Date: 2024-10-28T09:14:23+00:00

Actual source code: bvcuda.cu
slepc-3.22.1 2024-10-28
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      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:    CUDA-related code common to several BV impls
     12: */

     14: #include <slepc/private/bvimpl.h>
     15: #include <slepccupmblas.h>

     17: #define BLOCKSIZE 64

     19: /*
     20:     C := alpha*A*B + beta*C
     21: */
     22: PetscErrorCode BVMult_BLAS_CUDA(BV,PetscInt m_,PetscInt n_,PetscInt k_,PetscScalar alpha,const PetscScalar *d_A,PetscInt lda_,const PetscScalar *d_B,PetscInt ldb_,PetscScalar beta,PetscScalar *d_C,PetscInt ldc_)
     23: {
     24:   PetscCuBLASInt    m=0,n=0,k=0,lda=0,ldb=0,ldc=0;
     25:   cublasHandle_t    cublasv2handle;

     27:   PetscFunctionBegin;
     28:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
     29:   PetscCall(PetscCuBLASIntCast(m_,&m));
     30:   PetscCall(PetscCuBLASIntCast(n_,&n));
     31:   PetscCall(PetscCuBLASIntCast(k_,&k));
     32:   PetscCall(PetscCuBLASIntCast(lda_,&lda));
     33:   PetscCall(PetscCuBLASIntCast(ldb_,&ldb));
     34:   PetscCall(PetscCuBLASIntCast(ldc_,&ldc));
     35:   PetscCall(PetscLogGpuTimeBegin());
     36:   PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_N,CUBLAS_OP_N,m,n,k,&alpha,d_A,lda,d_B,ldb,&beta,d_C,ldc));
     37:   PetscCall(PetscLogGpuTimeEnd());
     38:   PetscCall(PetscLogGpuFlops(2.0*m*n*k));
     39:   PetscFunctionReturn(PETSC_SUCCESS);
     40: }

     42: /*
     43:     y := alpha*A*x + beta*y
     44: */
     45: PetscErrorCode BVMultVec_BLAS_CUDA(BV,PetscInt n_,PetscInt k_,PetscScalar alpha,const PetscScalar *d_A,PetscInt lda_,const PetscScalar *d_x,PetscScalar beta,PetscScalar *d_y)
     46: {
     47:   PetscCuBLASInt    n=0,k=0,lda=0,one=1;
     48:   cublasHandle_t    cublasv2handle;

     50:   PetscFunctionBegin;
     51:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
     52:   PetscCall(PetscCuBLASIntCast(n_,&n));
     53:   PetscCall(PetscCuBLASIntCast(k_,&k));
     54:   PetscCall(PetscCuBLASIntCast(lda_,&lda));
     55:   PetscCall(PetscLogGpuTimeBegin());
     56:   PetscCallCUBLAS(cublasXgemv(cublasv2handle,CUBLAS_OP_N,n,k,&alpha,d_A,lda,d_x,one,&beta,d_y,one));
     57:   PetscCall(PetscLogGpuTimeEnd());
     58:   PetscCall(PetscLogGpuFlops(2.0*n*k));
     59:   PetscFunctionReturn(PETSC_SUCCESS);
     60: }

     62: /*
     63:     A(:,s:e-1) := A*B(:,s:e-1)
     64: */
     65: PetscErrorCode BVMultInPlace_BLAS_CUDA(BV,PetscInt m_,PetscInt k_,PetscInt s,PetscInt e,PetscScalar *d_A,PetscInt lda_,const PetscScalar *d_B,PetscInt ldb_,PetscBool btrans)
     66: {
     67:   const PetscScalar *d_B1;
     68:   PetscScalar       *d_work,sone=1.0,szero=0.0;
     69:   PetscCuBLASInt    m=0,n=0,k=0,l=0,lda=0,ldb=0,bs=BLOCKSIZE;
     70:   size_t            freemem,totmem;
     71:   cublasHandle_t    cublasv2handle;
     72:   cublasOperation_t bt;

