Date: 2013-07-02T14:41:53+00:00

Actual source code: aijAssemble.cu
petsc-3.4.2 2013-07-02

      1: #include "petscconf.h"
      2: PETSC_CUDA_EXTERN_C_BEGIN
     3:  #include ../src/mat/impls/aij/seq/aij.h
     4:  #include petscbt.h
     5:  #include ../src/vec/vec/impls/dvecimpl.h
      6: #include "petsc-private/vecimpl.h"
      7: PETSC_CUDA_EXTERN_C_END
      8: #undef VecType
     9:  #include ../src/mat/impls/aij/seq/seqcusp/cuspmatimpl.h

     11: #include <thrust/reduce.h>
     12: #include <thrust/inner_product.h>

     14: #include <cusp/array1d.h>
     15: #include <cusp/print.h>
     16: #include <cusp/coo_matrix.h>

     18: #include <cusp/io/matrix_market.h>

     20: #include <thrust/iterator/counting_iterator.h>
     21: #include <thrust/iterator/transform_iterator.h>
     22: #include <thrust/iterator/permutation_iterator.h>
     23: #include <thrust/functional.h>

     25: // this example illustrates how to make repeated access to a range of values
     26: // examples:
     27: //   repeated_range([0, 1, 2, 3], 1) -> [0, 1, 2, 3]
     28: //   repeated_range([0, 1, 2, 3], 2) -> [0, 0, 1, 1, 2, 2, 3, 3]
     29: //   repeated_range([0, 1, 2, 3], 3) -> [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]
     30: //   ...

     32: template <typename Iterator>
     33: class repeated_range
     34: {
     35: public:

     37:   typedef typename thrust::iterator_difference<Iterator>::type difference_type;

     39:   struct repeat_functor : public thrust::unary_function<difference_type,difference_type>
     40:   {
     41:     difference_type repeats;

     43:     repeat_functor(difference_type repeats) : repeats(repeats) {}

     45:     __host__ __device__
     46:     difference_type operator()(const difference_type &i) const {
     47:       return i / repeats;
     48:     }
     49:   };

     51:   typedef typename thrust::counting_iterator<difference_type>                   CountingIterator;
     52:   typedef typename thrust::transform_iterator<repeat_functor, CountingIterator> TransformIterator;
     53:   typedef typename thrust::permutation_iterator<Iterator,TransformIterator>     PermutationIterator;

     55:   // type of the repeated_range iterator
     56:   typedef PermutationIterator iterator;

     58:   // construct repeated_range for the range [first,last)
     59:   repeated_range(Iterator first, Iterator last, difference_type repeats) : first(first), last(last), repeats(repeats) {}

     61:   iterator begin(void) const
     62:   {
     63:     return PermutationIterator(first, TransformIterator(CountingIterator(0), repeat_functor(repeats)));
     64:   }

     66:   iterator end(void) const
     67:   {
     68:     return begin() + repeats * (last - first);
     69:   }

     71: protected:
     72:   difference_type repeats;
     73:   Iterator        first;
     74:   Iterator        last;

     76: };

     78: // this example illustrates how to repeat blocks in a range multiple times
     79: // examples:
     80: //   tiled_range([0, 1, 2, 3], 2)    -> [0, 1, 2, 3, 0, 1, 2, 3]
     81: //   tiled_range([0, 1, 2, 3], 4, 2) -> [0, 1, 2, 3, 0, 1, 2, 3]
     82: //   tiled_range([0, 1, 2, 3], 2, 2) -> [0, 1, 0, 1, 2, 3, 2, 3]
     83: //   tiled_range([0, 1, 2, 3], 2, 3) -> [0, 1, 0, 1 0, 1, 2, 3, 2, 3, 2, 3]
     84: //   ...

     86: template <typename Iterator>
     87: class tiled_range
     88: {
     89: public:

     91:   typedef typename thrust::iterator_difference<Iterator>::type difference_type;

     93:   struct tile_functor : public thrust::unary_function<difference_type,difference_type>
     94:   {
     95:     difference_type repeats;
     96:     difference_type tile_size;

     98:     tile_functor(difference_type repeats, difference_type tile_size) : tile_size(tile_size), repeats(repeats) {}

    100:     __host__ __device__
    101:     difference_type operator()(const difference_type &i) const {
    102:       return tile_size * (i / (tile_size * repeats)) + i % tile_size;
    103:     }
    104:   };

    106:   typedef typename thrust::counting_iterator<difference_type>                   CountingIterator;
    107:   typedef typename thrust::transform_iterator<tile_functor, CountingIterator>   TransformIterator;
    108:   typedef typename thrust::permutation_iterator<Iterator,TransformIterator>     PermutationIterator;

