Actual source code: math2opus.cu
1: #include <h2opusconf.h>
2: /* skip compilation of this .cu file if H2OPUS is CPU only while PETSc has GPU support */
4: #include <h2opus.h>
5: #if defined(H2OPUS_USE_MPI)
6: #include <h2opus/distributed/distributed_h2opus_handle.h>
7: #include <h2opus/distributed/distributed_geometric_construction.h>
8: #include <h2opus/distributed/distributed_hgemv.h>
9: #include <h2opus/distributed/distributed_horthog.h>
10: #include <h2opus/distributed/distributed_hcompress.h>
11: #endif
12: #include <h2opus/util/boxentrygen.h>
13: #include <petsc/private/matimpl.h>
14: #include <petsc/private/vecimpl.h>
15: #include <petsc/private/deviceimpl.h>
16: #include <petscsf.h>
18: /* math2opusutils */
19: PETSC_INTERN PetscErrorCode MatDenseGetH2OpusStridedSF(Mat, PetscSF, PetscSF *);
20: PETSC_INTERN PetscErrorCode VecSign(Vec, Vec);
21: PETSC_INTERN PetscErrorCode VecSetDelta(Vec, PetscInt);
22: PETSC_INTERN PetscErrorCode MatApproximateNorm_Private(Mat, NormType, PetscInt, PetscReal *);
24: #define MatH2OpusGetThrustPointer(v) thrust::raw_pointer_cast((v).data())
26: /* Use GPU only if H2OPUS is configured for GPU */
27: #if defined(PETSC_HAVE_CUDA) && defined(H2OPUS_USE_GPU)
28: #define PETSC_H2OPUS_USE_GPU
29: #endif
30: #if defined(PETSC_H2OPUS_USE_GPU)
31: #define MatH2OpusUpdateIfNeeded(A, B) MatBindToCPU(A, (PetscBool)((A)->boundtocpu || (B)))
32: #else
33: #define MatH2OpusUpdateIfNeeded(A, B) PETSC_SUCCESS
34: #endif
36: // TODO H2OPUS:
37: // DistributedHMatrix
38: // unsymmetric ?
39: // transpose for distributed_hgemv?
40: // clearData()
41: // Unify interface for sequential and parallel?
42: // Reuse geometric construction (almost possible, only the unsymmetric case is explicitly handled)
43: //
44: template <class T>
45: class PetscPointCloud : public H2OpusDataSet<T> {
46: private:
47: int dimension;
48: size_t num_points;
49: std::vector<T> pts;
51: public:
52: PetscPointCloud(int dim, size_t num_pts, const T coords[])
53: {
54: dim = dim > 0 ? dim : 1;
55: this->dimension = dim;
56: this->num_points = num_pts;
58: pts.resize(num_pts * dim);
59: if (coords) {
60: for (size_t n = 0; n < num_pts; n++)
61: for (int i = 0; i < dim; i++) pts[n * dim + i] = coords[n * dim + i];
62: } else {
63: PetscReal h = 1.0; //num_pts > 1 ? 1./(num_pts - 1) : 0.0;
64: for (size_t n = 0; n < num_pts; n++) {
65: pts[n * dim] = n * h;
66: for (int i = 1; i < dim; i++) pts[n * dim + i] = 0.0;
67: }
68: }
69: }
71: PetscPointCloud(const PetscPointCloud<T> &other)
72: {
73: size_t N = other.dimension * other.num_points;
74: this->dimension = other.dimension;
75: this->num_points = other.num_points;
76: this->pts.resize(N);
77: for (size_t i = 0; i < N; i++) this->pts[i] = other.pts[i];
78: }
80: int getDimension() const { return dimension; }
82: size_t getDataSetSize() const { return num_points; }
84: T getDataPoint(size_t idx, int dim) const
85: {
86: assert(dim < dimension && idx < num_points);
87: return pts[idx * dimension + dim];
88: }
90: void Print(std::ostream &out = std::cout)
91: {
92: out << "Dimension: " << dimension << std::endl;
93: out << "NumPoints: " << num_points << std::endl;
94: for (size_t n = 0; n < num_points; n++) {
95: for (int d = 0; d < dimension; d++) out << pts[n * dimension + d] << " ";
96: out << std::endl;
97: }
98: }
99: };
101: template <class T>
102: class PetscFunctionGenerator {
103: private:
104: MatH2OpusKernelFn *k;
105: int dim;
106: void *ctx;
108: public:
109: PetscFunctionGenerator(MatH2OpusKernelFn *k, int dim, void *ctx)
110: {
111: this->k = k;
112: this->dim = dim;
113: this->ctx = ctx;
114: }
115: PetscFunctionGenerator(PetscFunctionGenerator &other)
116: {
117: this->k = other.k;
118: this->dim = other.dim;
119: this->ctx = other.ctx;
120: }
121: T operator()(PetscReal *pt1, PetscReal *pt2) { return (T)((*this->k)(this->dim, pt1, pt2, this->ctx)); }
122: };
124: #include <../src/mat/impls/h2opus/math2opussampler.hpp>
126: /* just to not clutter the code */
127: #if !defined(H2OPUS_USE_GPU)
128: typedef HMatrix HMatrix_GPU;
129: #if defined(H2OPUS_USE_MPI)
130: typedef DistributedHMatrix DistributedHMatrix_GPU;
131: #endif
132: #endif
134: typedef struct {
135: #if defined(H2OPUS_USE_MPI)
136: distributedH2OpusHandle_t handle;
137: #else
138: h2opusHandle_t handle;
139: #endif
140: /* Sequential and parallel matrices are two different classes at the moment */
141: HMatrix *hmatrix;
142: #if defined(H2OPUS_USE_MPI)
143: DistributedHMatrix *dist_hmatrix;
144: #else
145: HMatrix *dist_hmatrix; /* just to not clutter the code */
146: #endif
147: /* May use permutations */
148: PetscSF sf;
149: PetscLayout h2opus_rmap, h2opus_cmap;
150: IS h2opus_indexmap;
151: thrust::host_vector<PetscScalar> *xx, *yy;
152: PetscInt xxs, yys;
153: PetscBool multsetup;
155: /* GPU */
156: HMatrix_GPU *hmatrix_gpu;
157: #if defined(H2OPUS_USE_MPI)
158: DistributedHMatrix_GPU *dist_hmatrix_gpu;
159: #else
160: HMatrix_GPU *dist_hmatrix_gpu; /* just to not clutter the code */
161: #endif
162: #if defined(PETSC_H2OPUS_USE_GPU)
163: thrust::device_vector<PetscScalar> *xx_gpu, *yy_gpu;
164: PetscInt xxs_gpu, yys_gpu;
165: #endif
167: /* construction from matvecs */
168: PetscMatrixSampler *sampler;
169: PetscBool nativemult;
171: /* Admissibility */
172: PetscReal eta;
173: PetscInt leafsize;
175: /* for dof reordering */
176: PetscPointCloud<PetscReal> *ptcloud;
178: /* kernel for generating matrix entries */
179: PetscFunctionGenerator<PetscScalar> *kernel;
181: /* basis orthogonalized? */
182: PetscBool orthogonal;
184: /* customization */
185: PetscInt basisord;
186: PetscInt max_rank;
187: PetscInt bs;
188: PetscReal rtol;
189: PetscInt norm_max_samples;
190: PetscBool check_construction;
191: PetscBool hara_verbose;
192: PetscBool resize;
194: /* keeps track of MatScale values */
195: PetscScalar s;
196: } Mat_H2OPUS;
198: static PetscErrorCode MatDestroy_H2OPUS(Mat A)
199: {
200: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
202: PetscFunctionBegin;
203: #if defined(H2OPUS_USE_MPI)
204: h2opusDestroyDistributedHandle(a->handle);
205: #else
206: h2opusDestroyHandle(a->handle);
207: #endif
208: delete a->dist_hmatrix;
209: delete a->hmatrix;
210: PetscCall(PetscSFDestroy(&a->sf));
211: PetscCall(PetscLayoutDestroy(&a->h2opus_rmap));
212: PetscCall(PetscLayoutDestroy(&a->h2opus_cmap));
213: PetscCall(ISDestroy(&a->h2opus_indexmap));
214: delete a->xx;
215: delete a->yy;
216: delete a->hmatrix_gpu;
217: delete a->dist_hmatrix_gpu;
218: #if defined(PETSC_H2OPUS_USE_GPU)
219: delete a->xx_gpu;
220: delete a->yy_gpu;
221: #endif
222: delete a->sampler;
223: delete a->ptcloud;
224: delete a->kernel;
225: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_seqdense_C", NULL));
226: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_seqdensecuda_C", NULL));
227: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_mpidense_C", NULL));
228: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_mpidensecuda_C", NULL));
229: PetscCall(PetscObjectChangeTypeName((PetscObject)A, NULL));
230: PetscCall(PetscFree(A->data));
231: PetscFunctionReturn(PETSC_SUCCESS);
232: }
234: PetscErrorCode MatH2OpusSetNativeMult(Mat A, PetscBool nm)
235: {
236: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
237: PetscBool ish2opus;
239: PetscFunctionBegin;
242: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
243: if (ish2opus) {
244: if (a->h2opus_rmap) { /* need to swap layouts for vector creation */
245: if ((!a->nativemult && nm) || (a->nativemult && !nm)) {
246: PetscLayout t;
247: t = A->rmap;
248: A->rmap = a->h2opus_rmap;
249: a->h2opus_rmap = t;
250: t = A->cmap;
251: A->cmap = a->h2opus_cmap;
252: a->h2opus_cmap = t;
253: }
254: }
255: a->nativemult = nm;
256: }
257: PetscFunctionReturn(PETSC_SUCCESS);
258: }
260: PetscErrorCode MatH2OpusGetNativeMult(Mat A, PetscBool *nm)
261: {
262: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
263: PetscBool ish2opus;
265: PetscFunctionBegin;
267: PetscAssertPointer(nm, 2);
268: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
269: PetscCheck(ish2opus, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)A)->type_name);
270: *nm = a->nativemult;
271: PetscFunctionReturn(PETSC_SUCCESS);
272: }
274: PETSC_EXTERN PetscErrorCode MatNorm_H2OPUS(Mat A, NormType normtype, PetscReal *n)
275: {
276: PetscBool ish2opus;
277: PetscInt nmax = PETSC_DECIDE;
278: Mat_H2OPUS *a = NULL;
279: PetscBool mult = PETSC_FALSE;
281: PetscFunctionBegin;
282: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
283: if (ish2opus) { /* set userdefine number of samples and fastpath for mult (norms are order independent) */
284: a = (Mat_H2OPUS *)A->data;
286: nmax = a->norm_max_samples;
287: mult = a->nativemult;
288: PetscCall(MatH2OpusSetNativeMult(A, PETSC_TRUE));
289: } else {
290: PetscCall(PetscOptionsGetInt(((PetscObject)A)->options, ((PetscObject)A)->prefix, "-mat_approximate_norm_samples", &nmax, NULL));
291: }
292: PetscCall(MatApproximateNorm_Private(A, normtype, nmax, n));
293: if (a) PetscCall(MatH2OpusSetNativeMult(A, mult));
294: PetscFunctionReturn(PETSC_SUCCESS);
295: }
297: static PetscErrorCode MatH2OpusResizeBuffers_Private(Mat A, PetscInt xN, PetscInt yN)
298: {
299: Mat_H2OPUS *h2opus = (Mat_H2OPUS *)A->data;