     74:   PetscFunctionBegin;
     75:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
     76:   PetscCall(PetscCuBLASIntCast(m_,&m));
     77:   PetscCall(PetscCuBLASIntCast(e-s,&n));
     78:   PetscCall(PetscCuBLASIntCast(k_,&k));
     79:   PetscCall(PetscCuBLASIntCast(lda_,&lda));
     80:   PetscCall(PetscCuBLASIntCast(ldb_,&ldb));
     81:   PetscCall(PetscLogGpuTimeBegin());
     82:   if (PetscUnlikely(btrans)) {
     83:     d_B1 = d_B+s;
     84:     bt   = CUBLAS_OP_C;
     85:   } else {
     86:     d_B1 = d_B+s*ldb;
     87:     bt   = CUBLAS_OP_N;
     88:   }
     89:   /* try to allocate the whole matrix */
     90:   PetscCallCUDA(cudaMemGetInfo(&freemem,&totmem));
     91:   if (freemem>=lda*n*sizeof(PetscScalar)) {
     92:     PetscCallCUDA(cudaMalloc((void**)&d_work,lda*n*sizeof(PetscScalar)));
     93:     PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_N,bt,m,n,k,&sone,d_A,lda,d_B1,ldb,&szero,d_work,lda));
     94:     PetscCallCUDA(cudaMemcpy2D(d_A+s*lda,lda*sizeof(PetscScalar),d_work,lda*sizeof(PetscScalar),m*sizeof(PetscScalar),n,cudaMemcpyDeviceToDevice));
     95:   } else {
     96:     PetscCall(PetscCuBLASIntCast(freemem/(m*sizeof(PetscScalar)),&bs));
     97:     PetscCallCUDA(cudaMalloc((void**)&d_work,bs*n*sizeof(PetscScalar)));
     98:     PetscCall(PetscCuBLASIntCast(m % bs,&l));
     99:     if (l) {
    100:       PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_N,bt,l,n,k,&sone,d_A,lda,d_B1,ldb,&szero,d_work,l));
    101:       PetscCallCUDA(cudaMemcpy2D(d_A+s*lda,lda*sizeof(PetscScalar),d_work,l*sizeof(PetscScalar),l*sizeof(PetscScalar),n,cudaMemcpyDeviceToDevice));
    102:     }
    103:     for (;l<m;l+=bs) {
    104:       PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_N,bt,bs,n,k,&sone,d_A+l,lda,d_B1,ldb,&szero,d_work,bs));
    105:       PetscCallCUDA(cudaMemcpy2D(d_A+l+s*lda,lda*sizeof(PetscScalar),d_work,bs*sizeof(PetscScalar),bs*sizeof(PetscScalar),n,cudaMemcpyDeviceToDevice));
    106:     }
    107:   }
    108:   PetscCall(PetscLogGpuTimeEnd());
    109:   PetscCallCUDA(cudaFree(d_work));
    110:   PetscCall(PetscLogGpuFlops(2.0*m*n*k));
    111:   PetscFunctionReturn(PETSC_SUCCESS);
    112: }

    114: /*
    115:     B := alpha*A + beta*B
    116: */
    117: PetscErrorCode BVAXPY_BLAS_CUDA(BV,PetscInt n_,PetscInt k_,PetscScalar alpha,const PetscScalar *d_A,PetscInt lda_,PetscScalar beta,PetscScalar *d_B,PetscInt ldb_)
    118: {
    119:   PetscCuBLASInt n=0,k=0,lda=0,ldb=0;
    120:   cublasHandle_t cublasv2handle;

    122:   PetscFunctionBegin;
    123:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    124:   PetscCall(PetscCuBLASIntCast(n_,&n));
    125:   PetscCall(PetscCuBLASIntCast(k_,&k));
    126:   PetscCall(PetscCuBLASIntCast(lda_,&lda));
    127:   PetscCall(PetscCuBLASIntCast(ldb_,&ldb));
    128:   PetscCall(PetscLogGpuTimeBegin());
    129:   PetscCallCUBLAS(cublasXgeam(cublasv2handle,CUBLAS_OP_N,CUBLAS_OP_N,n,k,&alpha,d_A,lda,&beta,d_B,ldb,d_B,ldb));
    130:   PetscCall(PetscLogGpuTimeEnd());
    131:   PetscCall(PetscLogGpuFlops((beta==(PetscScalar)1.0)?2.0*n*k:3.0*n*k));
    132:   PetscFunctionReturn(PETSC_SUCCESS);
    133: }

