Actual source code: sveccuda.cu
slepc-3.21.1 2024-04-26
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain
6: This file is part of SLEPc.
7: SLEPc is distributed under a 2-clause BSD license (see LICENSE).
8: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
9: */
10: /*
11: BV implemented as a single Vec (CUDA version)
12: */
14: #include <slepc/private/bvimpl.h>
15: #include <slepccublas.h>
16: #include "../src/sys/classes/bv/impls/svec/svec.h"
18: PetscErrorCode BVMult_Svec_CUDA(BV Y,PetscScalar alpha,PetscScalar beta,BV X,Mat Q)
19: {
20: BV_SVEC *y = (BV_SVEC*)Y->data,*x = (BV_SVEC*)X->data;
21: const PetscScalar *d_px,*d_A,*d_B,*d_q;
22: PetscScalar *d_py,*d_C;
23: PetscInt ldq;
25: PetscFunctionBegin;
26: if (!Y->n) PetscFunctionReturn(PETSC_SUCCESS);
27: PetscCall(VecCUDAGetArrayRead(x->v,&d_px));
28: if (beta==(PetscScalar)0.0) PetscCall(VecCUDAGetArrayWrite(y->v,&d_py));
29: else PetscCall(VecCUDAGetArray(y->v,&d_py));
30: d_A = d_px+(X->nc+X->l)*X->ld;
31: d_C = d_py+(Y->nc+Y->l)*Y->ld;
32: if (Q) {
33: PetscCall(MatDenseGetLDA(Q,&ldq));
34: PetscCall(BV_MatDenseCUDAGetArrayRead(Y,Q,&d_q));
35: d_B = d_q+Y->l*ldq+X->l;
36: PetscCall(BVMult_BLAS_CUDA(Y,Y->n,Y->k-Y->l,X->k-X->l,alpha,d_A,X->ld,d_B,ldq,beta,d_C,Y->ld));
37: PetscCall(BV_MatDenseCUDARestoreArrayRead(Y,Q,&d_q));
38: } else PetscCall(BVAXPY_BLAS_CUDA(Y,Y->n,Y->k-Y->l,alpha,d_A,X->ld,beta,d_C,Y->ld));
39: PetscCall(VecCUDARestoreArrayRead(x->v,&d_px));
40: if (beta==(PetscScalar)0.0) PetscCall(VecCUDARestoreArrayWrite(y->v,&d_py));
41: else PetscCall(VecCUDARestoreArray(y->v,&d_py));
42: PetscFunctionReturn(PETSC_SUCCESS);
43: }
45: PetscErrorCode BVMultVec_Svec_CUDA(BV X,PetscScalar alpha,PetscScalar beta,Vec y,PetscScalar *q)
46: {
47: BV_SVEC *x = (BV_SVEC*)X->data;
48: PetscScalar *d_py,*d_q;
49: const PetscScalar *d_px;
51: PetscFunctionBegin;
52: PetscCall(VecCUDAGetArrayRead(x->v,&d_px));
53: if (beta==(PetscScalar)0.0) PetscCall(VecCUDAGetArrayWrite(y,&d_py));
54: else PetscCall(VecCUDAGetArray(y,&d_py));
55: if (!q) PetscCall(VecCUDAGetArray(X->buffer,&d_q));
56: else {
57: PetscInt k=X->k-X->l;
58: PetscCallCUDA(cudaMalloc((void**)&d_q,k*sizeof(PetscScalar)));
59: PetscCallCUDA(cudaMemcpy(d_q,q,k*sizeof(PetscScalar),cudaMemcpyHostToDevice));
60: PetscCall(PetscLogCpuToGpu(k*sizeof(PetscScalar)));
61: }
62: PetscCall(BVMultVec_BLAS_CUDA(X,X->n,X->k-X->l,alpha,d_px+(X->nc+X->l)*X->ld,X->ld,d_q,beta,d_py));