300: PetscInt n;
301: PetscBool boundtocpu = PETSC_TRUE;
303: PetscFunctionBegin;
304: #if defined(PETSC_H2OPUS_USE_GPU)
305: boundtocpu = A->boundtocpu;
306: #endif
307: PetscCall(PetscSFGetGraph(h2opus->sf, NULL, &n, NULL, NULL));
308: if (boundtocpu) {
309: if (h2opus->xxs < xN) {
310: h2opus->xx->resize(n * xN);
311: h2opus->xxs = xN;
312: }
313: if (h2opus->yys < yN) {
314: h2opus->yy->resize(n * yN);
315: h2opus->yys = yN;
316: }
317: }
318: #if defined(PETSC_H2OPUS_USE_GPU)
319: if (!boundtocpu) {
320: if (h2opus->xxs_gpu < xN) {
321: h2opus->xx_gpu->resize(n * xN);
322: h2opus->xxs_gpu = xN;
323: }
324: if (h2opus->yys_gpu < yN) {
325: h2opus->yy_gpu->resize(n * yN);
326: h2opus->yys_gpu = yN;
327: }
328: }
329: #endif
330: PetscFunctionReturn(PETSC_SUCCESS);
331: }
333: static PetscErrorCode MatMultNKernel_H2OPUS(Mat A, PetscBool transA, Mat B, Mat C)
334: {
335: Mat_H2OPUS *h2opus = (Mat_H2OPUS *)A->data;
336: #if defined(H2OPUS_USE_MPI)
337: h2opusHandle_t handle = h2opus->handle->handle;
338: #else
339: h2opusHandle_t handle = h2opus->handle;
340: #endif
341: PetscBool boundtocpu = PETSC_TRUE;
342: PetscScalar *xx, *yy, *uxx, *uyy;
343: PetscInt blda, clda;
344: PetscMPIInt size;
345: PetscSF bsf, csf;
346: PetscBool usesf = (PetscBool)(h2opus->sf && !h2opus->nativemult);
348: PetscFunctionBegin;
349: HLibProfile::clear();
350: #if defined(PETSC_H2OPUS_USE_GPU)
351: boundtocpu = A->boundtocpu;
352: #endif
353: PetscCall(MatDenseGetLDA(B, &blda));
354: PetscCall(MatDenseGetLDA(C, &clda));
355: if (usesf) {
356: PetscInt n;
358: PetscCall(MatDenseGetH2OpusStridedSF(B, h2opus->sf, &bsf));
359: PetscCall(MatDenseGetH2OpusStridedSF(C, h2opus->sf, &csf));
361: PetscCall(MatH2OpusResizeBuffers_Private(A, B->cmap->N, C->cmap->N));
362: PetscCall(PetscSFGetGraph(h2opus->sf, NULL, &n, NULL, NULL));
363: blda = n;
364: clda = n;
365: }
366: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
367: if (boundtocpu) {
368: PetscCall(MatDenseGetArrayRead(B, (const PetscScalar **)&xx));
369: PetscCall(MatDenseGetArrayWrite(C, &yy));
370: if (usesf) {
371: uxx = MatH2OpusGetThrustPointer(*h2opus->xx);
372: uyy = MatH2OpusGetThrustPointer(*h2opus->yy);
373: PetscCall(PetscSFBcastBegin(bsf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
374: PetscCall(PetscSFBcastEnd(bsf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
375: } else {
376: uxx = xx;
377: uyy = yy;
378: }
379: if (size > 1) {
380: PetscCheck(h2opus->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed CPU matrix");
381: PetscCheck(!transA || A->symmetric, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "MatMultTranspose not yet coded in parallel");
382: #if defined(H2OPUS_USE_MPI)
383: distributed_hgemv(/* transA ? H2Opus_Trans : H2Opus_NoTrans, */ h2opus->s, *h2opus->dist_hmatrix, uxx, blda, 0.0, uyy, clda, B->cmap->N, h2opus->handle);
384: #endif
385: } else {
386: PetscCheck(h2opus->hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
387: hgemv(transA ? H2Opus_Trans : H2Opus_NoTrans, h2opus->s, *h2opus->hmatrix, uxx, blda, 0.0, uyy, clda, B->cmap->N, handle);
388: }
389: PetscCall(MatDenseRestoreArrayRead(B, (const PetscScalar **)&xx));
390: if (usesf) {
391: PetscCall(PetscSFReduceBegin(csf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
392: PetscCall(PetscSFReduceEnd(csf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
393: }
394: PetscCall(MatDenseRestoreArrayWrite(C, &yy));
395: #if defined(PETSC_H2OPUS_USE_GPU)
396: } else {
397: PetscBool ciscuda, biscuda;
399: /* If not of type seqdensecuda, convert on the fly (i.e. allocate GPU memory) */
400: PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &biscuda, MATSEQDENSECUDA, MATMPIDENSECUDA, ""));
401: if (!biscuda) PetscCall(MatConvert(B, MATDENSECUDA, MAT_INPLACE_MATRIX, &B));
402: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &ciscuda, MATSEQDENSECUDA, MATMPIDENSECUDA, ""));
403: if (!ciscuda) {
404: C->assembled = PETSC_TRUE;
405: PetscCall(MatConvert(C, MATDENSECUDA, MAT_INPLACE_MATRIX, &C));
406: }
407: PetscCall(MatDenseCUDAGetArrayRead(B, (const PetscScalar **)&xx));
408: PetscCall(MatDenseCUDAGetArrayWrite(C, &yy));
409: if (usesf) {
410: uxx = MatH2OpusGetThrustPointer(*h2opus->xx_gpu);
411: uyy = MatH2OpusGetThrustPointer(*h2opus->yy_gpu);
412: PetscCall(PetscSFBcastBegin(bsf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
413: PetscCall(PetscSFBcastEnd(bsf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
414: } else {
415: uxx = xx;
416: uyy = yy;
417: }
418: PetscCall(PetscLogGpuTimeBegin());
419: if (size > 1) {
420: PetscCheck(h2opus->dist_hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed GPU matrix");
421: PetscCheck(!transA || A->symmetric, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "MatMultTranspose not yet coded in parallel");
422: #if defined(H2OPUS_USE_MPI)
423: distributed_hgemv(/* transA ? H2Opus_Trans : H2Opus_NoTrans, */ h2opus->s, *h2opus->dist_hmatrix_gpu, uxx, blda, 0.0, uyy, clda, B->cmap->N, h2opus->handle);
424: #endif
425: } else {
426: PetscCheck(h2opus->hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
427: hgemv(transA ? H2Opus_Trans : H2Opus_NoTrans, h2opus->s, *h2opus->hmatrix_gpu, uxx, blda, 0.0, uyy, clda, B->cmap->N, handle);
428: }
429: PetscCall(PetscLogGpuTimeEnd());
430: PetscCall(MatDenseCUDARestoreArrayRead(B, (const PetscScalar **)&xx));
431: if (usesf) {
432: PetscCall(PetscSFReduceBegin(csf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
433: PetscCall(PetscSFReduceEnd(csf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
434: }
435: PetscCall(MatDenseCUDARestoreArrayWrite(C, &yy));
436: if (!biscuda) PetscCall(MatConvert(B, MATDENSE, MAT_INPLACE_MATRIX, &B));
437: if (!ciscuda) PetscCall(MatConvert(C, MATDENSE, MAT_INPLACE_MATRIX, &C));
438: #endif
439: }
440: { /* log flops */
441: double gops, time, perf, dev;
442: HLibProfile::getHgemvPerf(gops, time, perf, dev);
443: #if defined(PETSC_H2OPUS_USE_GPU)
444: if (boundtocpu) {
445: PetscCall(PetscLogFlops(1e9 * gops));
446: } else {
447: PetscCall(PetscLogGpuFlops(1e9 * gops));
448: }
449: #else
450: PetscCall(PetscLogFlops(1e9 * gops));
451: #endif
452: }
453: PetscFunctionReturn(PETSC_SUCCESS);
454: }
456: static PetscErrorCode MatProductNumeric_H2OPUS(Mat C)
457: {
458: Mat_Product *product = C->product;
460: PetscFunctionBegin;
461: MatCheckProduct(C, 1);
462: switch (product->type) {
463: case MATPRODUCT_AB:
464: PetscCall(MatMultNKernel_H2OPUS(product->A, PETSC_FALSE, product->B, C));
465: break;
466: case MATPRODUCT_AtB:
467: PetscCall(MatMultNKernel_H2OPUS(product->A, PETSC_TRUE, product->B, C));
468: break;
469: default:
470: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatProduct type %s is not supported", MatProductTypes[product->type]);
471: }
472: PetscFunctionReturn(PETSC_SUCCESS);
473: }
475: static PetscErrorCode MatProductSymbolic_H2OPUS(Mat C)
476: {
477: Mat_Product *product = C->product;
478: PetscBool cisdense;
479: Mat A, B;
481: PetscFunctionBegin;
482: MatCheckProduct(C, 1);
483: A = product->A;
484: B = product->B;
485: switch (product->type) {
486: case MATPRODUCT_AB:
487: PetscCall(MatSetSizes(C, A->rmap->n, B->cmap->n, A->rmap->N, B->cmap->N));
488: PetscCall(MatSetBlockSizesFromMats(C, product->A, product->B));
489: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATMPIDENSE, MATSEQDENSECUDA, MATMPIDENSECUDA, ""));
490: if (!cisdense) PetscCall(MatSetType(C, ((PetscObject)product->B)->type_name));
491: PetscCall(MatSetUp(C));
492: break;
493: case MATPRODUCT_AtB:
494: PetscCall(MatSetSizes(C, A->cmap->n, B->cmap->n, A->cmap->N, B->cmap->N));
495: PetscCall(MatSetBlockSizesFromMats(C, product->A, product->B));
496: PetscCall(PetscObjectTypeCompareAny((PetscObject)C, &cisdense, MATSEQDENSE, MATMPIDENSE, MATSEQDENSECUDA, MATMPIDENSECUDA, ""));
497: if (!cisdense) PetscCall(MatSetType(C, ((PetscObject)product->B)->type_name));
498: PetscCall(MatSetUp(C));
499: break;
500: default:
501: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatProduct type %s is not supported", MatProductTypes[product->type]);
502: }
503: C->ops->productsymbolic = NULL;
504: C->ops->productnumeric = MatProductNumeric_H2OPUS;
505: PetscFunctionReturn(PETSC_SUCCESS);
506: }
508: static PetscErrorCode MatProductSetFromOptions_H2OPUS(Mat C)
509: {
510: PetscFunctionBegin;
511: MatCheckProduct(C, 1);
512: if (C->product->type == MATPRODUCT_AB || C->product->type == MATPRODUCT_AtB) C->ops->productsymbolic = MatProductSymbolic_H2OPUS;
513: PetscFunctionReturn(PETSC_SUCCESS);
514: }
516: static PetscErrorCode MatMultKernel_H2OPUS(Mat A, Vec x, PetscScalar sy, Vec y, PetscBool trans)
517: {
518: Mat_H2OPUS *h2opus = (Mat_H2OPUS *)A->data;
519: #if defined(H2OPUS_USE_MPI)
520: h2opusHandle_t handle = h2opus->handle->handle;
521: #else
522: h2opusHandle_t handle = h2opus->handle;
523: #endif
524: PetscBool boundtocpu = PETSC_TRUE;
525: PetscInt n;
526: PetscScalar *xx, *yy, *uxx, *uyy;
527: PetscMPIInt size;
528: PetscBool usesf = (PetscBool)(h2opus->sf && !h2opus->nativemult);
530: PetscFunctionBegin;
531: HLibProfile::clear();
532: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
533: #if defined(PETSC_H2OPUS_USE_GPU)
534: boundtocpu = A->boundtocpu;
535: #endif