    135: /*
    136:     C := A'*B

    138:     C is a CPU array
    139: */
    140: PetscErrorCode BVDot_BLAS_CUDA(BV bv,PetscInt m_,PetscInt n_,PetscInt k_,const PetscScalar *d_A,PetscInt lda_,const PetscScalar *d_B,PetscInt ldb_,PetscScalar *C,PetscInt ldc_,PetscBool mpi)
    141: {
    142:   PetscScalar       *d_work,sone=1.0,szero=0.0,*CC;
    143:   PetscInt          j;
    144:   PetscCuBLASInt    m=0,n=0,k=0,lda=0,ldb=0,ldc=0;
    145:   PetscMPIInt       len;
    146:   cublasHandle_t    cublasv2handle;

    148:   PetscFunctionBegin;
    149:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    150:   PetscCall(PetscCuBLASIntCast(m_,&m));
    151:   PetscCall(PetscCuBLASIntCast(n_,&n));
    152:   PetscCall(PetscCuBLASIntCast(k_,&k));
    153:   PetscCall(PetscCuBLASIntCast(lda_,&lda));
    154:   PetscCall(PetscCuBLASIntCast(ldb_,&ldb));
    155:   PetscCall(PetscCuBLASIntCast(ldc_,&ldc));
    156:   PetscCallCUDA(cudaMalloc((void**)&d_work,m*n*sizeof(PetscScalar)));
    157:   if (mpi) {
    158:     if (ldc==m) {
    159:       PetscCall(BVAllocateWork_Private(bv,m*n));
    160:       if (k) {
    161:         PetscCall(PetscLogGpuTimeBegin());
    162:         PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_C,CUBLAS_OP_N,m,n,k,&sone,d_A,lda,d_B,ldb,&szero,d_work,ldc));
    163:         PetscCall(PetscLogGpuTimeEnd());
    164:         PetscCallCUDA(cudaMemcpy(bv->work,d_work,m*n*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    165:         PetscCall(PetscLogGpuToCpu(m*n*sizeof(PetscScalar)));
    166:       } else PetscCall(PetscArrayzero(bv->work,m*n));
    167:       PetscCall(PetscMPIIntCast(m*n,&len));
    168:       PetscCallMPI(MPIU_Allreduce(bv->work,C,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)bv)));
    169:     } else {
    170:       PetscCall(BVAllocateWork_Private(bv,2*m*n));
    171:       CC = bv->work+m*n;
    172:       if (k) {
    173:         PetscCall(PetscLogGpuTimeBegin());
    174:         PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_C,CUBLAS_OP_N,m,n,k,&sone,d_A,lda,d_B,ldb,&szero,d_work,m));
    175:         PetscCall(PetscLogGpuTimeEnd());
    176:         PetscCallCUDA(cudaMemcpy(bv->work,d_work,m*n*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    177:         PetscCall(PetscLogGpuToCpu(m*n*sizeof(PetscScalar)));
    178:       } else PetscCall(PetscArrayzero(bv->work,m*n));
    179:       PetscCall(PetscMPIIntCast(m*n,&len));
    180:       PetscCallMPI(MPIU_Allreduce(bv->work,CC,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)bv)));
    181:       for (j=0;j<n;j++) PetscCall(PetscArraycpy(C+j*ldc,CC+j*m,m));
    182:     }
    183:   } else {
    184:     if (k) {
    185:       PetscCall(BVAllocateWork_Private(bv,m*n));
    186:       PetscCall(PetscLogGpuTimeBegin());
    187:       PetscCallCUBLAS(cublasXgemm(cublasv2handle,CUBLAS_OP_C,CUBLAS_OP_N,m,n,k,&sone,d_A,lda,d_B,ldb,&szero,d_work,m));
    188:       PetscCall(PetscLogGpuTimeEnd());
    189:       PetscCallCUDA(cudaMemcpy(bv->work,d_work,m*n*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    190:       PetscCall(PetscLogGpuToCpu(m*n*sizeof(PetscScalar)));
    191:       for (j=0;j<n;j++) PetscCall(PetscArraycpy(C+j*ldc,bv->work+j*m,m));
    192:     }
    193:   }
    194:   PetscCallCUDA(cudaFree(d_work));
    195:   PetscCall(PetscLogGpuFlops(2.0*m*n*k));
    196:   PetscFunctionReturn(PETSC_SUCCESS);
    197: }