63: PetscCall(VecCUDARestoreArrayRead(x->v,&d_px));
64: if (beta==(PetscScalar)0.0) PetscCall(VecCUDARestoreArrayWrite(y,&d_py));
65: else PetscCall(VecCUDARestoreArray(y,&d_py));
66: if (!q) PetscCall(VecCUDARestoreArray(X->buffer,&d_q));
67: else PetscCallCUDA(cudaFree(d_q));
68: PetscFunctionReturn(PETSC_SUCCESS);
69: }
71: PetscErrorCode BVMultInPlace_Svec_CUDA(BV V,Mat Q,PetscInt s,PetscInt e)
72: {
73: BV_SVEC *ctx = (BV_SVEC*)V->data;
74: PetscScalar *d_pv;
75: const PetscScalar *d_q;
76: PetscInt ldq;
78: PetscFunctionBegin;
79: if (s>=e || !V->n) PetscFunctionReturn(PETSC_SUCCESS);
80: PetscCall(MatDenseGetLDA(Q,&ldq));
81: PetscCall(VecCUDAGetArray(ctx->v,&d_pv));
82: PetscCall(BV_MatDenseCUDAGetArrayRead(V,Q,&d_q));
83: PetscCall(BVMultInPlace_BLAS_CUDA(V,V->n,V->k-V->l,s-V->l,e-V->l,d_pv+(V->nc+V->l)*V->ld,V->ld,d_q+V->l*ldq+V->l,ldq,PETSC_FALSE));
84: PetscCall(BV_MatDenseCUDARestoreArrayRead(V,Q,&d_q));
85: PetscCall(VecCUDARestoreArray(ctx->v,&d_pv));
86: PetscFunctionReturn(PETSC_SUCCESS);
87: }
89: PetscErrorCode BVMultInPlaceHermitianTranspose_Svec_CUDA(BV V,Mat Q,PetscInt s,PetscInt e)
90: {
91: BV_SVEC *ctx = (BV_SVEC*)V->data;
92: PetscScalar *d_pv;
93: const PetscScalar *d_q;
94: PetscInt ldq;
96: PetscFunctionBegin;
97: if (s>=e || !V->n) PetscFunctionReturn(PETSC_SUCCESS);
98: PetscCall(MatDenseGetLDA(Q,&ldq));
99: PetscCall(VecCUDAGetArray(ctx->v,&d_pv));
100: PetscCall(BV_MatDenseCUDAGetArrayRead(V,Q,&d_q));
101: PetscCall(BVMultInPlace_BLAS_CUDA(V,V->n,V->k-V->l,s-V->l,e-V->l,d_pv+(V->nc+V->l)*V->ld,V->ld,d_q+V->l*ldq+V->l,ldq,PETSC_TRUE));
102: PetscCall(BV_MatDenseCUDARestoreArrayRead(V,Q,&d_q));
103: PetscCall(VecCUDARestoreArray(ctx->v,&d_pv));
104: PetscFunctionReturn(PETSC_SUCCESS);
105: }
107: PetscErrorCode BVDot_Svec_CUDA(BV X,BV Y,Mat M)
108: {
109: BV_SVEC *x = (BV_SVEC*)X->data,*y = (BV_SVEC*)Y->data;
110: const PetscScalar *d_px,*d_py;
111: PetscScalar *pm;
112: PetscInt ldm;
114: PetscFunctionBegin;
115: PetscCall(MatDenseGetLDA(M,&ldm));
116: PetscCall(VecCUDAGetArrayRead(x->v,&d_px));
117: PetscCall(VecCUDAGetArrayRead(y->v,&d_py));
118: PetscCall(MatDenseGetArrayWrite(M,&pm));
119: PetscCall(BVDot_BLAS_CUDA(X,Y->k-Y->l,X->k-X->l,X->n,d_py+(Y->nc+Y->l)*Y->ld,Y->ld,d_px+(X->nc+X->l)*X->ld,X->ld,pm+X->l*ldm+Y->l,ldm,x->mpi));
120: PetscCall(MatDenseRestoreArrayWrite(M,&pm));
121: PetscCall(VecCUDARestoreArrayRead(x->v,&d_px));