536: if (usesf) PetscCall(PetscSFGetGraph(h2opus->sf, NULL, &n, NULL, NULL));
537: else n = A->rmap->n;
538: if (boundtocpu) {
539: PetscCall(VecGetArrayRead(x, (const PetscScalar **)&xx));
540: if (sy == 0.0) {
541: PetscCall(VecGetArrayWrite(y, &yy));
542: } else {
543: PetscCall(VecGetArray(y, &yy));
544: }
545: if (usesf) {
546: uxx = MatH2OpusGetThrustPointer(*h2opus->xx);
547: uyy = MatH2OpusGetThrustPointer(*h2opus->yy);
549: PetscCall(PetscSFBcastBegin(h2opus->sf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
550: PetscCall(PetscSFBcastEnd(h2opus->sf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
551: if (sy != 0.0) {
552: PetscCall(PetscSFBcastBegin(h2opus->sf, MPIU_SCALAR, yy, uyy, MPI_REPLACE));
553: PetscCall(PetscSFBcastEnd(h2opus->sf, MPIU_SCALAR, yy, uyy, MPI_REPLACE));
554: }
555: } else {
556: uxx = xx;
557: uyy = yy;
558: }
559: if (size > 1) {
560: PetscCheck(h2opus->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed CPU matrix");
561: PetscCheck(!trans || A->symmetric, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "MatMultTranspose not yet coded in parallel");
562: #if defined(H2OPUS_USE_MPI)
563: distributed_hgemv(/*trans ? H2Opus_Trans : H2Opus_NoTrans, */ h2opus->s, *h2opus->dist_hmatrix, uxx, n, sy, uyy, n, 1, h2opus->handle);
564: #endif
565: } else {
566: PetscCheck(h2opus->hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
567: hgemv(trans ? H2Opus_Trans : H2Opus_NoTrans, h2opus->s, *h2opus->hmatrix, uxx, n, sy, uyy, n, 1, handle);
568: }
569: PetscCall(VecRestoreArrayRead(x, (const PetscScalar **)&xx));
570: if (usesf) {
571: PetscCall(PetscSFReduceBegin(h2opus->sf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
572: PetscCall(PetscSFReduceEnd(h2opus->sf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
573: }
574: if (sy == 0.0) {
575: PetscCall(VecRestoreArrayWrite(y, &yy));
576: } else {
577: PetscCall(VecRestoreArray(y, &yy));
578: }
579: #if defined(PETSC_H2OPUS_USE_GPU)
580: } else {
581: PetscCall(VecCUDAGetArrayRead(x, (const PetscScalar **)&xx));
582: if (sy == 0.0) {
583: PetscCall(VecCUDAGetArrayWrite(y, &yy));
584: } else {
585: PetscCall(VecCUDAGetArray(y, &yy));
586: }
587: if (usesf) {
588: uxx = MatH2OpusGetThrustPointer(*h2opus->xx_gpu);
589: uyy = MatH2OpusGetThrustPointer(*h2opus->yy_gpu);
591: PetscCall(PetscSFBcastBegin(h2opus->sf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
592: PetscCall(PetscSFBcastEnd(h2opus->sf, MPIU_SCALAR, xx, uxx, MPI_REPLACE));
593: if (sy != 0.0) {
594: PetscCall(PetscSFBcastBegin(h2opus->sf, MPIU_SCALAR, yy, uyy, MPI_REPLACE));
595: PetscCall(PetscSFBcastEnd(h2opus->sf, MPIU_SCALAR, yy, uyy, MPI_REPLACE));
596: }
597: } else {
598: uxx = xx;
599: uyy = yy;
600: }
601: PetscCall(PetscLogGpuTimeBegin());
602: if (size > 1) {
603: PetscCheck(h2opus->dist_hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed GPU matrix");
604: PetscCheck(!trans || A->symmetric, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "MatMultTranspose not yet coded in parallel");
605: #if defined(H2OPUS_USE_MPI)
606: distributed_hgemv(/*trans ? H2Opus_Trans : H2Opus_NoTrans, */ h2opus->s, *h2opus->dist_hmatrix_gpu, uxx, n, sy, uyy, n, 1, h2opus->handle);
607: #endif
608: } else {
609: PetscCheck(h2opus->hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
610: hgemv(trans ? H2Opus_Trans : H2Opus_NoTrans, h2opus->s, *h2opus->hmatrix_gpu, uxx, n, sy, uyy, n, 1, handle);
611: }
612: PetscCall(PetscLogGpuTimeEnd());
613: PetscCall(VecCUDARestoreArrayRead(x, (const PetscScalar **)&xx));
614: if (usesf) {
615: PetscCall(PetscSFReduceBegin(h2opus->sf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
616: PetscCall(PetscSFReduceEnd(h2opus->sf, MPIU_SCALAR, uyy, yy, MPI_REPLACE));
617: }
618: if (sy == 0.0) {
619: PetscCall(VecCUDARestoreArrayWrite(y, &yy));
620: } else {
621: PetscCall(VecCUDARestoreArray(y, &yy));
622: }
623: #endif
624: }
625: { /* log flops */
626: double gops, time, perf, dev;
627: HLibProfile::getHgemvPerf(gops, time, perf, dev);
628: #if defined(PETSC_H2OPUS_USE_GPU)
629: if (boundtocpu) {
630: PetscCall(PetscLogFlops(1e9 * gops));
631: } else {
632: PetscCall(PetscLogGpuFlops(1e9 * gops));
633: }
634: #else
635: PetscCall(PetscLogFlops(1e9 * gops));
636: #endif
637: }
638: PetscFunctionReturn(PETSC_SUCCESS);
639: }
641: static PetscErrorCode MatMultTranspose_H2OPUS(Mat A, Vec x, Vec y)
642: {
643: PetscBool xiscuda, yiscuda;
645: PetscFunctionBegin;
646: PetscCall(PetscObjectTypeCompareAny((PetscObject)x, &xiscuda, VECSEQCUDA, VECMPICUDA, ""));
647: PetscCall(PetscObjectTypeCompareAny((PetscObject)y, &yiscuda, VECSEQCUDA, VECMPICUDA, ""));
648: PetscCall(MatH2OpusUpdateIfNeeded(A, !xiscuda || !yiscuda));
649: PetscCall(MatMultKernel_H2OPUS(A, x, 0.0, y, PETSC_TRUE));
650: PetscFunctionReturn(PETSC_SUCCESS);
651: }
653: static PetscErrorCode MatMult_H2OPUS(Mat A, Vec x, Vec y)
654: {
655: PetscBool xiscuda, yiscuda;
657: PetscFunctionBegin;
658: PetscCall(PetscObjectTypeCompareAny((PetscObject)x, &xiscuda, VECSEQCUDA, VECMPICUDA, ""));
659: PetscCall(PetscObjectTypeCompareAny((PetscObject)y, &yiscuda, VECSEQCUDA, VECMPICUDA, ""));
660: PetscCall(MatH2OpusUpdateIfNeeded(A, !xiscuda || !yiscuda));
661: PetscCall(MatMultKernel_H2OPUS(A, x, 0.0, y, PETSC_FALSE));
662: PetscFunctionReturn(PETSC_SUCCESS);
663: }
665: static PetscErrorCode MatMultTransposeAdd_H2OPUS(Mat A, Vec x, Vec y, Vec z)
666: {
667: PetscBool xiscuda, ziscuda;
669: PetscFunctionBegin;
670: PetscCall(VecCopy(y, z));
671: PetscCall(PetscObjectTypeCompareAny((PetscObject)x, &xiscuda, VECSEQCUDA, VECMPICUDA, ""));
672: PetscCall(PetscObjectTypeCompareAny((PetscObject)z, &ziscuda, VECSEQCUDA, VECMPICUDA, ""));
673: PetscCall(MatH2OpusUpdateIfNeeded(A, !xiscuda || !ziscuda));
674: PetscCall(MatMultKernel_H2OPUS(A, x, 1.0, z, PETSC_TRUE));
675: PetscFunctionReturn(PETSC_SUCCESS);
676: }
678: static PetscErrorCode MatMultAdd_H2OPUS(Mat A, Vec x, Vec y, Vec z)
679: {
680: PetscBool xiscuda, ziscuda;
682: PetscFunctionBegin;
683: PetscCall(VecCopy(y, z));
684: PetscCall(PetscObjectTypeCompareAny((PetscObject)x, &xiscuda, VECSEQCUDA, VECMPICUDA, ""));
685: PetscCall(PetscObjectTypeCompareAny((PetscObject)z, &ziscuda, VECSEQCUDA, VECMPICUDA, ""));
686: PetscCall(MatH2OpusUpdateIfNeeded(A, !xiscuda || !ziscuda));
687: PetscCall(MatMultKernel_H2OPUS(A, x, 1.0, z, PETSC_FALSE));
688: PetscFunctionReturn(PETSC_SUCCESS);
689: }
691: static PetscErrorCode MatScale_H2OPUS(Mat A, PetscScalar s)
692: {
693: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
695: PetscFunctionBegin;
696: a->s *= s;
697: PetscFunctionReturn(PETSC_SUCCESS);
698: }
700: static PetscErrorCode MatSetFromOptions_H2OPUS(Mat A, PetscOptionItems PetscOptionsObject)
701: {
702: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
704: PetscFunctionBegin;
705: PetscOptionsHeadBegin(PetscOptionsObject, "H2OPUS options");
706: PetscCall(PetscOptionsInt("-mat_h2opus_leafsize", "Leaf size of cluster tree", NULL, a->leafsize, &a->leafsize, NULL));
707: PetscCall(PetscOptionsReal("-mat_h2opus_eta", "Admissibility condition tolerance", NULL, a->eta, &a->eta, NULL));
708: PetscCall(PetscOptionsInt("-mat_h2opus_order", "Basis order for off-diagonal sampling when constructed from kernel", NULL, a->basisord, &a->basisord, NULL));
709: PetscCall(PetscOptionsInt("-mat_h2opus_maxrank", "Maximum rank when constructed from matvecs", NULL, a->max_rank, &a->max_rank, NULL));
710: PetscCall(PetscOptionsInt("-mat_h2opus_samples", "Maximum number of samples to be taken concurrently when constructing from matvecs", NULL, a->bs, &a->bs, NULL));
711: PetscCall(PetscOptionsInt("-mat_h2opus_normsamples", "Maximum number of samples to be when estimating norms", NULL, a->norm_max_samples, &a->norm_max_samples, NULL));
712: PetscCall(PetscOptionsReal("-mat_h2opus_rtol", "Relative tolerance for construction from sampling", NULL, a->rtol, &a->rtol, NULL));
713: PetscCall(PetscOptionsBool("-mat_h2opus_check", "Check error when constructing from sampling during MatAssemblyEnd()", NULL, a->check_construction, &a->check_construction, NULL));
714: PetscCall(PetscOptionsBool("-mat_h2opus_hara_verbose", "Verbose output from hara construction", NULL, a->hara_verbose, &a->hara_verbose, NULL));
715: PetscCall(PetscOptionsBool("-mat_h2opus_resize", "Resize after compression", NULL, a->resize, &a->resize, NULL));
716: PetscOptionsHeadEnd();
717: PetscFunctionReturn(PETSC_SUCCESS);
718: }
720: static PetscErrorCode MatH2OpusSetCoords_H2OPUS(Mat, PetscInt, const PetscReal[], PetscBool, MatH2OpusKernelFn *, void *);
722: static PetscErrorCode MatH2OpusInferCoordinates_Private(Mat A)
723: {
724: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
725: Vec c;
726: PetscInt spacedim;
727: const PetscScalar *coords;
729: PetscFunctionBegin;
730: if (a->ptcloud) PetscFunctionReturn(PETSC_SUCCESS);
731: PetscCall(PetscObjectQuery((PetscObject)A, "__math2opus_coords", (PetscObject *)&c));
732: if (!c && a->sampler) {
733: Mat S = a->sampler->GetSamplingMat();
735: PetscCall(PetscObjectQuery((PetscObject)S, "__math2opus_coords", (PetscObject *)&c));
736: }
737: if (!c) {
738: PetscCall(MatH2OpusSetCoords_H2OPUS(A, -1, NULL, PETSC_FALSE, NULL, NULL));
739: } else {
740: PetscCall(VecGetArrayRead(c, &coords));