    199: /*
    200:     y := A'*x

    202:     y is a CPU array, if NULL bv->buffer is used as a workspace
    203: */
    204: PetscErrorCode BVDotVec_BLAS_CUDA(BV bv,PetscInt n_,PetscInt k_,const PetscScalar *d_A,PetscInt lda_,const PetscScalar *d_x,PetscScalar *y,PetscBool mpi)
    205: {
    206:   PetscScalar       *d_work,szero=0.0,sone=1.0,*yy;
    207:   PetscCuBLASInt    n=0,k=0,lda=0,one=1;
    208:   PetscMPIInt       len;
    209:   cublasHandle_t    cublasv2handle;

    211:   PetscFunctionBegin;
    212:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    213:   PetscCall(PetscCuBLASIntCast(n_,&n));
    214:   PetscCall(PetscCuBLASIntCast(k_,&k));
    215:   PetscCall(PetscCuBLASIntCast(lda_,&lda));
    216:   if (!y) PetscCall(VecCUDAGetArrayWrite(bv->buffer,&d_work));
    217:   else PetscCallCUDA(cudaMalloc((void**)&d_work,k*sizeof(PetscScalar)));
    218:   if (mpi) {
    219:     PetscCall(BVAllocateWork_Private(bv,k));
    220:     if (n) {
    221:       PetscCall(PetscLogGpuTimeBegin());
    222:       PetscCallCUBLAS(cublasXgemv(cublasv2handle,CUBLAS_OP_C,n,k,&sone,d_A,lda,d_x,one,&szero,d_work,one));
    223:       PetscCall(PetscLogGpuTimeEnd());
    224:       PetscCallCUDA(cudaMemcpy(bv->work,d_work,k*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    225:       PetscCall(PetscLogGpuToCpu(k*sizeof(PetscScalar)));
    226:     } else PetscCall(PetscArrayzero(bv->work,k));
    227:     /* reduction */
    228:     PetscCall(PetscMPIIntCast(k,&len));
    229:     if (!y) {
    230:       if (use_gpu_aware_mpi) {  /* case 1: reduce on GPU using a temporary buffer */
    231:         PetscCallCUDA(cudaMalloc((void**)&yy,k*sizeof(PetscScalar)));
    232:         PetscCallMPI(MPIU_Allreduce(d_work,yy,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)bv)));
    233:         PetscCallCUDA(cudaMemcpy(d_work,yy,k*sizeof(PetscScalar),cudaMemcpyDeviceToDevice));
    234:         PetscCallCUDA(cudaFree(yy));
    235:       } else {  /* case 2: reduce on CPU, copy result back to GPU */
    236:         PetscCall(BVAllocateWork_Private(bv,2*k));
    237:         yy = bv->work+k;
    238:         PetscCallCUDA(cudaMemcpy(bv->work,d_work,k*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    239:         PetscCall(PetscLogGpuToCpu(k*sizeof(PetscScalar)));
    240:         PetscCallMPI(MPIU_Allreduce(bv->work,yy,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)bv)));
    241:         PetscCallCUDA(cudaMemcpy(d_work,yy,k*sizeof(PetscScalar),cudaMemcpyHostToDevice));
    242:         PetscCall(PetscLogCpuToGpu(k*sizeof(PetscScalar)));
    243:       }
    244:       PetscCall(VecCUDARestoreArrayWrite(bv->buffer,&d_work));
    245:     } else {  /* case 3: user-provided array y, reduce on CPU */
    246:       PetscCallCUDA(cudaFree(d_work));
    247:       PetscCallMPI(MPIU_Allreduce(bv->work,y,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)bv)));
    248:     }
    249:   } else {
    250:     if (n) {
    251:       PetscCall(PetscLogGpuTimeBegin());
    252:       PetscCallCUBLAS(cublasXgemv(cublasv2handle,CUBLAS_OP_C,n,k,&sone,d_A,lda,d_x,one,&szero,d_work,one));
    253:       PetscCall(PetscLogGpuTimeEnd());
    254:     }
    255:     if (!y) PetscCall(VecCUDARestoreArrayWrite(bv->buffer,&d_work));
    256:     else {
    257:       PetscCallCUDA(cudaMemcpy(y,d_work,k*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    258:       PetscCall(PetscLogGpuToCpu(k*sizeof(PetscScalar)));
    259:       PetscCallCUDA(cudaFree(d_work));
    260:     }
    261:   }
    262:   PetscCall(PetscLogGpuFlops(2.0*n*k));
    263:   PetscFunctionReturn(PETSC_SUCCESS);
    264: }