122: PetscCall(VecCUDARestoreArrayRead(y->v,&d_py));
123: PetscFunctionReturn(PETSC_SUCCESS);
124: }
126: PetscErrorCode BVDotVec_Svec_CUDA(BV X,Vec y,PetscScalar *q)
127: {
128: BV_SVEC *x = (BV_SVEC*)X->data;
129: const PetscScalar *d_px,*d_py;
130: Vec z = y;
132: PetscFunctionBegin;
133: if (PetscUnlikely(X->matrix)) {
134: PetscCall(BV_IPMatMult(X,y));
135: z = X->Bx;
136: }
137: PetscCall(VecCUDAGetArrayRead(x->v,&d_px));
138: PetscCall(VecCUDAGetArrayRead(z,&d_py));
139: PetscCall(BVDotVec_BLAS_CUDA(X,X->n,X->k-X->l,d_px+(X->nc+X->l)*X->ld,X->ld,d_py,q,x->mpi));
140: PetscCall(VecCUDARestoreArrayRead(z,&d_py));
141: PetscCall(VecCUDARestoreArrayRead(x->v,&d_px));
142: PetscFunctionReturn(PETSC_SUCCESS);
143: }
145: PetscErrorCode BVDotVec_Local_Svec_CUDA(BV X,Vec y,PetscScalar *m)
146: {
147: BV_SVEC *x = (BV_SVEC*)X->data;
148: const PetscScalar *d_px,*d_py;
149: Vec z = y;
151: PetscFunctionBegin;
152: if (PetscUnlikely(X->matrix)) {
153: PetscCall(BV_IPMatMult(X,y));
154: z = X->Bx;
155: }
156: PetscCall(VecCUDAGetArrayRead(x->v,&d_px));
157: PetscCall(VecCUDAGetArrayRead(z,&d_py));
158: PetscCall(BVDotVec_BLAS_CUDA(X,X->n,X->k-X->l,d_px+(X->nc+X->l)*X->ld,X->ld,d_py,m,PETSC_FALSE));
159: PetscCall(VecCUDARestoreArrayRead(z,&d_py));
160: PetscCall(VecCUDARestoreArrayRead(x->v,&d_px));
161: PetscFunctionReturn(PETSC_SUCCESS);
162: }
164: PetscErrorCode BVScale_Svec_CUDA(BV bv,PetscInt j,PetscScalar alpha)
165: {
166: BV_SVEC *ctx = (BV_SVEC*)bv->data;
167: PetscScalar *d_array,*d_A;
168: PetscInt n=0;
170: PetscFunctionBegin;
171: if (!bv->n) PetscFunctionReturn(PETSC_SUCCESS);
172: PetscCall(VecCUDAGetArray(ctx->v,&d_array));
173: if (PetscUnlikely(j<0)) {
174: d_A = d_array+(bv->nc+bv->l)*bv->ld;
175: n = (bv->k-bv->l)*bv->ld;
176: } else {
177: d_A = d_array+(bv->nc+j)*bv->ld;
178: n = bv->n;
179: }
180: PetscCall(BVScale_BLAS_CUDA(bv,n,d_A,alpha));
181: PetscCall(VecCUDARestoreArray(ctx->v,&d_array));
182: PetscFunctionReturn(PETSC_SUCCESS);
183: }
185: PetscErrorCode BVNorm_Svec_CUDA(BV bv,PetscInt j,NormType type,PetscReal *val)
186: {
187: BV_SVEC *ctx = (BV_SVEC*)bv->data;
188: const PetscScalar *array,*d_array,*d_A;
189: PetscInt n=0;
191: PetscFunctionBegin;
192: if (!ctx->mpi && ((j<0 && type==NORM_FROBENIUS && bv->ld==bv->n) || (j>=0 && type==NORM_2))) {
193: /* compute on GPU with cuBLAS - TODO: include the MPI case here */
194: *val = 0.0;