741: PetscCall(VecGetBlockSize(c, &spacedim));
742: PetscCall(MatH2OpusSetCoords_H2OPUS(A, spacedim, coords, PETSC_FALSE, NULL, NULL));
743: PetscCall(VecRestoreArrayRead(c, &coords));
744: }
745: PetscFunctionReturn(PETSC_SUCCESS);
746: }
748: static PetscErrorCode MatSetUpMultiply_H2OPUS(Mat A)
749: {
750: MPI_Comm comm;
751: PetscMPIInt size;
752: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
753: PetscInt n = 0, *idx = NULL;
754: int *iidx = NULL;
755: PetscCopyMode own;
756: PetscBool rid;
758: PetscFunctionBegin;
759: if (a->multsetup) PetscFunctionReturn(PETSC_SUCCESS);
760: if (a->sf) { /* MatDuplicate_H2OPUS takes reference to the SF */
761: PetscCall(PetscSFGetGraph(a->sf, NULL, &n, NULL, NULL));
762: #if defined(PETSC_H2OPUS_USE_GPU)
763: a->xx_gpu = new thrust::device_vector<PetscScalar>(n);
764: a->yy_gpu = new thrust::device_vector<PetscScalar>(n);
765: a->xxs_gpu = 1;
766: a->yys_gpu = 1;
767: #endif
768: a->xx = new thrust::host_vector<PetscScalar>(n);
769: a->yy = new thrust::host_vector<PetscScalar>(n);
770: a->xxs = 1;
771: a->yys = 1;
772: } else {
773: IS is;
774: PetscCall(PetscObjectGetComm((PetscObject)A, &comm));
775: PetscCallMPI(MPI_Comm_size(comm, &size));
776: if (!a->h2opus_indexmap) {
777: if (size > 1) {
778: PetscCheck(a->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed CPU matrix");
779: #if defined(H2OPUS_USE_MPI)
780: iidx = MatH2OpusGetThrustPointer(a->dist_hmatrix->basis_tree.basis_branch.index_map);
781: n = a->dist_hmatrix->basis_tree.basis_branch.index_map.size();
782: #endif
783: } else {
784: iidx = MatH2OpusGetThrustPointer(a->hmatrix->u_basis_tree.index_map);
785: n = a->hmatrix->u_basis_tree.index_map.size();
786: }
788: if (PetscDefined(USE_64BIT_INDICES)) {
789: PetscInt i;
791: own = PETSC_OWN_POINTER;
792: PetscCall(PetscMalloc1(n, &idx));
793: for (i = 0; i < n; i++) idx[i] = iidx[i];
794: } else {
795: own = PETSC_COPY_VALUES;
796: idx = (PetscInt *)iidx;
797: }
798: PetscCall(ISCreateGeneral(comm, n, idx, own, &is));
799: PetscCall(ISSetPermutation(is));
800: PetscCall(ISViewFromOptions(is, (PetscObject)A, "-mat_h2opus_indexmap_view"));
801: a->h2opus_indexmap = is;
802: }
803: PetscCall(ISGetLocalSize(a->h2opus_indexmap, &n));
804: PetscCall(ISGetIndices(a->h2opus_indexmap, (const PetscInt **)&idx));
805: rid = (PetscBool)(n == A->rmap->n);
806: PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, &rid, 1, MPIU_BOOL, MPI_LAND, comm));
807: if (rid) PetscCall(ISIdentity(a->h2opus_indexmap, &rid));
808: if (!rid) {
809: if (size > 1) { /* Parallel distribution may be different, save it here for fast path in MatMult (see MatH2OpusSetNativeMult) */
810: PetscCall(PetscLayoutCreate(comm, &a->h2opus_rmap));
811: PetscCall(PetscLayoutSetLocalSize(a->h2opus_rmap, n));
812: PetscCall(PetscLayoutSetUp(a->h2opus_rmap));
813: PetscCall(PetscLayoutReference(a->h2opus_rmap, &a->h2opus_cmap));
814: }
815: PetscCall(PetscSFCreate(comm, &a->sf));
816: PetscCall(PetscSFSetGraphLayout(a->sf, A->rmap, n, NULL, PETSC_OWN_POINTER, idx));
817: PetscCall(PetscSFSetUp(a->sf));
818: PetscCall(PetscSFViewFromOptions(a->sf, (PetscObject)A, "-mat_h2opus_sf_view"));
819: #if defined(PETSC_H2OPUS_USE_GPU)
820: a->xx_gpu = new thrust::device_vector<PetscScalar>(n);
821: a->yy_gpu = new thrust::device_vector<PetscScalar>(n);
822: a->xxs_gpu = 1;
823: a->yys_gpu = 1;
824: #endif
825: a->xx = new thrust::host_vector<PetscScalar>(n);
826: a->yy = new thrust::host_vector<PetscScalar>(n);
827: a->xxs = 1;
828: a->yys = 1;
829: }
830: PetscCall(ISRestoreIndices(a->h2opus_indexmap, (const PetscInt **)&idx));
831: }
832: a->multsetup = PETSC_TRUE;
833: PetscFunctionReturn(PETSC_SUCCESS);
834: }
836: static PetscErrorCode MatAssemblyEnd_H2OPUS(Mat A, MatAssemblyType assemblytype)
837: {
838: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
839: #if defined(H2OPUS_USE_MPI)
840: h2opusHandle_t handle = a->handle->handle;
841: #else
842: h2opusHandle_t handle = a->handle;
843: #endif
844: PetscBool kernel = PETSC_FALSE;
845: PetscBool boundtocpu = PETSC_TRUE;
846: PetscBool samplingdone = PETSC_FALSE;
847: MPI_Comm comm;
848: PetscMPIInt size;
850: PetscFunctionBegin;
851: PetscCall(PetscObjectGetComm((PetscObject)A, &comm));
852: PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Different row and column local sizes are not supported");
853: PetscCheck(A->rmap->N == A->cmap->N, comm, PETSC_ERR_SUP, "Rectangular matrices are not supported");
855: /* XXX */
856: a->leafsize = PetscMin(a->leafsize, PetscMin(A->rmap->N, A->cmap->N));
858: PetscCallMPI(MPI_Comm_size(comm, &size));
859: /* TODO REUSABILITY of geometric construction */
860: delete a->hmatrix;
861: delete a->dist_hmatrix;
862: #if defined(PETSC_H2OPUS_USE_GPU)
863: delete a->hmatrix_gpu;
864: delete a->dist_hmatrix_gpu;
865: #endif
866: a->orthogonal = PETSC_FALSE;
868: /* TODO: other? */
869: H2OpusBoxCenterAdmissibility adm(a->eta);
871: PetscCall(PetscLogEventBegin(MAT_H2Opus_Build, A, 0, 0, 0));
872: if (size > 1) {
873: #if defined(H2OPUS_USE_MPI)
874: a->dist_hmatrix = new DistributedHMatrix(A->rmap->n /* ,A->symmetric */);
875: #else
876: a->dist_hmatrix = NULL;
877: #endif
878: } else a->hmatrix = new HMatrix(A->rmap->n, A->symmetric == PETSC_BOOL3_TRUE);
879: PetscCall(MatH2OpusInferCoordinates_Private(A));
880: PetscCheck(a->ptcloud, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing pointcloud");
881: if (a->kernel) {
882: BoxEntryGen<PetscScalar, H2OPUS_HWTYPE_CPU, PetscFunctionGenerator<PetscScalar>> entry_gen(*a->kernel);
883: if (size > 1) {
884: PetscCheck(a->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed CPU matrix");
885: #if defined(H2OPUS_USE_MPI)
886: buildDistributedHMatrix(*a->dist_hmatrix, a->ptcloud, adm, entry_gen, a->leafsize, a->basisord, a->handle);
887: #endif
888: } else {
889: buildHMatrix(*a->hmatrix, a->ptcloud, adm, entry_gen, a->leafsize, a->basisord);
890: }
891: kernel = PETSC_TRUE;
892: } else {
893: PetscCheck(size <= 1, comm, PETSC_ERR_SUP, "Construction from sampling not supported in parallel");
894: buildHMatrixStructure(*a->hmatrix, a->ptcloud, a->leafsize, adm);
895: }
896: PetscCall(MatSetUpMultiply_H2OPUS(A));
898: #if defined(PETSC_H2OPUS_USE_GPU)
899: boundtocpu = A->boundtocpu;
900: if (!boundtocpu) {
901: if (size > 1) {
902: PetscCheck(a->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing distributed CPU matrix");
903: #if defined(H2OPUS_USE_MPI)
904: a->dist_hmatrix_gpu = new DistributedHMatrix_GPU(*a->dist_hmatrix);
905: #endif
906: } else {
907: a->hmatrix_gpu = new HMatrix_GPU(*a->hmatrix);
908: }
909: }
910: #endif
911: if (size == 1) {
912: if (!kernel && a->sampler && a->sampler->GetSamplingMat()) {
913: PetscReal Anorm;
914: bool verbose;
916: PetscCall(PetscOptionsGetBool(((PetscObject)A)->options, ((PetscObject)A)->prefix, "-mat_h2opus_hara_verbose", &a->hara_verbose, NULL));
917: verbose = a->hara_verbose;
918: PetscCall(MatApproximateNorm_Private(a->sampler->GetSamplingMat(), NORM_2, a->norm_max_samples, &Anorm));
919: if (a->hara_verbose) PetscCall(PetscPrintf(PETSC_COMM_SELF, "Sampling uses max rank %d, tol %g (%g*%g), %s samples %d\n", a->max_rank, a->rtol * Anorm, a->rtol, Anorm, boundtocpu ? "CPU" : "GPU", a->bs));
920: if (a->sf && !a->nativemult) a->sampler->SetIndexMap(a->hmatrix->u_basis_tree.index_map.size(), a->hmatrix->u_basis_tree.index_map.data());
921: a->sampler->SetStream(handle->getMainStream());
922: if (boundtocpu) {
923: a->sampler->SetGPUSampling(false);
924: hara(a->sampler, *a->hmatrix, a->max_rank, 10 /* TODO */, a->rtol * Anorm, a->bs, handle, verbose);
925: #if defined(PETSC_H2OPUS_USE_GPU)
926: } else {
927: a->sampler->SetGPUSampling(true);
928: hara(a->sampler, *a->hmatrix_gpu, a->max_rank, 10 /* TODO */, a->rtol * Anorm, a->bs, handle, verbose);
929: #endif
930: }
931: samplingdone = PETSC_TRUE;
932: }
933: }
934: #if defined(PETSC_H2OPUS_USE_GPU)
935: if (!boundtocpu) {
936: delete a->hmatrix;
937: delete a->dist_hmatrix;
938: a->hmatrix = NULL;
939: a->dist_hmatrix = NULL;
940: }
941: A->offloadmask = boundtocpu ? PETSC_OFFLOAD_CPU : PETSC_OFFLOAD_GPU;
942: #endif
943: PetscCall(PetscLogEventEnd(MAT_H2Opus_Build, A, 0, 0, 0));
945: if (!a->s) a->s = 1.0;
946: A->assembled = PETSC_TRUE;
948: if (samplingdone) {
949: PetscBool check = a->check_construction;
950: PetscBool checke = PETSC_FALSE;
952: PetscCall(PetscOptionsGetBool(((PetscObject)A)->options, ((PetscObject)A)->prefix, "-mat_h2opus_check", &check, NULL));
953: PetscCall(PetscOptionsGetBool(((PetscObject)A)->options, ((PetscObject)A)->prefix, "-mat_h2opus_check_explicit", &checke, NULL));
954: if (check) {
955: Mat E, Ae;
956: PetscReal n1, ni, n2;
957: PetscReal n1A, niA, n2A;
958: void (*normfunc)(void);
960: Ae = a->sampler->GetSamplingMat();
961: PetscCall(MatConvert(A, MATSHELL, MAT_INITIAL_MATRIX, &E));
962: PetscCall(MatShellSetOperation(E, MATOP_NORM, (void (*)(void))MatNorm_H2OPUS));
963: PetscCall(MatAXPY(E, -1.0, Ae, DIFFERENT_NONZERO_PATTERN));
964: PetscCall(MatNorm(E, NORM_1, &n1));
965: PetscCall(MatNorm(E, NORM_INFINITY, &ni));
966: PetscCall(MatNorm(E, NORM_2, &n2));
967: if (checke) {
968: Mat eA, eE, eAe;
970: PetscCall(MatComputeOperator(A, MATAIJ, &eA));