    266: /*
    267:     Scale n scalars
    268: */
    269: PetscErrorCode BVScale_BLAS_CUDA(BV,PetscInt n_,PetscScalar *d_A,PetscScalar alpha)
    270: {
    271:   PetscCuBLASInt n=0,one=1;
    272:   cublasHandle_t cublasv2handle;

    274:   PetscFunctionBegin;
    275:   PetscCall(PetscCuBLASIntCast(n_,&n));
    276:   if (PetscUnlikely(alpha == (PetscScalar)0.0)) PetscCallCUDA(cudaMemset(d_A,0,n*sizeof(PetscScalar)));
    277:   else if (alpha != (PetscScalar)1.0) {
    278:     PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    279:     PetscCall(PetscLogGpuTimeBegin());
    280:     PetscCallCUBLAS(cublasXscal(cublasv2handle,n,&alpha,d_A,one));
    281:     PetscCall(PetscLogGpuTimeEnd());
    282:     PetscCall(PetscLogGpuFlops(1.0*n));
    283:   }
    284:   PetscFunctionReturn(PETSC_SUCCESS);
    285: }

    287: /*
    288:     Compute 2-norm of vector consisting of n scalars
    289: */
    290: PetscErrorCode BVNorm_BLAS_CUDA(BV,PetscInt n_,const PetscScalar *d_A,PetscReal *nrm)
    291: {
    292:   PetscCuBLASInt n=0,one=1;
    293:   cublasHandle_t cublasv2handle;

    295:   PetscFunctionBegin;
    296:   PetscCall(PetscCuBLASIntCast(n_,&n));
    297:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    298:   PetscCall(PetscLogGpuTimeBegin());
    299:   PetscCallCUBLAS(cublasXnrm2(cublasv2handle,n,d_A,one,nrm));
    300:   PetscCall(PetscLogGpuTimeEnd());
    301:   PetscCall(PetscLogGpuFlops(2.0*n));
    302:   PetscFunctionReturn(PETSC_SUCCESS);
    303: }

    305: /*
    306:     Normalize the columns of A
    307: */
    308: PetscErrorCode BVNormalize_BLAS_CUDA(BV,PetscInt m_,PetscInt n_,PetscScalar *d_A,PetscInt lda_,PetscScalar *eigi)
    309: {
    310:   PetscInt       j,k;
    311:   PetscReal      nrm,nrm1;
    312:   PetscScalar    alpha;
    313:   PetscCuBLASInt m=0,one=1;
    314:   cublasHandle_t cublasv2handle;

    316:   PetscFunctionBegin;
    317:   PetscCall(PetscCuBLASIntCast(m_,&m));
    318:   PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    319:   PetscCall(PetscLogGpuTimeBegin());
    320:   for (j=0;j<n_;j++) {
    321:     k = 1;
    322: #if !defined(PETSC_USE_COMPLEX)
    323:     if (eigi && eigi[j] != 0.0) k = 2;
    324: #endif
    325:     PetscCallCUBLAS(cublasXnrm2(cublasv2handle,m,d_A+j*lda_,one,&nrm));
    326:     if (k==2) {
    327:       PetscCallCUBLAS(cublasXnrm2(cublasv2handle,m,d_A+(j+1)*lda_,one,&nrm1));
    328:       nrm = SlepcAbs(nrm,nrm1);
    329:     }
    330:     alpha = 1.0/nrm;
    331:     PetscCallCUBLAS(cublasXscal(cublasv2handle,m,&alpha,d_A+j*lda_,one));
    332:     if (k==2) {
    333:       PetscCallCUBLAS(cublasXscal(cublasv2handle,m,&alpha,d_A+(j+1)*lda_,one));
    334:       j++;
    335:     }
    336:   }
    337:   PetscCall(PetscLogGpuTimeEnd());
    338:   PetscCall(PetscLogGpuFlops(3.0*m*n_));
    339:   PetscFunctionReturn(PETSC_SUCCESS);
    340: }