195: if (!bv->n) PetscFunctionReturn(PETSC_SUCCESS);
196: PetscCall(VecCUDAGetArrayRead(ctx->v,&d_array));
197: if (PetscUnlikely(j<0)) {
198: d_A = d_array+(bv->nc+bv->l)*bv->ld;
199: n = (bv->k-bv->l)*bv->ld;
200: } else {
201: d_A = d_array+(bv->nc+j)*bv->ld;
202: n = bv->n;
203: }
204: PetscCall(BVNorm_BLAS_CUDA(bv,n,d_A,val));
205: PetscCall(VecCUDARestoreArrayRead(ctx->v,&d_array));
206: } else {
207: /* compute on CPU */
208: PetscCall(VecGetArrayRead(ctx->v,&array));
209: if (PetscUnlikely(j<0)) PetscCall(BVNorm_LAPACK_Private(bv,bv->n,bv->k-bv->l,array+(bv->nc+bv->l)*bv->ld,bv->ld,type,val,ctx->mpi));
210: else PetscCall(BVNorm_LAPACK_Private(bv,bv->n,1,array+(bv->nc+j)*bv->ld,bv->ld,type,val,ctx->mpi));
211: PetscCall(VecRestoreArrayRead(ctx->v,&array));
212: }
213: PetscFunctionReturn(PETSC_SUCCESS);
214: }
216: PetscErrorCode BVNorm_Local_Svec_CUDA(BV bv,PetscInt j,NormType type,PetscReal *val)
217: {
218: BV_SVEC *ctx = (BV_SVEC*)bv->data;
219: const PetscScalar *array,*d_array,*d_A;
220: PetscInt n=0;
222: PetscFunctionBegin;
223: if ((j<0 && type==NORM_FROBENIUS && bv->ld==bv->n) || (j>=0 && type==NORM_2)) {
224: /* compute on GPU with cuBLAS */
225: *val = 0.0;
226: if (!bv->n) PetscFunctionReturn(PETSC_SUCCESS);
227: PetscCall(VecCUDAGetArrayRead(ctx->v,&d_array));
228: if (PetscUnlikely(j<0)) {
229: d_A = d_array+(bv->nc+bv->l)*bv->ld;
230: n = (bv->k-bv->l)*bv->ld;
231: } else {
232: d_A = d_array+(bv->nc+j)*bv->ld;
233: n = bv->n;
234: }
235: PetscCall(BVNorm_BLAS_CUDA(bv,n,d_A,val));
236: PetscCall(VecCUDARestoreArrayRead(ctx->v,&d_array));
237: } else {
238: /* compute on CPU */
239: PetscCall(VecGetArrayRead(ctx->v,&array));
240: if (PetscUnlikely(j<0)) PetscCall(BVNorm_LAPACK_Private(bv,bv->n,bv->k-bv->l,array+(bv->nc+bv->l)*bv->ld,bv->ld,type,val,PETSC_FALSE));
241: else PetscCall(BVNorm_LAPACK_Private(bv,bv->n,1,array+(bv->nc+j)*bv->ld,bv->ld,type,val,PETSC_FALSE));
242: PetscCall(VecRestoreArrayRead(ctx->v,&array));
243: }
244: PetscFunctionReturn(PETSC_SUCCESS);
245: }
247: PetscErrorCode BVNormalize_Svec_CUDA(BV bv,PetscScalar *eigi)
248: {
249: BV_SVEC *ctx = (BV_SVEC*)bv->data;
250: PetscScalar *array,*d_array,*wi=NULL;
252: PetscFunctionBegin;
253: if (eigi) wi = eigi+bv->l;
254: if (!ctx->mpi) {
255: /* compute on GPU with cuBLAS - TODO: include the MPI case here */
256: if (!bv->n) PetscFunctionReturn(PETSC_SUCCESS);
257: PetscCall(VecCUDAGetArray(ctx->v,&d_array));