    110:   // type of the tiled_range iterator
    111:   typedef PermutationIterator iterator;

    113:   // construct repeated_range for the range [first,last)
    114:   tiled_range(Iterator first, Iterator last, difference_type repeats)
    115:     : first(first), last(last), repeats(repeats), tile_size(last - first) {}

    117:   tiled_range(Iterator first, Iterator last, difference_type repeats, difference_type tile_size)
    118:     : first(first), last(last), repeats(repeats), tile_size(tile_size)
    119:   {
    120:     // ASSERT((last - first) % tile_size == 0)
    121:   }

    123:   iterator begin(void) const
    124:   {
    125:     return PermutationIterator(first, TransformIterator(CountingIterator(0), tile_functor(repeats, tile_size)));
    126:   }

    128:   iterator end(void) const
    129:   {
    130:     return begin() + repeats * (last - first);
    131:   }

    133: protected:
    134:   difference_type repeats;
    135:   difference_type tile_size;
    136:   Iterator        first;
    137:   Iterator        last;
    138: };

    140: typedef cusp::device_memory memSpace;
    141: typedef int IndexType;
    142: typedef PetscScalar ValueType;
    143: typedef cusp::array1d<IndexType, memSpace> IndexArray;
    144: typedef cusp::array1d<ValueType, memSpace> ValueArray;
    145: typedef IndexArray::iterator IndexArrayIterator;
    146: typedef ValueArray::iterator ValueArrayIterator;

    148: // Ne: Number of elements
    149: // Nl: Number of dof per element
    152: PetscErrorCode MatSetValuesBatch_SeqAIJCUSP(Mat J, PetscInt Ne, PetscInt Nl, PetscInt *elemRows, const PetscScalar *elemMats)
    153: {
    154:   size_t         N  = Ne * Nl;
    155:   size_t         No = Ne * Nl*Nl;
    156:   PetscInt       Nr; // Number of rows

    159:   // copy elemRows and elemMat to device
    160:   IndexArray d_elemRows(elemRows, elemRows + N);
    161:   ValueArray d_elemMats(elemMats, elemMats + No);

    164:   MatGetSize(J, &Nr, NULL);
    165:   // allocate storage for "fat" COO representation of matrix
    166:   PetscInfo1(J, "Making COO matrix of size %d\n", Nr);
    167:   cusp::coo_matrix<IndexType,ValueType, memSpace> COO(Nr, Nr, No);

    169:   // repeat elemRows entries Nl times
    170:   PetscInfo(J, "Making row indices\n");
    171:   repeated_range<IndexArrayIterator> rowInd(d_elemRows.begin(), d_elemRows.end(), Nl);
    172:   thrust::copy(rowInd.begin(), rowInd.end(), COO.row_indices.begin());

    174:   // tile rows of elemRows Nl times
    175:   PetscInfo(J, "Making column indices\n");
    176:   tiled_range<IndexArrayIterator> colInd(d_elemRows.begin(), d_elemRows.end(), Nl, Nl);
    177:   thrust::copy(colInd.begin(), colInd.end(), COO.column_indices.begin());

    179:   // copy values from elemMats into COO structure (could be avoided)
    180:   thrust::copy(d_elemMats.begin(), d_elemMats.end(), COO.values.begin());

    182:   // For MPIAIJ, split this into two COO matrices, and return both
    183:   //   Need the column map

    185:   // print the "fat" COO representation
    186: #if !defined(PETSC_USE_COMPLEX)
    187:   if (PetscLogPrintInfo) cusp::print(COO);
    188: #endif
    189:   // sort COO format by (i,j), this is the most costly step
    190:   PetscInfo(J, "Sorting rows and columns\n");
    191: #if 1
    192:   COO.sort_by_row_and_column();
    193: #else
    194:   {
    195:     PetscInfo(J, "  Making permutation\n");
    196:     IndexArray permutation(No);
    197:     thrust::sequence(permutation.begin(), permutation.end());

    199:     // compute permutation and sort by (I,J)
    200:     {
    201:       PetscInfo(J, "  Sorting columns\n");
    202:       IndexArray temp(No);
    203:       thrust::copy(COO.column_indices.begin(), COO.column_indices.end(), temp.begin());
    204:       thrust::stable_sort_by_key(temp.begin(), temp.end(), permutation.begin());
    205:       PetscInfo(J, "    Sorted columns\n");
    206:       if (PetscLogPrintInfo) {
    207:         for (IndexArrayIterator t_iter = temp.begin(), p_iter = permutation.begin(); t_iter != temp.end(); ++t_iter, ++p_iter) {
    208:           PetscInfo2(J, "%d(%d)\n", *t_iter, *p_iter);
    209:         }
    210:       }