    342: /*
    343:    BV_CleanCoefficients_CUDA - Sets to zero all entries of column j of the bv buffer
    344: */
    345: PetscErrorCode BV_CleanCoefficients_CUDA(BV bv,PetscInt j,PetscScalar *h)
    346: {
    347:   PetscScalar    *d_hh,*d_a;
    348:   PetscInt       i;

    350:   PetscFunctionBegin;
    351:   if (!h) {
    352:     PetscCall(VecCUDAGetArray(bv->buffer,&d_a));
    353:     PetscCall(PetscLogGpuTimeBegin());
    354:     d_hh = d_a + j*(bv->nc+bv->m);
    355:     PetscCallCUDA(cudaMemset(d_hh,0,(bv->nc+j)*sizeof(PetscScalar)));
    356:     PetscCall(PetscLogGpuTimeEnd());
    357:     PetscCall(VecCUDARestoreArray(bv->buffer,&d_a));
    358:   } else { /* cpu memory */
    359:     for (i=0;i<bv->nc+j;i++) h[i] = 0.0;
    360:   }
    361:   PetscFunctionReturn(PETSC_SUCCESS);
    362: }

    364: /*
    365:    BV_AddCoefficients_CUDA - Add the contents of the scratch (0-th column) of the bv buffer
    366:    into column j of the bv buffer
    367:  */
    368: PetscErrorCode BV_AddCoefficients_CUDA(BV bv,PetscInt j,PetscScalar *h,PetscScalar *c)
    369: {
    370:   PetscScalar    *d_h,*d_c,sone=1.0;
    371:   PetscInt       i;
    372:   PetscCuBLASInt idx=0,one=1;
    373:   cublasHandle_t cublasv2handle;

    375:   PetscFunctionBegin;
    376:   if (!h) {
    377:     PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    378:     PetscCall(VecCUDAGetArray(bv->buffer,&d_c));
    379:     d_h = d_c + j*(bv->nc+bv->m);
    380:     PetscCall(PetscCuBLASIntCast(bv->nc+j,&idx));
    381:     PetscCall(PetscLogGpuTimeBegin());
    382:     PetscCallCUBLAS(cublasXaxpy(cublasv2handle,idx,&sone,d_c,one,d_h,one));
    383:     PetscCall(PetscLogGpuTimeEnd());
    384:     PetscCall(PetscLogGpuFlops(1.0*(bv->nc+j)));
    385:     PetscCall(VecCUDARestoreArray(bv->buffer,&d_c));
    386:   } else { /* cpu memory */
    387:     for (i=0;i<bv->nc+j;i++) h[i] += c[i];
    388:     PetscCall(PetscLogFlops(1.0*(bv->nc+j)));
    389:   }
    390:   PetscFunctionReturn(PETSC_SUCCESS);
    391: }

    393: /*
    394:    BV_SetValue_CUDA - Sets value in row j (counted after the constraints) of column k
    395:    of the coefficients array
    396: */
    397: PetscErrorCode BV_SetValue_CUDA(BV bv,PetscInt j,PetscInt k,PetscScalar *h,PetscScalar value)
    398: {
    399:   PetscScalar    *d_h,*a;

