transformation, if possible
//
// Ta * Ainp = Aout => Ta = Aout * Ainp^{-1}
mat_GF2 Ainp = LinearAffineEq::vectorSet2GF2matrix(Avect, 8), AinpInv;
mat_GF2 Aout = LinearAffineEq::values2GF2matrix(Avect, mapA, 8);
mat_GF2 TAinv;
GF2 det;
// Dimension check, each matrix has to have exactly 8 rows (dimension) and at least 8 columns
// (number of equations, sample points)
if ( Ainp.NumCols() < dim || Ainp.NumRows() != dim
|| Aout.NumCols() < dim || Aout.NumRows() != dim){
if (verbosity) cout << "Dimension mismatch for Ainp || Aout matrices " << endl;
return -1;
}
if (verbosity){
cout << "Input matrix: " << endl;
dumpMatrix(Ainp);
cout << "Output matrix: " << endl;
dumpMatrix(Aout);
}
// invertible?
inv(det, AinpInv, Ainp);
if (det == 0) {
if (verbosity) cout << "A Matrix is not invertible! " << endl;
return -2;
}
if (verbosity){
cout << "Inverse matrix: " << endl;
dumpMatrix(AinpInv);
}
// obtain linear transformation
Ta = Aout * AinpInv;
if (verbosity) {
cout << "Ta matrix: " << endl;
dumpMatrix(Ta);
}
// invertible?
inv(det, TAinv, Ta);
if (det==0){
if (verbosity) cout << "Transformation is not linear & invertible!" << endl;
return -3;
}
if (verbosity){
cout << "Transformation matrix repr. obtained!!!" << endl;
dumpMatrix(Ta);
}
//
// A is known (matrix representation), build lookup table
//
if (buildLookupTableAndCheck(Ta, 0, mapA)<0){
return -4;
}
//
// Deriving mapping B from mapping A that is complete now and in matrix form.
//
// B * S2 = S1 * A
// B(x) = S1 * A * S2^{-1} (x)
// From this we derive mapping for B for basis vectors directly.
//
// Or B and A are swapped here and we want to compute values for A(x)
// knowing mapping for B(x) (AisA==false)
//
// A(x) = S1inv * B * S2 (x)
//
Tb.SetDims(dim,dim);
for(unsigned int i=0; i<dim; i++){
bsetElem base = 1 << i;
bsetElem res = AisA ? S1[mapA[S2inv[base]]] : S1inv[mapA[S2[base]]];
for(unsigned int j=0; j<dim; j++){
Tb.put(j, i, (res & (1<<j)) > 0 ? 1 : 0);
}
}
if (verbosity){
cout << "Mapping B derived" << endl;
dumpMatrix(Tb);
}
// Transformation B invertibility test.
// Inversion is needed for final test for relations properties with S-boxes.
// If AisA==false, it does not mind, both relations has to be invertible.
inv(det, Tbinv, Tb);
if (det==0){
if (verbosity) cout << "B is not linear invertible transformation, cannot create inversion." << endl;
return -4;
}
// build lookup table for B and check already precomputed values
if (buildLookupTableAndCheck(Tb, 0, mapB)<0){
return -4;
}
// Whole range test for holding desired properties with Sboxes for which
// they were designed.
// For this we also need B^{-1} transformation.
//
// We apply this equation here:
// B^{-1} * S1 * A = S2
//
// If AisA==false, we have to reverse mapping here, Ta, Tb, Tainv, Tbinv are swapped,
// but relations works only according to equations. We need to return mapBinv for
// real B mapping (B^{-1} is needed to verify relations).
if (AisA){
buildLookupTableAndCheck(Tbinv, 0, mapBinv);
} else {
mapBinv.clear();
buildLookupTableAndCheck(TAinv, 0, mapBinv);
Tbinv = TAinv;
}
//
// Again take swapping A and B into account.
//
if (verbosity) cout << "Testing matrix representation with |Ua| = " << Ua.size() << " and |Ub| = " << Ub.size() << endl;
for(bsetElem iter = 0; iter < size; iter++){
bsetElem desiredResult = S2[iter];
bsetElem myResult = AisA ? mapBinv[S1[mapA[iter]]] : mapBinv[S1[mapB[iter]]];
if (desiredResult!=myResult){
if (verbosity){
cout << "Problem with relations, it does not work for: " << iter << endl;
cout << "S2["<<iter<<"]= " << desiredResult << endl;
cout << "B^{-1}[S1[A["<<iter<<"]]]=" << myResult << endl;
}
return -5;
}
}
return 0;
}