    212:       PetscInfo(J, "  Copying rows\n");
    213:       //cusp::copy(COO.row_indices, temp);
    214:       thrust::copy(COO.row_indices.begin(), COO.row_indices.end(), temp.begin());
    215:       PetscInfo(J, "  Gathering rows\n");
    216:       thrust::gather(permutation.begin(), permutation.end(), temp.begin(), COO.row_indices.begin());
    217:       PetscInfo(J, "  Sorting rows\n");
    218:       thrust::stable_sort_by_key(COO.row_indices.begin(), COO.row_indices.end(), permutation.begin());

    220:       PetscInfo(J, "  Gathering columns\n");
    221:       cusp::copy(COO.column_indices, temp);
    222:       thrust::gather(permutation.begin(), permutation.end(), temp.begin(), COO.column_indices.begin());
    223:     }

    225:     // use permutation to reorder the values
    226:     {
    227:       PetscInfo(J, "  Sorting values\n");
    228:       ValueArray temp(COO.values);
    229:       cusp::copy(COO.values, temp);
    230:       thrust::gather(permutation.begin(), permutation.end(), temp.begin(), COO.values.begin());
    231:     }
    232:   }
    233: #endif

    235:   // print the "fat" COO representation
    236: #if !defined(PETSC_USE_COMPLEX)
    237:   if (PetscLogPrintInfo) cusp::print(COO);
    238: #endif
    239:   // compute number of unique (i,j) entries
    240:   //   this counts the number of changes as we move along the (i,j) list
    241:   PetscInfo(J, "Computing number of unique entries\n");
    242:   size_t num_entries = thrust::inner_product
    243:                          (thrust::make_zip_iterator(thrust::make_tuple(COO.row_indices.begin(), COO.column_indices.begin())),
    244:                          thrust::make_zip_iterator(thrust::make_tuple(COO.row_indices.end (),  COO.column_indices.end()))   - 1,
    245:                          thrust::make_zip_iterator(thrust::make_tuple(COO.row_indices.begin(), COO.column_indices.begin())) + 1,
    246:                          size_t(1),
    247:                          thrust::plus<size_t>(),
    248:                          thrust::not_equal_to< thrust::tuple<IndexType,IndexType> >());

    250:   // allocate COO storage for final matrix
    251:   PetscInfo(J, "Allocating compressed matrix\n");
    252:   cusp::coo_matrix<IndexType, ValueType, memSpace> A(Nr, Nr, num_entries);

    254:   // sum values with the same (i,j) index
    255:   // XXX thrust::reduce_by_key is unoptimized right now, so we provide a SpMV-based one in cusp::detail
    256:   //     the Cusp one is 2x faster, but still not optimal
    257:   // This could possibly be done in-place
    258:   PetscInfo(J, "Compressing matrix\n");
    259:   thrust::reduce_by_key(thrust::make_zip_iterator(thrust::make_tuple(COO.row_indices.begin(), COO.column_indices.begin())),
    260:                         thrust::make_zip_iterator(thrust::make_tuple(COO.row_indices.end(),   COO.column_indices.end())),
    261:                         COO.values.begin(),
    262:                         thrust::make_zip_iterator(thrust::make_tuple(A.row_indices.begin(), A.column_indices.begin())),
    263:                         A.values.begin(),
    264:                         thrust::equal_to< thrust::tuple<IndexType,IndexType> >(),
    265:                         thrust::plus<ValueType>());

    267:   // print the final matrix
    268: #if !defined(PETSC_USE_COMPLEX)
    269:   if (PetscLogPrintInfo) cusp::print(A);
    270: #endif
    271:   //std::cout << "Writing matrix" << std::endl;
    272:   //cusp::io::write_matrix_market_file(A, "A.mtx");

    274:   PetscInfo(J, "Converting to PETSc matrix\n");
    275:   MatSetType(J, MATSEQAIJCUSP);
    276:   //cusp::csr_matrix<PetscInt,PetscScalar,cusp::device_memory> Jgpu;
    277:   CUSPMATRIX *Jgpu = new CUSPMATRIX;
    278:   cusp::convert(A, *Jgpu);
    279: #if !defined(PETSC_USE_COMPLEX)
    280:   if (PetscLogPrintInfo) cusp::print(*Jgpu);
    281: #endif
    282:   PetscInfo(J, "Copying to CPU matrix\n");
    283:   MatCUSPCopyFromGPU(J, Jgpu);
    284:   return(0);
    285: }