971: PetscCall(MatComputeOperator(E, MATAIJ, &eE));
972: PetscCall(MatComputeOperator(Ae, MATAIJ, &eAe));
973: PetscCall(MatFilter(eA, PETSC_SMALL, PETSC_FALSE, PETSC_FALSE));
974: PetscCall(MatFilter(eE, PETSC_SMALL, PETSC_FALSE, PETSC_FALSE));
975: PetscCall(MatFilter(eAe, PETSC_SMALL, PETSC_FALSE, PETSC_FALSE));
976: PetscCall(PetscObjectSetName((PetscObject)eA, "H2Mat"));
977: PetscCall(MatView(eA, NULL));
978: PetscCall(PetscObjectSetName((PetscObject)eAe, "S"));
979: PetscCall(MatView(eAe, NULL));
980: PetscCall(PetscObjectSetName((PetscObject)eE, "H2Mat - S"));
981: PetscCall(MatView(eE, NULL));
982: PetscCall(MatDestroy(&eA));
983: PetscCall(MatDestroy(&eE));
984: PetscCall(MatDestroy(&eAe));
985: }
987: PetscCall(MatGetOperation(Ae, MATOP_NORM, &normfunc));
988: PetscCall(MatSetOperation(Ae, MATOP_NORM, (void (*)(void))MatNorm_H2OPUS));
989: PetscCall(MatNorm(Ae, NORM_1, &n1A));
990: PetscCall(MatNorm(Ae, NORM_INFINITY, &niA));
991: PetscCall(MatNorm(Ae, NORM_2, &n2A));
992: n1A = PetscMax(n1A, PETSC_SMALL);
993: n2A = PetscMax(n2A, PETSC_SMALL);
994: niA = PetscMax(niA, PETSC_SMALL);
995: PetscCall(MatSetOperation(Ae, MATOP_NORM, normfunc));
996: PetscCall(PetscPrintf(PetscObjectComm((PetscObject)A), "MATH2OPUS construction errors: NORM_1 %g, NORM_INFINITY %g, NORM_2 %g (%g %g %g)\n", (double)n1, (double)ni, (double)n2, (double)(n1 / n1A), (double)(ni / niA), (double)(n2 / n2A)));
997: PetscCall(MatDestroy(&E));
998: }
999: a->sampler->SetSamplingMat(NULL);
1000: }
1001: PetscFunctionReturn(PETSC_SUCCESS);
1002: }
1004: static PetscErrorCode MatZeroEntries_H2OPUS(Mat A)
1005: {
1006: PetscMPIInt size;
1007: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1009: PetscFunctionBegin;
1010: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1011: PetscCheck(size <= 1, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Not yet supported");
1012: a->hmatrix->clearData();
1013: #if defined(PETSC_H2OPUS_USE_GPU)
1014: if (a->hmatrix_gpu) a->hmatrix_gpu->clearData();
1015: #endif
1016: PetscFunctionReturn(PETSC_SUCCESS);
1017: }
1019: static PetscErrorCode MatDuplicate_H2OPUS(Mat B, MatDuplicateOption op, Mat *nA)
1020: {
1021: Mat A;
1022: Mat_H2OPUS *a, *b = (Mat_H2OPUS *)B->data;
1023: #if defined(PETSC_H2OPUS_USE_GPU)
1024: PetscBool iscpu = PETSC_FALSE;
1025: #else
1026: PetscBool iscpu = PETSC_TRUE;
1027: #endif
1028: MPI_Comm comm;
1030: PetscFunctionBegin;
1031: PetscCall(PetscObjectGetComm((PetscObject)B, &comm));
1032: PetscCall(MatCreate(comm, &A));
1033: PetscCall(MatSetSizes(A, B->rmap->n, B->cmap->n, B->rmap->N, B->cmap->N));
1034: PetscCall(MatSetType(A, MATH2OPUS));
1035: PetscCall(MatPropagateSymmetryOptions(B, A));
1036: a = (Mat_H2OPUS *)A->data;
1038: a->eta = b->eta;
1039: a->leafsize = b->leafsize;
1040: a->basisord = b->basisord;
1041: a->max_rank = b->max_rank;
1042: a->bs = b->bs;
1043: a->rtol = b->rtol;
1044: a->norm_max_samples = b->norm_max_samples;
1045: if (op == MAT_COPY_VALUES) a->s = b->s;
1047: a->ptcloud = new PetscPointCloud<PetscReal>(*b->ptcloud);
1048: if (op == MAT_COPY_VALUES && b->kernel) a->kernel = new PetscFunctionGenerator<PetscScalar>(*b->kernel);
1050: #if defined(H2OPUS_USE_MPI)
1051: if (b->dist_hmatrix) a->dist_hmatrix = new DistributedHMatrix(*b->dist_hmatrix);
1052: #if defined(PETSC_H2OPUS_USE_GPU)
1053: if (b->dist_hmatrix_gpu) a->dist_hmatrix_gpu = new DistributedHMatrix_GPU(*b->dist_hmatrix_gpu);
1054: #endif
1055: #endif
1056: if (b->hmatrix) {
1057: a->hmatrix = new HMatrix(*b->hmatrix);
1058: if (op == MAT_DO_NOT_COPY_VALUES) a->hmatrix->clearData();
1059: }
1060: #if defined(PETSC_H2OPUS_USE_GPU)
1061: if (b->hmatrix_gpu) {
1062: a->hmatrix_gpu = new HMatrix_GPU(*b->hmatrix_gpu);
1063: if (op == MAT_DO_NOT_COPY_VALUES) a->hmatrix_gpu->clearData();
1064: }
1065: #endif
1066: if (b->sf) {
1067: PetscCall(PetscObjectReference((PetscObject)b->sf));
1068: a->sf = b->sf;
1069: }
1070: if (b->h2opus_indexmap) {
1071: PetscCall(PetscObjectReference((PetscObject)b->h2opus_indexmap));
1072: a->h2opus_indexmap = b->h2opus_indexmap;
1073: }
1075: PetscCall(MatSetUp(A));
1076: PetscCall(MatSetUpMultiply_H2OPUS(A));
1077: if (op == MAT_COPY_VALUES) {
1078: A->assembled = PETSC_TRUE;
1079: a->orthogonal = b->orthogonal;
1080: #if defined(PETSC_H2OPUS_USE_GPU)
1081: A->offloadmask = B->offloadmask;
1082: #endif
1083: }
1084: #if defined(PETSC_H2OPUS_USE_GPU)
1085: iscpu = B->boundtocpu;
1086: #endif
1087: PetscCall(MatBindToCPU(A, iscpu));
1089: *nA = A;
1090: PetscFunctionReturn(PETSC_SUCCESS);
1091: }
1093: static PetscErrorCode MatView_H2OPUS(Mat A, PetscViewer view)
1094: {
1095: Mat_H2OPUS *h2opus = (Mat_H2OPUS *)A->data;
1096: PetscBool isascii, vieweps;
1097: PetscMPIInt size;
1098: PetscViewerFormat format;
1100: PetscFunctionBegin;
1101: PetscCall(PetscObjectTypeCompare((PetscObject)view, PETSCVIEWERASCII, &isascii));
1102: PetscCall(PetscViewerGetFormat(view, &format));
1103: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1104: if (isascii) {
1105: if (format == PETSC_VIEWER_ASCII_MATLAB) {
1106: if (size == 1) {
1107: FILE *fp;
1108: PetscCall(PetscViewerASCIIGetPointer(view, &fp));
1109: dumpHMatrix(*h2opus->hmatrix, 6, fp);
1110: }
1111: } else {
1112: PetscCall(PetscViewerASCIIPrintf(view, " H-Matrix constructed from %s\n", h2opus->kernel ? "Kernel" : "Mat"));
1113: PetscCall(PetscViewerASCIIPrintf(view, " PointCloud dim %" PetscInt_FMT "\n", h2opus->ptcloud ? h2opus->ptcloud->getDimension() : 0));
1114: PetscCall(PetscViewerASCIIPrintf(view, " Admissibility parameters: leaf size %" PetscInt_FMT ", eta %g\n", h2opus->leafsize, (double)h2opus->eta));
1115: if (!h2opus->kernel) {
1116: PetscCall(PetscViewerASCIIPrintf(view, " Sampling parameters: max_rank %" PetscInt_FMT ", samples %" PetscInt_FMT ", tolerance %g\n", h2opus->max_rank, h2opus->bs, (double)h2opus->rtol));
1117: } else {
1118: PetscCall(PetscViewerASCIIPrintf(view, " Off-diagonal blocks approximation order %" PetscInt_FMT "\n", h2opus->basisord));
1119: }
1120: PetscCall(PetscViewerASCIIPrintf(view, " Number of samples for norms %" PetscInt_FMT "\n", h2opus->norm_max_samples));
1121: if (size == 1) {
1122: double dense_mem_cpu = h2opus->hmatrix ? h2opus->hmatrix->getDenseMemoryUsage() : 0;
1123: double low_rank_cpu = h2opus->hmatrix ? h2opus->hmatrix->getLowRankMemoryUsage() : 0;
1124: #if defined(PETSC_HAVE_CUDA)
1125: double dense_mem_gpu = h2opus->hmatrix_gpu ? h2opus->hmatrix_gpu->getDenseMemoryUsage() : 0;
1126: double low_rank_gpu = h2opus->hmatrix_gpu ? h2opus->hmatrix_gpu->getLowRankMemoryUsage() : 0;
1127: #endif
1128: PetscCall(PetscViewerASCIIPrintf(view, " Memory consumption GB (CPU): %g (dense) %g (low rank) %g (total)\n", dense_mem_cpu, low_rank_cpu, low_rank_cpu + dense_mem_cpu));
1129: #if defined(PETSC_HAVE_CUDA)
1130: PetscCall(PetscViewerASCIIPrintf(view, " Memory consumption GB (GPU): %g (dense) %g (low rank) %g (total)\n", dense_mem_gpu, low_rank_gpu, low_rank_gpu + dense_mem_gpu));
1131: #endif
1132: } else {
1133: #if defined(PETSC_HAVE_CUDA)
1134: double matrix_mem[4] = {0., 0., 0., 0.};
1135: PetscMPIInt rsize = 4;
1136: #else
1137: double matrix_mem[2] = {0., 0.};
1138: PetscMPIInt rsize = 2;
1139: #endif
1140: #if defined(H2OPUS_USE_MPI)
1141: matrix_mem[0] = h2opus->dist_hmatrix ? h2opus->dist_hmatrix->getLocalDenseMemoryUsage() : 0;
1142: matrix_mem[1] = h2opus->dist_hmatrix ? h2opus->dist_hmatrix->getLocalLowRankMemoryUsage() : 0;
1143: #if defined(PETSC_HAVE_CUDA)
1144: matrix_mem[2] = h2opus->dist_hmatrix_gpu ? h2opus->dist_hmatrix_gpu->getLocalDenseMemoryUsage() : 0;
1145: matrix_mem[3] = h2opus->dist_hmatrix_gpu ? h2opus->dist_hmatrix_gpu->getLocalLowRankMemoryUsage() : 0;
1146: #endif
1147: #endif
1148: PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, matrix_mem, rsize, MPI_DOUBLE_PRECISION, MPI_SUM, PetscObjectComm((PetscObject)A)));
1149: PetscCall(PetscViewerASCIIPrintf(view, " Memory consumption GB (CPU): %g (dense) %g (low rank) %g (total)\n", matrix_mem[0], matrix_mem[1], matrix_mem[0] + matrix_mem[1]));
1150: #if defined(PETSC_HAVE_CUDA)
1151: PetscCall(PetscViewerASCIIPrintf(view, " Memory consumption GB (GPU): %g (dense) %g (low rank) %g (total)\n", matrix_mem[2], matrix_mem[3], matrix_mem[2] + matrix_mem[3]));
1152: #endif
1153: }
1154: }
1155: }
1156: vieweps = PETSC_FALSE;
1157: PetscCall(PetscOptionsGetBool(((PetscObject)A)->options, ((PetscObject)A)->prefix, "-mat_h2opus_vieweps", &vieweps, NULL));
1158: if (vieweps) {
1159: char filename[256];
1160: const char *name;
1162: PetscCall(PetscObjectGetName((PetscObject)A, &name));
1163: PetscCall(PetscSNPrintf(filename, sizeof(filename), "%s_structure.eps", name));
1164: PetscCall(PetscOptionsGetString(((PetscObject)A)->options, ((PetscObject)A)->prefix, "-mat_h2opus_vieweps_filename", filename, sizeof(filename), NULL));
1165: outputEps(*h2opus->hmatrix, filename);
1166: }
1167: PetscFunctionReturn(PETSC_SUCCESS);
1168: }
1170: static PetscErrorCode MatH2OpusSetCoords_H2OPUS(Mat A, PetscInt spacedim, const PetscReal coords[], PetscBool cdist, MatH2OpusKernelFn *kernel, void *kernelctx)
1171: {
1172: Mat_H2OPUS *h2opus = (Mat_H2OPUS *)A->data;
1173: PetscReal *gcoords;
1174: PetscInt N;
1175: MPI_Comm comm;
1176: PetscMPIInt size;
1177: PetscBool cong;
