Date: 2016-07-24T16:53:20+00:00

Actual source code: aijAssemble.cu
petsc-3.7.3 2016-07-24
Report Typos and Errors

      1: #define PETSC_SKIP_COMPLEX
      2: #define PETSC_SKIP_SPINLOCK

      4: #include <petscconf.h>
      5: #include <../src/mat/impls/aij/seq/aij.h>          /*I "petscmat.h" I*/
      6: #include <petscbt.h>
      7: #include <../src/vec/vec/impls/dvecimpl.h>
      8: #include <petsc/private/vecimpl.h>
      9: #undef VecType
     10: #include <../src/mat/impls/aij/seq/seqcusp/cuspmatimpl.h>

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

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

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

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

     26: // this example illustrates how to make repeated access to a range of values
     27: // examples:
     28: //   repeated_range([0, 1, 2, 3], 1) -> [0, 1, 2, 3]
     29: //   repeated_range([0, 1, 2, 3], 2) -> [0, 0, 1, 1, 2, 2, 3, 3]
     30: //   repeated_range([0, 1, 2, 3], 3) -> [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]
     31: //   ...

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

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

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

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

     46:     __host__ __device__
     47:     difference_type operator()(const difference_type &i) const {
     48:       return i / repeats;
     49:     }
     50:   };

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

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

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

     62:   iterator begin(void) const
     63:   {
     64:     return PermutationIterator(first, TransformIterator(CountingIterator(0), repeat_functor(repeats)));
     65:   }

     67:   iterator end(void) const
     68:   {
     69:     return begin() + repeats * (last - first);
     70:   }

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

     77: };

     79: // this example illustrates how to repeat blocks in a range multiple times
     80: // examples:
     81: //   tiled_range([0, 1, 2, 3], 2)    -> [0, 1, 2, 3, 0, 1, 2, 3]
     82: //   tiled_range([0, 1, 2, 3], 4, 2) -> [0, 1, 2, 3, 0, 1, 2, 3]
     83: //   tiled_range([0, 1, 2, 3], 2, 2) -> [0, 1, 0, 1, 2, 3, 2, 3]
     84: //   tiled_range([0, 1, 2, 3], 2, 3) -> [0, 1, 0, 1 0, 1, 2, 3, 2, 3, 2, 3]
     85: //   ...

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

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

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

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

    101:     __host__ __device__
    102:     difference_type operator()(const difference_type &i) const {
    103:       return tile_size * (i / (tile_size * repeats)) + i % tile_size;
    104:     }
    105:   };

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

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

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

    118:   tiled_range(Iterator first, Iterator last, difference_type repeats, difference_type tile_size)
    119:     : first(first), last(last), repeats(repeats), tile_size(tile_size)
    120:   {
    121:     // ASSERT((last - first) % tile_size == 0)
    122:   }

    124:   iterator begin(void) const
    125:   {
    126:     return PermutationIterator(first, TransformIterator(CountingIterator(0), tile_functor(repeats, tile_size)));
    127:   }

    129:   iterator end(void) const
    130:   {
    131:     return begin() + repeats * (last - first);
    132:   }

    134: protected:
    135:   difference_type repeats;
    136:   difference_type tile_size;
    137:   Iterator        first;
    138:   Iterator        last;
    139: };

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

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

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

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

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

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

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

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

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

    200:     // compute permutation and sort by (I,J)
    201:     {
    202:       PetscInfo(J, "  Sorting columns\n");
    203:       IndexArray temp(No);
    204:       thrust::copy(COO.column_indices.begin(), COO.column_indices.end(), temp.begin());
    205:       thrust::stable_sort_by_key(temp.begin(), temp.end(), permutation.begin());
    206:       PetscInfo(J, "    Sorted columns\n");
    207:       if (PetscLogPrintInfo) {
    208:         for (IndexArrayIterator t_iter = temp.begin(), p_iter = permutation.begin(); t_iter != temp.end(); ++t_iter, ++p_iter) {
    209:           PetscInfo2(J, "%d(%d)\n", *t_iter, *p_iter);
    210:         }
    211:       }

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

    221:       PetscInfo(J, "  Gathering columns\n");
    222:       cusp::copy(COO.column_indices, temp);
    223:       thrust::gather(permutation.begin(), permutation.end(), temp.begin(), COO.column_indices.begin());
    224:     }

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

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

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

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

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

    275:   PetscInfo(J, "Converting to PETSc matrix\n");
    276:   MatSetType(J, MATSEQAIJCUSP);
    277:   //cusp::csr_matrix<PetscInt,PetscScalar,cusp::device_memory> Jgpu;
    278:   CUSPMATRIX *Jgpu = new CUSPMATRIX;
    279:   cusp::convert(A, *Jgpu);
    280: #if !defined(PETSC_USE_COMPLEX)
    281:   if (PetscLogPrintInfo) cusp::print(*Jgpu);
    282: #endif
    283:   PetscInfo(J, "Copying to CPU matrix\n");
    284:   MatCUSPCopyFromGPU(J, Jgpu);
    285:   return(0);
    286: }