    401:   PetscFunctionBegin;
    402:   if (!h) {
    403:     PetscCall(VecCUDAGetArray(bv->buffer,&a));
    404:     PetscCall(PetscLogGpuTimeBegin());
    405:     d_h = a + k*(bv->nc+bv->m) + bv->nc+j;
    406:     PetscCallCUDA(cudaMemcpy(d_h,&value,sizeof(PetscScalar),cudaMemcpyHostToDevice));
    407:     PetscCall(PetscLogCpuToGpu(sizeof(PetscScalar)));
    408:     PetscCall(PetscLogGpuTimeEnd());
    409:     PetscCall(VecCUDARestoreArray(bv->buffer,&a));
    410:   } else { /* cpu memory */
    411:     h[bv->nc+j] = value;
    412:   }
    413:   PetscFunctionReturn(PETSC_SUCCESS);
    414: }

    416: /*
    417:    BV_SquareSum_CUDA - Returns the value h'*h, where h represents the contents of the
    418:    coefficients array (up to position j)
    419: */
    420: PetscErrorCode BV_SquareSum_CUDA(BV bv,PetscInt j,PetscScalar *h,PetscReal *sum)
    421: {
    422:   const PetscScalar *d_h;
    423:   PetscScalar       dot;
    424:   PetscInt          i;
    425:   PetscCuBLASInt    idx=0,one=1;
    426:   cublasHandle_t    cublasv2handle;

    428:   PetscFunctionBegin;
    429:   if (!h) {
    430:     PetscCall(PetscCUBLASGetHandle(&cublasv2handle));
    431:     PetscCall(VecCUDAGetArrayRead(bv->buffer,&d_h));
    432:     PetscCall(PetscCuBLASIntCast(bv->nc+j,&idx));
    433:     PetscCall(PetscLogGpuTimeBegin());
    434:     PetscCallCUBLAS(cublasXdot(cublasv2handle,idx,d_h,one,d_h,one,&dot));
    435:     PetscCall(PetscLogGpuTimeEnd());
    436:     PetscCall(PetscLogGpuFlops(2.0*(bv->nc+j)));
    437:     *sum = PetscRealPart(dot);
    438:     PetscCall(VecCUDARestoreArrayRead(bv->buffer,&d_h));
    439:   } else { /* cpu memory */
    440:     *sum = 0.0;
    441:     for (i=0;i<bv->nc+j;i++) *sum += PetscRealPart(h[i]*PetscConj(h[i]));
    442:     PetscCall(PetscLogFlops(2.0*(bv->nc+j)));
    443:   }
    444:   PetscFunctionReturn(PETSC_SUCCESS);
    445: }

    447: /* pointwise multiplication */
    448: static __global__ void PointwiseMult_kernel(PetscInt xcount,PetscScalar *a,const PetscScalar *b,PetscInt n)
    449: {
    450:   PetscInt x;

    452:   x = xcount*gridDim.x*blockDim.x+blockIdx.x*blockDim.x+threadIdx.x;
    453:   if (x<n) a[x] *= PetscRealPart(b[x]);
    454: }

    456: /* pointwise division */
    457: static __global__ void PointwiseDiv_kernel(PetscInt xcount,PetscScalar *a,const PetscScalar *b,PetscInt n)
    458: {
    459:   PetscInt x;

    461:   x = xcount*gridDim.x*blockDim.x+blockIdx.x*blockDim.x+threadIdx.x;
    462:   if (x<n) a[x] /= PetscRealPart(b[x]);
    463: }

    465: /*
    466:    BV_ApplySignature_CUDA - Computes the pointwise product h*omega, where h represents
    467:    the contents of the coefficients array (up to position j) and omega is the signature;
    468:    if inverse=TRUE then the operation is h/omega
    469: */
    470: PetscErrorCode BV_ApplySignature_CUDA(BV bv,PetscInt j,PetscScalar *h,PetscBool inverse)
    471: {
    472:   PetscScalar       *d_h;
    473:   const PetscScalar *d_omega,*omega;
    474:   PetscInt          i,xcount;
    475:   dim3              blocks3d, threads3d;