1179: PetscFunctionBegin;
1180: PetscCall(PetscLayoutSetUp(A->rmap));
1181: PetscCall(PetscLayoutSetUp(A->cmap));
1182: PetscCall(PetscObjectGetComm((PetscObject)A, &comm));
1183: PetscCall(MatHasCongruentLayouts(A, &cong));
1184: PetscCheck(cong, comm, PETSC_ERR_SUP, "Only for square matrices with congruent layouts");
1185: N = A->rmap->N;
1186: PetscCallMPI(MPI_Comm_size(comm, &size));
1187: if (spacedim > 0 && size > 1 && cdist) {
1188: PetscSF sf;
1189: MPI_Datatype dtype;
1191: PetscCallMPI(MPI_Type_contiguous(spacedim, MPIU_REAL, &dtype));
1192: PetscCallMPI(MPI_Type_commit(&dtype));
1194: PetscCall(PetscSFCreate(comm, &sf));
1195: PetscCall(PetscSFSetGraphWithPattern(sf, A->rmap, PETSCSF_PATTERN_ALLGATHER));
1196: PetscCall(PetscMalloc1(spacedim * N, &gcoords));
1197: PetscCall(PetscSFBcastBegin(sf, dtype, coords, gcoords, MPI_REPLACE));
1198: PetscCall(PetscSFBcastEnd(sf, dtype, coords, gcoords, MPI_REPLACE));
1199: PetscCall(PetscSFDestroy(&sf));
1200: PetscCallMPI(MPI_Type_free(&dtype));
1201: } else gcoords = (PetscReal *)coords;
1203: delete h2opus->ptcloud;
1204: delete h2opus->kernel;
1205: h2opus->ptcloud = new PetscPointCloud<PetscReal>(spacedim, N, gcoords);
1206: if (kernel) h2opus->kernel = new PetscFunctionGenerator<PetscScalar>(kernel, spacedim, kernelctx);
1207: if (gcoords != coords) PetscCall(PetscFree(gcoords));
1208: A->preallocated = PETSC_TRUE;
1209: PetscFunctionReturn(PETSC_SUCCESS);
1210: }
1212: #if defined(PETSC_H2OPUS_USE_GPU)
1213: static PetscErrorCode MatBindToCPU_H2OPUS(Mat A, PetscBool flg)
1214: {
1215: PetscMPIInt size;
1216: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1218: PetscFunctionBegin;
1219: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1220: if (flg && A->offloadmask == PETSC_OFFLOAD_GPU) {
1221: if (size > 1) {
1222: PetscCheck(a->dist_hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1223: #if defined(H2OPUS_USE_MPI)
1224: if (!a->dist_hmatrix) a->dist_hmatrix = new DistributedHMatrix(*a->dist_hmatrix_gpu);
1225: else *a->dist_hmatrix = *a->dist_hmatrix_gpu;
1226: #endif
1227: } else {
1228: PetscCheck(a->hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1229: if (!a->hmatrix) a->hmatrix = new HMatrix(*a->hmatrix_gpu);
1230: else *a->hmatrix = *a->hmatrix_gpu;
1231: }
1232: delete a->hmatrix_gpu;
1233: delete a->dist_hmatrix_gpu;
1234: a->hmatrix_gpu = NULL;
1235: a->dist_hmatrix_gpu = NULL;
1236: A->offloadmask = PETSC_OFFLOAD_CPU;
1237: } else if (!flg && A->offloadmask == PETSC_OFFLOAD_CPU) {
1238: if (size > 1) {
1239: PetscCheck(a->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1240: #if defined(H2OPUS_USE_MPI)
1241: if (!a->dist_hmatrix_gpu) a->dist_hmatrix_gpu = new DistributedHMatrix_GPU(*a->dist_hmatrix);
1242: else *a->dist_hmatrix_gpu = *a->dist_hmatrix;
1243: #endif
1244: } else {
1245: PetscCheck(a->hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1246: if (!a->hmatrix_gpu) a->hmatrix_gpu = new HMatrix_GPU(*a->hmatrix);
1247: else *a->hmatrix_gpu = *a->hmatrix;
1248: }
1249: delete a->hmatrix;
1250: delete a->dist_hmatrix;
1251: a->hmatrix = NULL;
1252: a->dist_hmatrix = NULL;
1253: A->offloadmask = PETSC_OFFLOAD_GPU;
1254: }
1255: PetscCall(PetscFree(A->defaultvectype));
1256: if (!flg) {
1257: PetscCall(PetscStrallocpy(VECCUDA, &A->defaultvectype));
1258: } else {
1259: PetscCall(PetscStrallocpy(VECSTANDARD, &A->defaultvectype));
1260: }
1261: A->boundtocpu = flg;
1262: PetscFunctionReturn(PETSC_SUCCESS);
1263: }
1264: #endif
1266: /*MC
1267: MATH2OPUS = "h2opus" - A matrix type for hierarchical matrices using the H2Opus package {cite}`zampinibouakaramturkiyyahkniokeyes2022`.
1269: Options Database Key:
1270: . -mat_type h2opus - matrix type to "h2opus"
1272: Level: beginner
1274: Notes:
1275: H2Opus implements hierarchical matrices in the $H^2$ flavour. It supports CPU or NVIDIA GPUs.
1277: For CPU only builds, use `./configure --download-h2opus --download-thrust` to install PETSc to use H2Opus.
1278: In order to run on NVIDIA GPUs, use `./configure --download-h2opus --download-magma --download-kblas`.
1280: .seealso: [](ch_matrices), `Mat`, `MATH2OPUS`, `MATHTOOL`, `MATDENSE`, `MatCreateH2OpusFromKernel()`, `MatCreateH2OpusFromMat()`
1281: M*/
1282: PETSC_EXTERN PetscErrorCode MatCreate_H2OPUS(Mat A)
1283: {
1284: Mat_H2OPUS *a;
1285: PetscMPIInt size;
1287: PetscFunctionBegin;
1288: #if defined(PETSC_H2OPUS_USE_GPU)
1289: PetscCall(PetscDeviceInitialize(PETSC_DEVICE_CUDA));
1290: #endif
1291: PetscCall(PetscNew(&a));
1292: A->data = (void *)a;
1294: a->eta = 0.9;
1295: a->leafsize = 32;
1296: a->basisord = 4;
1297: a->max_rank = 64;
1298: a->bs = 32;
1299: a->rtol = 1.e-4;
1300: a->s = 1.0;
1301: a->norm_max_samples = 10;
1302: a->resize = PETSC_TRUE; /* reallocate after compression */
1303: #if defined(H2OPUS_USE_MPI)
1304: h2opusCreateDistributedHandleComm(&a->handle, PetscObjectComm((PetscObject)A));
1305: #else
1306: h2opusCreateHandle(&a->handle);
1307: #endif
1308: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1309: PetscCall(PetscObjectChangeTypeName((PetscObject)A, MATH2OPUS));
1310: PetscCall(PetscMemzero(A->ops, sizeof(struct _MatOps)));
1312: A->ops->destroy = MatDestroy_H2OPUS;
1313: A->ops->view = MatView_H2OPUS;
1314: A->ops->assemblyend = MatAssemblyEnd_H2OPUS;
1315: A->ops->mult = MatMult_H2OPUS;
1316: A->ops->multtranspose = MatMultTranspose_H2OPUS;
1317: A->ops->multadd = MatMultAdd_H2OPUS;
1318: A->ops->multtransposeadd = MatMultTransposeAdd_H2OPUS;
1319: A->ops->scale = MatScale_H2OPUS;
1320: A->ops->duplicate = MatDuplicate_H2OPUS;
1321: A->ops->setfromoptions = MatSetFromOptions_H2OPUS;
1322: A->ops->norm = MatNorm_H2OPUS;
1323: A->ops->zeroentries = MatZeroEntries_H2OPUS;
1324: #if defined(PETSC_H2OPUS_USE_GPU)
1325: A->ops->bindtocpu = MatBindToCPU_H2OPUS;
1326: #endif
1328: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_seqdense_C", MatProductSetFromOptions_H2OPUS));
1329: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_seqdensecuda_C", MatProductSetFromOptions_H2OPUS));
1330: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_mpidense_C", MatProductSetFromOptions_H2OPUS));
1331: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatProductSetFromOptions_h2opus_mpidensecuda_C", MatProductSetFromOptions_H2OPUS));
1332: #if defined(PETSC_H2OPUS_USE_GPU)
1333: PetscCall(PetscFree(A->defaultvectype));
1334: PetscCall(PetscStrallocpy(VECCUDA, &A->defaultvectype));
1335: #endif
1336: PetscFunctionReturn(PETSC_SUCCESS);
1337: }
1339: /*@
1340: MatH2OpusOrthogonalize - Orthogonalize the basis tree of a hierarchical matrix.
1342: Input Parameter:
1343: . A - the matrix
1345: Level: intermediate
1347: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`, `MatCreateH2OpusFromKernel()`, `MatH2OpusCompress()`
1348: @*/
1349: PetscErrorCode MatH2OpusOrthogonalize(Mat A)
1350: {
1351: PetscBool ish2opus;
1352: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1353: PetscMPIInt size;
1354: PetscBool boundtocpu = PETSC_TRUE;
1356: PetscFunctionBegin;
1359: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
1360: if (!ish2opus) PetscFunctionReturn(PETSC_SUCCESS);
1361: if (a->orthogonal) PetscFunctionReturn(PETSC_SUCCESS);
1362: HLibProfile::clear();
1363: PetscCall(PetscLogEventBegin(MAT_H2Opus_Orthog, A, 0, 0, 0));
1364: #if defined(PETSC_H2OPUS_USE_GPU)
1365: boundtocpu = A->boundtocpu;
1366: #endif
1367: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1368: if (size > 1) {
1369: if (boundtocpu) {
1370: PetscCheck(a->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1371: #if defined(H2OPUS_USE_MPI)
1372: distributed_horthog(*a->dist_hmatrix, a->handle);
1373: #endif
1374: #if defined(PETSC_H2OPUS_USE_GPU)
1375: A->offloadmask = PETSC_OFFLOAD_CPU;
1376: } else {
1377: PetscCheck(a->dist_hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1378: PetscCall(PetscLogGpuTimeBegin());
1379: #if defined(H2OPUS_USE_MPI)
1380: distributed_horthog(*a->dist_hmatrix_gpu, a->handle);
1381: #endif
1382: PetscCall(PetscLogGpuTimeEnd());
1383: #endif
1384: }
1385: } else {
1386: #if defined(H2OPUS_USE_MPI)
1387: h2opusHandle_t handle = a->handle->handle;
1388: #else
1389: h2opusHandle_t handle = a->handle;
1390: #endif
1391: if (boundtocpu) {
1392: PetscCheck(a->hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1393: horthog(*a->hmatrix, handle);
1394: #if defined(PETSC_H2OPUS_USE_GPU)
1395: A->offloadmask = PETSC_OFFLOAD_CPU;
1396: } else {
1397: PetscCheck(a->hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1398: PetscCall(PetscLogGpuTimeBegin());
1399: horthog(*a->hmatrix_gpu, handle);
1400: PetscCall(PetscLogGpuTimeEnd());
1401: #endif
1402: }
1403: }
1404: a->orthogonal = PETSC_TRUE;
1405: { /* log flops */
1406: double gops, time, perf, dev;
1407: HLibProfile::getHorthogPerf(gops, time, perf, dev);
1408: #if defined(PETSC_H2OPUS_USE_GPU)
1409: if (boundtocpu) {
1410: PetscCall(PetscLogFlops(1e9 * gops));
1411: } else {
1412: PetscCall(PetscLogGpuFlops(1e9 * gops));
1413: }
1414: #else
1415: PetscCall(PetscLogFlops(1e9 * gops));
1416: #endif
1417: }
1418: PetscCall(PetscLogEventEnd(MAT_H2Opus_Orthog, A, 0, 0, 0));
1419: PetscFunctionReturn(PETSC_SUCCESS);
1420: }
1422: /*@
1423: MatH2OpusCompress - Compress a hierarchical matrix.