258: PetscCall(BVNormalize_BLAS_CUDA(bv,bv->n,bv->k-bv->l,d_array+(bv->nc+bv->l)*bv->ld,bv->ld,wi));
259: PetscCall(VecCUDARestoreArray(ctx->v,&d_array));
260: } else {
261: /* compute on CPU */
262: PetscCall(VecGetArray(ctx->v,&array));
263: PetscCall(BVNormalize_LAPACK_Private(bv,bv->n,bv->k-bv->l,array+(bv->nc+bv->l)*bv->ld,bv->ld,wi,ctx->mpi));
264: PetscCall(VecRestoreArray(ctx->v,&array));
265: }
266: PetscFunctionReturn(PETSC_SUCCESS);
267: }
269: PetscErrorCode BVMatMult_Svec_CUDA(BV V,Mat A,BV W)
270: {
271: BV_SVEC *v = (BV_SVEC*)V->data,*w = (BV_SVEC*)W->data;
272: Mat Vmat,Wmat;
273: const PetscScalar *d_pv;
274: PetscScalar *d_pw;
275: PetscInt j;
277: PetscFunctionBegin;
278: if (V->vmm) {
279: PetscCall(BVGetMat(V,&Vmat));
280: PetscCall(BVGetMat(W,&Wmat));
281: PetscCall(MatProductCreateWithMat(A,Vmat,NULL,Wmat));
282: PetscCall(MatProductSetType(Wmat,MATPRODUCT_AB));
283: PetscCall(MatProductSetFromOptions(Wmat));
284: PetscCall(MatProductSymbolic(Wmat));
285: PetscCall(MatProductNumeric(Wmat));
286: PetscCall(MatProductClear(Wmat));
287: PetscCall(BVRestoreMat(V,&Vmat));
288: PetscCall(BVRestoreMat(W,&Wmat));
289: } else {
290: PetscCall(VecCUDAGetArrayRead(v->v,&d_pv));
291: PetscCall(VecCUDAGetArrayWrite(w->v,&d_pw));
292: for (j=0;j<V->k-V->l;j++) {
293: PetscCall(VecCUDAPlaceArray(V->cv[1],(PetscScalar *)d_pv+(V->nc+V->l+j)*V->ld));
294: PetscCall(VecCUDAPlaceArray(W->cv[1],d_pw+(W->nc+W->l+j)*W->ld));
295: PetscCall(MatMult(A,V->cv[1],W->cv[1]));
296: PetscCall(VecCUDAResetArray(V->cv[1]));
297: PetscCall(VecCUDAResetArray(W->cv[1]));
298: }
299: PetscCall(VecCUDARestoreArrayRead(v->v,&d_pv));
300: PetscCall(VecCUDARestoreArrayWrite(w->v,&d_pw));
301: }
302: PetscFunctionReturn(PETSC_SUCCESS);
303: }
305: PetscErrorCode BVCopy_Svec_CUDA(BV V,BV W)
306: {
307: BV_SVEC *v = (BV_SVEC*)V->data,*w = (BV_SVEC*)W->data;
308: const PetscScalar *d_pv;
309: PetscScalar *d_pw;
311: PetscFunctionBegin;
312: PetscCall(VecCUDAGetArrayRead(v->v,&d_pv));
313: PetscCall(VecCUDAGetArray(w->v,&d_pw));
314: PetscCallCUDA(cudaMemcpy2D(d_pw+(W->nc+W->l)*W->ld,W->ld*sizeof(PetscScalar),d_pv+(V->nc+V->l)*V->ld,V->ld*sizeof(PetscScalar),V->n*sizeof(PetscScalar),V->k-V->l,cudaMemcpyDeviceToDevice));
315: PetscCall(VecCUDARestoreArrayRead(v->v,&d_pv));
316: PetscCall(VecCUDARestoreArray(w->v,&d_pw));
317: PetscFunctionReturn(PETSC_SUCCESS);
318: }
320: PetscErrorCode BVCopyColumn_Svec_CUDA(BV V,PetscInt j,PetscInt i)