    477:   PetscFunctionBegin;
    478:   if (!(bv->nc+j)) PetscFunctionReturn(PETSC_SUCCESS);
    479:   if (!h) {
    480:     PetscCall(VecCUDAGetArray(bv->buffer,&d_h));
    481:     PetscCall(VecCUDAGetArrayRead(bv->omega,&d_omega));
    482:     PetscCall(SlepcKernelSetGrid1D(bv->nc+j,&blocks3d,&threads3d,&xcount));
    483:     PetscCall(PetscLogGpuTimeBegin());
    484:     if (inverse) {
    485:       for (i=0;i<xcount;i++) PointwiseDiv_kernel<<<blocks3d,threads3d>>>(i,d_h,d_omega,bv->nc+j);
    486:     } else {
    487:       for (i=0;i<xcount;i++) PointwiseMult_kernel<<<blocks3d,threads3d>>>(i,d_h,d_omega,bv->nc+j);
    488:     }
    489:     PetscCallCUDA(cudaGetLastError());
    490:     PetscCall(PetscLogGpuTimeEnd());
    491:     PetscCall(PetscLogGpuFlops(1.0*(bv->nc+j)));
    492:     PetscCall(VecCUDARestoreArrayRead(bv->omega,&d_omega));
    493:     PetscCall(VecCUDARestoreArray(bv->buffer,&d_h));
    494:   } else {
    495:     PetscCall(VecGetArrayRead(bv->omega,&omega));
    496:     if (inverse) for (i=0;i<bv->nc+j;i++) h[i] /= PetscRealPart(omega[i]);
    497:     else for (i=0;i<bv->nc+j;i++) h[i] *= PetscRealPart(omega[i]);
    498:     PetscCall(VecRestoreArrayRead(bv->omega,&omega));
    499:     PetscCall(PetscLogFlops(1.0*(bv->nc+j)));
    500:   }
    501:   PetscFunctionReturn(PETSC_SUCCESS);
    502: }

    504: /*
    505:    BV_SquareRoot_CUDA - Returns the square root of position j (counted after the constraints)
    506:    of the coefficients array
    507: */
    508: PetscErrorCode BV_SquareRoot_CUDA(BV bv,PetscInt j,PetscScalar *h,PetscReal *beta)
    509: {
    510:   const PetscScalar *d_h;
    511:   PetscScalar       hh;

    513:   PetscFunctionBegin;
    514:   if (!h) {
    515:     PetscCall(VecCUDAGetArrayRead(bv->buffer,&d_h));
    516:     PetscCall(PetscLogGpuTimeBegin());
    517:     PetscCallCUDA(cudaMemcpy(&hh,d_h+bv->nc+j,sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    518:     PetscCall(PetscLogGpuToCpu(sizeof(PetscScalar)));
    519:     PetscCall(PetscLogGpuTimeEnd());
    520:     PetscCall(BV_SafeSqrt(bv,hh,beta));
    521:     PetscCall(VecCUDARestoreArrayRead(bv->buffer,&d_h));
    522:   } else PetscCall(BV_SafeSqrt(bv,h[bv->nc+j],beta));
    523:   PetscFunctionReturn(PETSC_SUCCESS);
    524: }

    526: /*
    527:    BV_StoreCoefficients_CUDA - Copy the contents of the coefficients array to an array dest
    528:    provided by the caller (only values from l to j are copied)
    529: */
    530: PetscErrorCode BV_StoreCoefficients_CUDA(BV bv,PetscInt j,PetscScalar *h,PetscScalar *dest)
    531: {
    532:   const PetscScalar *d_h,*d_a;
    533:   PetscInt          i;

    535:   PetscFunctionBegin;
    536:   if (!h) {
    537:     PetscCall(VecCUDAGetArrayRead(bv->buffer,&d_a));
    538:     PetscCall(PetscLogGpuTimeBegin());
    539:     d_h = d_a + j*(bv->nc+bv->m)+bv->nc;
    540:     PetscCallCUDA(cudaMemcpy(dest-bv->l,d_h,(j-bv->l)*sizeof(PetscScalar),cudaMemcpyDeviceToHost));
    541:     PetscCall(PetscLogGpuToCpu((j-bv->l)*sizeof(PetscScalar)));
    542:     PetscCall(PetscLogGpuTimeEnd());
    543:     PetscCall(VecCUDARestoreArrayRead(bv->buffer,&d_a));
    544:   } else {
    545:     for (i=bv->l;i<j;i++) dest[i-bv->l] = h[bv->nc+i];
    546:   }
    547:   PetscFunctionReturn(PETSC_SUCCESS);
    548: }