1425: Input Parameters:
1426: + A - the matrix
1427: - tol - the absolute truncation threshold
1429: Level: intermediate
1431: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`, `MatCreateH2OpusFromKernel()`, `MatH2OpusOrthogonalize()`
1432: @*/
1433: PetscErrorCode MatH2OpusCompress(Mat A, PetscReal tol)
1434: {
1435: PetscBool ish2opus;
1436: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1437: PetscMPIInt size;
1438: PetscBool boundtocpu = PETSC_TRUE;
1440: PetscFunctionBegin;
1444: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
1445: if (!ish2opus || tol <= 0.0) PetscFunctionReturn(PETSC_SUCCESS);
1446: PetscCall(MatH2OpusOrthogonalize(A));
1447: HLibProfile::clear();
1448: PetscCall(PetscLogEventBegin(MAT_H2Opus_Compress, A, 0, 0, 0));
1449: #if defined(PETSC_H2OPUS_USE_GPU)
1450: boundtocpu = A->boundtocpu;
1451: #endif
1452: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1453: if (size > 1) {
1454: if (boundtocpu) {
1455: PetscCheck(a->dist_hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1456: #if defined(H2OPUS_USE_MPI)
1457: distributed_hcompress(*a->dist_hmatrix, tol, a->handle);
1458: if (a->resize) {
1459: DistributedHMatrix *dist_hmatrix = new DistributedHMatrix(*a->dist_hmatrix);
1460: delete a->dist_hmatrix;
1461: a->dist_hmatrix = dist_hmatrix;
1462: }
1463: #endif
1464: #if defined(PETSC_H2OPUS_USE_GPU)
1465: A->offloadmask = PETSC_OFFLOAD_CPU;
1466: } else {
1467: PetscCheck(a->dist_hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1468: PetscCall(PetscLogGpuTimeBegin());
1469: #if defined(H2OPUS_USE_MPI)
1470: distributed_hcompress(*a->dist_hmatrix_gpu, tol, a->handle);
1472: if (a->resize) {
1473: DistributedHMatrix_GPU *dist_hmatrix_gpu = new DistributedHMatrix_GPU(*a->dist_hmatrix_gpu);
1474: delete a->dist_hmatrix_gpu;
1475: a->dist_hmatrix_gpu = dist_hmatrix_gpu;
1476: }
1477: #endif
1478: PetscCall(PetscLogGpuTimeEnd());
1479: #endif
1480: }
1481: } else {
1482: #if defined(H2OPUS_USE_MPI)
1483: h2opusHandle_t handle = a->handle->handle;
1484: #else
1485: h2opusHandle_t handle = a->handle;
1486: #endif
1487: if (boundtocpu) {
1488: PetscCheck(a->hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1489: hcompress(*a->hmatrix, tol, handle);
1491: if (a->resize) {
1492: HMatrix *hmatrix = new HMatrix(*a->hmatrix);
1493: delete a->hmatrix;
1494: a->hmatrix = hmatrix;
1495: }
1496: #if defined(PETSC_H2OPUS_USE_GPU)
1497: A->offloadmask = PETSC_OFFLOAD_CPU;
1498: } else {
1499: PetscCheck(a->hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1500: PetscCall(PetscLogGpuTimeBegin());
1501: hcompress(*a->hmatrix_gpu, tol, handle);
1502: PetscCall(PetscLogGpuTimeEnd());
1504: if (a->resize) {
1505: HMatrix_GPU *hmatrix_gpu = new HMatrix_GPU(*a->hmatrix_gpu);
1506: delete a->hmatrix_gpu;
1507: a->hmatrix_gpu = hmatrix_gpu;
1508: }
1509: #endif
1510: }
1511: }
1512: { /* log flops */
1513: double gops, time, perf, dev;
1514: HLibProfile::getHcompressPerf(gops, time, perf, dev);
1515: #if defined(PETSC_H2OPUS_USE_GPU)
1516: if (boundtocpu) {
1517: PetscCall(PetscLogFlops(1e9 * gops));
1518: } else {
1519: PetscCall(PetscLogGpuFlops(1e9 * gops));
1520: }
1521: #else
1522: PetscCall(PetscLogFlops(1e9 * gops));
1523: #endif
1524: }
1525: PetscCall(PetscLogEventEnd(MAT_H2Opus_Compress, A, 0, 0, 0));
1526: PetscFunctionReturn(PETSC_SUCCESS);
1527: }
1529: /*@
1530: MatH2OpusSetSamplingMat - Set a matrix to be sampled from matrix-vector products on another matrix to construct a hierarchical matrix.
1532: Input Parameters:
1533: + A - the hierarchical matrix
1534: . B - the matrix to be sampled
1535: . bs - maximum number of samples to be taken concurrently
1536: - tol - relative tolerance for construction
1538: Level: intermediate
1540: Notes:
1541: You need to call `MatAssemblyBegin()` and `MatAssemblyEnd()` to update the hierarchical matrix.
1543: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`, `MatCreateH2OpusFromKernel()`, `MatH2OpusCompress()`, `MatH2OpusOrthogonalize()`
1544: @*/
1545: PetscErrorCode MatH2OpusSetSamplingMat(Mat A, Mat B, PetscInt bs, PetscReal tol)
1546: {
1547: PetscBool ish2opus;
1549: PetscFunctionBegin;
1555: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
1556: if (ish2opus) {
1557: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1559: if (!a->sampler) a->sampler = new PetscMatrixSampler();
1560: a->sampler->SetSamplingMat(B);
1561: if (bs > 0) a->bs = bs;
1562: if (tol > 0.) a->rtol = tol;
1563: delete a->kernel;
1564: }
1565: PetscFunctionReturn(PETSC_SUCCESS);
1566: }
1568: /*@C
1569: MatCreateH2OpusFromKernel - Creates a `MATH2OPUS` from a user-supplied kernel.
1571: Input Parameters:
1572: + comm - MPI communicator
1573: . m - number of local rows (or `PETSC_DECIDE` to have calculated if `M` is given)
1574: . n - number of local columns (or `PETSC_DECIDE` to have calculated if `N` is given)
1575: . M - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given)
1576: . N - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given)
1577: . spacedim - dimension of the space coordinates
1578: . coords - coordinates of the points
1579: . cdist - whether or not coordinates are distributed
1580: . kernel - computational kernel (or `NULL`)
1581: . kernelctx - kernel context
1582: . eta - admissibility condition tolerance
1583: . leafsize - leaf size in cluster tree
1584: - basisord - approximation order for Chebychev interpolation of low-rank blocks
1586: Output Parameter:
1587: . nA - matrix
1589: Options Database Keys:
1590: + -mat_h2opus_leafsize <`PetscInt`> - Leaf size of cluster tree
1591: . -mat_h2opus_eta <`PetscReal`> - Admissibility condition tolerance
1592: . -mat_h2opus_order <`PetscInt`> - Chebychev approximation order
1593: - -mat_h2opus_normsamples <`PetscInt`> - Maximum number of samples to be used when estimating norms
1595: Level: intermediate
1597: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`
1598: @*/
1599: PetscErrorCode MatCreateH2OpusFromKernel(MPI_Comm comm, PetscInt m, PetscInt n, PetscInt M, PetscInt N, PetscInt spacedim, const PetscReal coords[], PetscBool cdist, MatH2OpusKernelFn *kernel, void *kernelctx, PetscReal eta, PetscInt leafsize, PetscInt basisord, Mat *nA)
1600: {
1601: Mat A;
1602: Mat_H2OPUS *h2opus;
1603: #if defined(PETSC_H2OPUS_USE_GPU)
1604: PetscBool iscpu = PETSC_FALSE;
1605: #else
1606: PetscBool iscpu = PETSC_TRUE;
1607: #endif
1609: PetscFunctionBegin;
1610: PetscCheck(m == n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Different row and column local sizes are not supported");
1611: PetscCall(MatCreate(comm, &A));
1612: PetscCall(MatSetSizes(A, m, n, M, N));
1613: PetscCheck(M == N, comm, PETSC_ERR_SUP, "Rectangular matrices are not supported");
1614: PetscCall(MatSetType(A, MATH2OPUS));
1615: PetscCall(MatBindToCPU(A, iscpu));
1616: PetscCall(MatH2OpusSetCoords_H2OPUS(A, spacedim, coords, cdist, kernel, kernelctx));
1618: h2opus = (Mat_H2OPUS *)A->data;
1619: if (eta > 0.) h2opus->eta = eta;
1620: if (leafsize > 0) h2opus->leafsize = leafsize;
1621: if (basisord > 0) h2opus->basisord = basisord;
1623: *nA = A;
1624: PetscFunctionReturn(PETSC_SUCCESS);
1625: }
1627: /*@
1628: MatCreateH2OpusFromMat - Creates a `MATH2OPUS` sampling from a user-supplied operator.
1630: Input Parameters:
1631: + B - the matrix to be sampled
1632: . spacedim - dimension of the space coordinates
1633: . coords - coordinates of the points
1634: . cdist - whether or not coordinates are distributed
1635: . eta - admissibility condition tolerance
1636: . leafsize - leaf size in cluster tree
1637: . maxrank - maximum rank allowed
1638: . bs - maximum number of samples to be taken concurrently
1639: - rtol - relative tolerance for construction
1641: Output Parameter:
1642: . nA - matrix
1644: Options Database Keys:
1645: + -mat_h2opus_leafsize <`PetscInt`> - Leaf size of cluster tree
1646: . -mat_h2opus_eta <`PetscReal`> - Admissibility condition tolerance
1647: . -mat_h2opus_maxrank <`PetscInt`> - Maximum rank when constructed from matvecs
1648: . -mat_h2opus_samples <`PetscInt`> - Maximum number of samples to be taken concurrently when constructing from matvecs
1649: . -mat_h2opus_rtol <`PetscReal`> - Relative tolerance for construction from sampling
1650: . -mat_h2opus_check <`PetscBool`> - Check error when constructing from sampling during MatAssemblyEnd()
1651: . -mat_h2opus_hara_verbose <`PetscBool`> - Verbose output from hara construction
1652: - -mat_h2opus_normsamples <`PetscInt`> - Maximum number of samples to be when estimating norms
1654: Level: intermediate
1656: Note:
1657: Not available in parallel
1659: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromKernel()`
1660: @*/
1661: PetscErrorCode MatCreateH2OpusFromMat(Mat B, PetscInt spacedim, const PetscReal coords[], PetscBool cdist, PetscReal eta, PetscInt leafsize, PetscInt maxrank, PetscInt bs, PetscReal rtol, Mat *nA)
1662: {
1663: Mat A;
1664: Mat_H2OPUS *h2opus;
1665: MPI_Comm comm;
1666: PetscBool boundtocpu = PETSC_TRUE;
1668: PetscFunctionBegin;
1677: PetscAssertPointer(nA, 10);
1678: PetscCall(PetscObjectGetComm((PetscObject)B, &comm));
1679: PetscCheck(B->rmap->n == B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Different row and column local sizes are not supported");
1680: PetscCheck(B->rmap->N == B->cmap->N, comm, PETSC_ERR_SUP, "Rectangular matrices are not supported");
1681: PetscCall(MatCreate(comm, &A));
1682: PetscCall(MatSetSizes(A, B->rmap->n, B->cmap->n, B->rmap->N, B->cmap->N));
1683: #if defined(PETSC_H2OPUS_USE_GPU)
1684: {
1685: VecType vtype;
1686: PetscBool isstd, iscuda, iskok;
1688: PetscCall(MatGetVecType(B, &vtype));
1689: PetscCall(PetscStrcmpAny(vtype, &isstd, VECSTANDARD, VECSEQ, VECMPI, ""));
1690: PetscCall(PetscStrcmpAny(vtype, &iscuda, VECCUDA, VECSEQCUDA, VECMPICUDA, ""));
1691: PetscCall(PetscStrcmpAny(vtype, &iskok, VECKOKKOS, VECSEQKOKKOS, VECMPIKOKKOS, ""));
1692: PetscCheck(isstd || iscuda || iskok, comm, PETSC_ERR_SUP, "Not for type %s", vtype);
1693: if (iscuda && !B->boundtocpu) boundtocpu = PETSC_FALSE;
1694: if (iskok && PetscDefined(HAVE_MACRO_KOKKOS_ENABLE_CUDA)) boundtocpu = PETSC_FALSE;
1695: }
1696: #endif
1697: PetscCall(MatSetType(A, MATH2OPUS));
1698: PetscCall(MatBindToCPU(A, boundtocpu));
1699: if (spacedim) PetscCall(MatH2OpusSetCoords_H2OPUS(A, spacedim, coords, cdist, NULL, NULL));
1700: PetscCall(MatPropagateSymmetryOptions(B, A));
1701: /* PetscCheck(A->symmetric,comm,PETSC_ERR_SUP,"Unsymmetric sampling does not work"); */
1703: h2opus = (Mat_H2OPUS *)A->data;
1704: h2opus->sampler = new PetscMatrixSampler(B);
1705: if (eta > 0.) h2opus->eta = eta;
1706: if (leafsize > 0) h2opus->leafsize = leafsize;
1707: if (maxrank > 0) h2opus->max_rank = maxrank;
1708: if (bs > 0) h2opus->bs = bs;
1709: if (rtol > 0.) h2opus->rtol = rtol;
1710: *nA = A;
1711: A->preallocated = PETSC_TRUE;
1712: PetscFunctionReturn(PETSC_SUCCESS);
1713: }
1715: /*@
1716: MatH2OpusGetIndexMap - Access reordering index set.