321: {
322: BV_SVEC *v = (BV_SVEC*)V->data;
323: PetscScalar *d_pv;
325: PetscFunctionBegin;
326: PetscCall(VecCUDAGetArray(v->v,&d_pv));
327: PetscCallCUDA(cudaMemcpy(d_pv+(V->nc+i)*V->ld,d_pv+(V->nc+j)*V->ld,V->n*sizeof(PetscScalar),cudaMemcpyDeviceToDevice));
328: PetscCall(VecCUDARestoreArray(v->v,&d_pv));
329: PetscFunctionReturn(PETSC_SUCCESS);
330: }
332: PetscErrorCode BVResize_Svec_CUDA(BV bv,PetscInt m,PetscBool copy)
333: {
334: BV_SVEC *ctx = (BV_SVEC*)bv->data;
335: const PetscScalar *d_pv;
336: PetscScalar *d_pnew;
337: PetscInt bs;
338: Vec vnew;
339: char str[50];
341: PetscFunctionBegin;
342: PetscCall(PetscLayoutGetBlockSize(bv->map,&bs));
343: PetscCall(VecCreate(PetscObjectComm((PetscObject)bv),&vnew));
344: PetscCall(VecSetType(vnew,bv->vtype));
345: PetscCall(VecSetSizes(vnew,m*bv->ld,PETSC_DECIDE));
346: PetscCall(VecSetBlockSize(vnew,bs));
347: if (((PetscObject)bv)->name) {
348: PetscCall(PetscSNPrintf(str,sizeof(str),"%s_0",((PetscObject)bv)->name));
349: PetscCall(PetscObjectSetName((PetscObject)vnew,str));
350: }
351: if (copy) {
352: PetscCall(VecCUDAGetArrayRead(ctx->v,&d_pv));
353: PetscCall(VecCUDAGetArrayWrite(vnew,&d_pnew));
354: PetscCallCUDA(cudaMemcpy(d_pnew,d_pv,PetscMin(m,bv->m)*bv->ld*sizeof(PetscScalar),cudaMemcpyDeviceToDevice));
355: PetscCall(VecCUDARestoreArrayRead(ctx->v,&d_pv));
356: PetscCall(VecCUDARestoreArrayWrite(vnew,&d_pnew));
357: }
358: PetscCall(VecDestroy(&ctx->v));
359: ctx->v = vnew;
360: PetscFunctionReturn(PETSC_SUCCESS);
361: }
363: PetscErrorCode BVGetColumn_Svec_CUDA(BV bv,PetscInt j,Vec*)
364: {
365: BV_SVEC *ctx = (BV_SVEC*)bv->data;
366: PetscScalar *d_pv;
367: PetscInt l;
369: PetscFunctionBegin;
370: l = BVAvailableVec;
371: PetscCall(VecCUDAGetArray(ctx->v,&d_pv));
372: PetscCall(VecCUDAPlaceArray(bv->cv[l],d_pv+(bv->nc+j)*bv->ld));
373: PetscFunctionReturn(PETSC_SUCCESS);
374: }
376: PetscErrorCode BVRestoreColumn_Svec_CUDA(BV bv,PetscInt j,Vec*)
377: {
378: BV_SVEC *ctx = (BV_SVEC*)bv->data;
379: PetscInt l;
381: PetscFunctionBegin;
382: l = (j==bv->ci[0])? 0: 1;
383: PetscCall(VecCUDAResetArray(bv->cv[l]));
384: PetscCall(VecCUDARestoreArray(ctx->v,NULL));
385: PetscFunctionReturn(PETSC_SUCCESS);
386: }
388: PetscErrorCode BVRestoreSplit_Svec_CUDA(BV bv,BV *L,BV *R)
389: {
390: Vec v;
391: const PetscScalar *d_pv;
392: PetscObjectState lstate,rstate;
393: PetscBool change=PETSC_FALSE;
395: PetscFunctionBegin;
396: /* force sync flag to PETSC_CUDA_BOTH */
397: if (L) {
398: PetscCall(PetscObjectStateGet((PetscObject)*L,&lstate));
399: if (lstate != bv->lstate) {
400: v = ((BV_SVEC*)bv->L->data)->v;
401: PetscCall(VecCUDAGetArrayRead(v,&d_pv));
402: PetscCall(VecCUDARestoreArrayRead(v,&d_pv));
403: change = PETSC_TRUE;
404: }
405: }
406: if (R) {
407: PetscCall(PetscObjectStateGet((PetscObject)*R,&rstate));
408: if (rstate != bv->rstate) {
409: v = ((BV_SVEC*)bv->R->data)->v;
410: PetscCall(VecCUDAGetArrayRead(v,&d_pv));
411: PetscCall(VecCUDARestoreArrayRead(v,&d_pv));
412: change = PETSC_TRUE;
413: }
414: }
415: if (change) {
416: v = ((BV_SVEC*)bv->data)->v;
417: PetscCall(VecCUDAGetArray(v,(PetscScalar **)&d_pv));
418: PetscCall(VecCUDARestoreArray(v,(PetscScalar **)&d_pv));
419: }
420: PetscFunctionReturn(PETSC_SUCCESS);
421: }
423: PetscErrorCode BVGetMat_Svec_CUDA(BV bv,Mat *A)
424: {
425: BV_SVEC *ctx = (BV_SVEC*)bv->data;
426: PetscScalar *vv,*aa;
427: PetscBool create=PETSC_FALSE;
428: PetscInt m,cols;
430: PetscFunctionBegin;
431: m = bv->k-bv->l;
432: if (!bv->Aget) create=PETSC_TRUE;
433: else {
434: PetscCall(MatDenseCUDAGetArray(bv->Aget,&aa));
435: PetscCheck(!aa,PetscObjectComm((PetscObject)bv),PETSC_ERR_ARG_WRONGSTATE,"BVGetMat already called on this BV");
436: PetscCall(MatGetSize(bv->Aget,NULL,&cols));
437: if (cols!=m) {
438: PetscCall(MatDestroy(&bv->Aget));
439: create=PETSC_TRUE;
440: }
441: }
442: PetscCall(VecCUDAGetArray(ctx->v,&vv));
443: if (create) {
444: PetscCall(MatCreateDenseFromVecType(PetscObjectComm((PetscObject)bv),bv->vtype,bv->n,PETSC_DECIDE,bv->N,m,bv->ld,vv,&bv->Aget)); /* pass a pointer to avoid allocation of storage */
445: PetscCall(MatDenseCUDAReplaceArray(bv->Aget,NULL)); /* replace with a null pointer, the value after BVRestoreMat */
446: }
447: PetscCall(MatDenseCUDAPlaceArray(bv->Aget,vv+(bv->nc+bv->l)*bv->ld)); /* set the actual pointer */
448: *A = bv->Aget;
449: PetscFunctionReturn(PETSC_SUCCESS);
450: }
452: PetscErrorCode BVRestoreMat_Svec_CUDA(BV bv,Mat *A)
453: {
454: BV_SVEC *ctx = (BV_SVEC*)bv->data;
455: PetscScalar *vv,*aa;
457: PetscFunctionBegin;
458: PetscCall(MatDenseCUDAGetArray(bv->Aget,&aa));
459: vv = aa-(bv->nc+bv->l)*bv->ld;
460: PetscCall(MatDenseCUDAResetArray(bv->Aget));
461: PetscCall(VecCUDARestoreArray(ctx->v,&vv));
462: *A = NULL;
463: PetscFunctionReturn(PETSC_SUCCESS);
464: }