1718: Input Parameter:
1719: . A - the matrix
1721: Output Parameter:
1722: . indexmap - the index set for the reordering
1724: Level: intermediate
1726: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`, `MatCreateH2OpusFromKernel()`
1727: @*/
1728: PetscErrorCode MatH2OpusGetIndexMap(Mat A, IS *indexmap)
1729: {
1730: PetscBool ish2opus;
1731: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1733: PetscFunctionBegin;
1736: PetscAssertPointer(indexmap, 2);
1737: PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
1738: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
1739: PetscCheck(ish2opus, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)A)->type_name);
1740: *indexmap = a->h2opus_indexmap;
1741: PetscFunctionReturn(PETSC_SUCCESS);
1742: }
1744: /*@
1745: MatH2OpusMapVec - Maps a vector between PETSc and H2Opus ordering
1747: Input Parameters:
1748: + A - the matrix
1749: . nativetopetsc - if true, maps from H2Opus ordering to PETSc ordering. If false, applies the reverse map
1750: - in - the vector to be mapped
1752: Output Parameter:
1753: . out - the newly created mapped vector
1755: Level: intermediate
1757: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`, `MatCreateH2OpusFromKernel()`
1758: @*/
1759: PetscErrorCode MatH2OpusMapVec(Mat A, PetscBool nativetopetsc, Vec in, Vec *out)
1760: {
1761: PetscBool ish2opus;
1762: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1763: PetscScalar *xin, *xout;
1764: PetscBool nm;
1766: PetscFunctionBegin;
1771: PetscAssertPointer(out, 4);
1772: PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
1773: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &ish2opus));
1774: PetscCheck(ish2opus, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)A)->type_name);
1775: nm = a->nativemult;
1776: PetscCall(MatH2OpusSetNativeMult(A, (PetscBool)!nativetopetsc));
1777: PetscCall(MatCreateVecs(A, out, NULL));
1778: PetscCall(MatH2OpusSetNativeMult(A, nm));
1779: if (!a->sf) { /* same ordering */
1780: PetscCall(VecCopy(in, *out));
1781: PetscFunctionReturn(PETSC_SUCCESS);
1782: }
1783: PetscCall(VecGetArrayRead(in, (const PetscScalar **)&xin));
1784: PetscCall(VecGetArrayWrite(*out, &xout));
1785: if (nativetopetsc) {
1786: PetscCall(PetscSFReduceBegin(a->sf, MPIU_SCALAR, xin, xout, MPI_REPLACE));
1787: PetscCall(PetscSFReduceEnd(a->sf, MPIU_SCALAR, xin, xout, MPI_REPLACE));
1788: } else {
1789: PetscCall(PetscSFBcastBegin(a->sf, MPIU_SCALAR, xin, xout, MPI_REPLACE));
1790: PetscCall(PetscSFBcastEnd(a->sf, MPIU_SCALAR, xin, xout, MPI_REPLACE));
1791: }
1792: PetscCall(VecRestoreArrayRead(in, (const PetscScalar **)&xin));
1793: PetscCall(VecRestoreArrayWrite(*out, &xout));
1794: PetscFunctionReturn(PETSC_SUCCESS);
1795: }
1797: /*@
1798: MatH2OpusLowRankUpdate - Perform a low-rank update of the form $ A = A + s * U * V^T $
1800: Input Parameters:
1801: + A - the hierarchical `MATH2OPUS` matrix
1802: . s - the scaling factor
1803: . U - the dense low-rank update matrix
1804: - V - (optional) the dense low-rank update matrix (if `NULL`, then `V` = `U` is assumed)
1806: Note:
1807: The `U` and `V` matrices must be in `MATDENSE` dense format
1809: Level: intermediate
1811: .seealso: [](ch_matrices), `Mat`, `MatCreate()`, `MATH2OPUS`, `MatCreateH2OpusFromMat()`, `MatCreateH2OpusFromKernel()`, `MatH2OpusCompress()`, `MatH2OpusOrthogonalize()`, `MATDENSE`
1812: @*/
1813: PetscErrorCode MatH2OpusLowRankUpdate(Mat A, Mat U, Mat V, PetscScalar s)
1814: {
1815: PetscBool flg;
1817: PetscFunctionBegin;
1820: PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
1822: PetscCheckSameComm(A, 1, U, 2);
1823: if (V) {
1825: PetscCheckSameComm(A, 1, V, 3);
1826: }
1829: if (!V) V = U;
1830: PetscCheck(U->cmap->N == V->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "Non matching rank update %" PetscInt_FMT " != %" PetscInt_FMT, U->cmap->N, V->cmap->N);
1831: if (!U->cmap->N) PetscFunctionReturn(PETSC_SUCCESS);
1832: PetscCall(PetscLayoutCompare(U->rmap, A->rmap, &flg));
1833: PetscCheck(flg, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "A and U must have the same row layout");
1834: PetscCall(PetscLayoutCompare(V->rmap, A->cmap, &flg));
1835: PetscCheck(flg, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONGSTATE, "A column layout must match V row column layout");
1836: PetscCall(PetscObjectTypeCompare((PetscObject)A, MATH2OPUS, &flg));
1837: if (flg) {
1838: Mat_H2OPUS *a = (Mat_H2OPUS *)A->data;
1839: const PetscScalar *u, *v, *uu, *vv;
1840: PetscInt ldu, ldv;
1841: PetscMPIInt size;
1842: #if defined(H2OPUS_USE_MPI)
1843: h2opusHandle_t handle = a->handle->handle;
1844: #else
1845: h2opusHandle_t handle = a->handle;
1846: #endif
1847: PetscBool usesf = (PetscBool)(a->sf && !a->nativemult);
1848: PetscSF usf, vsf;
1850: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
1851: PetscCheck(size <= 1, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Not yet implemented in parallel");
1852: PetscCall(PetscLogEventBegin(MAT_H2Opus_LR, A, 0, 0, 0));
1853: PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)U, &flg, MATSEQDENSE, MATMPIDENSE, ""));
1854: PetscCheck(flg, PetscObjectComm((PetscObject)U), PETSC_ERR_SUP, "Not for U of type %s", ((PetscObject)U)->type_name);
1855: PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)V, &flg, MATSEQDENSE, MATMPIDENSE, ""));
1856: PetscCheck(flg, PetscObjectComm((PetscObject)V), PETSC_ERR_SUP, "Not for V of type %s", ((PetscObject)V)->type_name);
1857: PetscCall(MatDenseGetLDA(U, &ldu));
1858: PetscCall(MatDenseGetLDA(V, &ldv));
1859: PetscCall(MatBoundToCPU(A, &flg));
1860: if (usesf) {
1861: PetscInt n;
1863: PetscCall(MatDenseGetH2OpusStridedSF(U, a->sf, &usf));
1864: PetscCall(MatDenseGetH2OpusStridedSF(V, a->sf, &vsf));
1865: PetscCall(MatH2OpusResizeBuffers_Private(A, U->cmap->N, V->cmap->N));
1866: PetscCall(PetscSFGetGraph(a->sf, NULL, &n, NULL, NULL));
1867: ldu = n;
1868: ldv = n;
1869: }
1870: if (flg) {
1871: PetscCheck(a->hmatrix, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing CPU matrix");
1872: PetscCall(MatDenseGetArrayRead(U, &u));
1873: PetscCall(MatDenseGetArrayRead(V, &v));
1874: if (usesf) {
1875: vv = MatH2OpusGetThrustPointer(*a->yy);
1876: PetscCall(PetscSFBcastBegin(vsf, MPIU_SCALAR, v, (PetscScalar *)vv, MPI_REPLACE));
1877: PetscCall(PetscSFBcastEnd(vsf, MPIU_SCALAR, v, (PetscScalar *)vv, MPI_REPLACE));
1878: if (U != V) {
1879: uu = MatH2OpusGetThrustPointer(*a->xx);
1880: PetscCall(PetscSFBcastBegin(usf, MPIU_SCALAR, u, (PetscScalar *)uu, MPI_REPLACE));
1881: PetscCall(PetscSFBcastEnd(usf, MPIU_SCALAR, u, (PetscScalar *)uu, MPI_REPLACE));
1882: } else uu = vv;
1883: } else {
1884: uu = u;
1885: vv = v;
1886: }
1887: hlru_global(*a->hmatrix, uu, ldu, vv, ldv, U->cmap->N, s, handle);
1888: PetscCall(MatDenseRestoreArrayRead(U, &u));
1889: PetscCall(MatDenseRestoreArrayRead(V, &v));
1890: } else {
1891: #if defined(PETSC_H2OPUS_USE_GPU)
1892: PetscBool flgU, flgV;
1894: PetscCheck(a->hmatrix_gpu, PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "Missing GPU matrix");
1895: PetscCall(PetscObjectTypeCompareAny((PetscObject)U, &flgU, MATSEQDENSE, MATMPIDENSE, ""));
1896: if (flgU) PetscCall(MatConvert(U, MATDENSECUDA, MAT_INPLACE_MATRIX, &U));
1897: PetscCall(PetscObjectTypeCompareAny((PetscObject)V, &flgV, MATSEQDENSE, MATMPIDENSE, ""));
1898: if (flgV) PetscCall(MatConvert(V, MATDENSECUDA, MAT_INPLACE_MATRIX, &V));
1899: PetscCall(MatDenseCUDAGetArrayRead(U, &u));
1900: PetscCall(MatDenseCUDAGetArrayRead(V, &v));
1901: if (usesf) {
1902: vv = MatH2OpusGetThrustPointer(*a->yy_gpu);
1903: PetscCall(PetscSFBcastBegin(vsf, MPIU_SCALAR, v, (PetscScalar *)vv, MPI_REPLACE));
1904: PetscCall(PetscSFBcastEnd(vsf, MPIU_SCALAR, v, (PetscScalar *)vv, MPI_REPLACE));
1905: if (U != V) {
1906: uu = MatH2OpusGetThrustPointer(*a->xx_gpu);
1907: PetscCall(PetscSFBcastBegin(usf, MPIU_SCALAR, u, (PetscScalar *)uu, MPI_REPLACE));
1908: PetscCall(PetscSFBcastEnd(usf, MPIU_SCALAR, u, (PetscScalar *)uu, MPI_REPLACE));
1909: } else uu = vv;
1910: } else {
1911: uu = u;
1912: vv = v;
1913: }
1914: #else
1915: SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_PLIB, "This should not happen");
1916: #endif
1917: hlru_global(*a->hmatrix_gpu, uu, ldu, vv, ldv, U->cmap->N, s, handle);
1918: #if defined(PETSC_H2OPUS_USE_GPU)
1919: PetscCall(MatDenseCUDARestoreArrayRead(U, &u));
1920: PetscCall(MatDenseCUDARestoreArrayRead(V, &v));
1921: if (flgU) PetscCall(MatConvert(U, MATDENSE, MAT_INPLACE_MATRIX, &U));
1922: if (flgV) PetscCall(MatConvert(V, MATDENSE, MAT_INPLACE_MATRIX, &V));
1923: #endif
1924: }
1925: PetscCall(PetscLogEventEnd(MAT_H2Opus_LR, A, 0, 0, 0));
1926: a->orthogonal = PETSC_FALSE;
1927: }
1928: PetscFunctionReturn(PETSC_SUCCESS);
1929: }
1930: #endif