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Fix SpGEMM crashing on empty rows #1220

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merged 4 commits into from
Dec 8, 2021
Merged

Fix SpGEMM crashing on empty rows #1220

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2d6cb76
Add SPGEMM_KK_LP and SPGEMM_KK_SPEED in spgemm unit test
Dec 8, 2021
8e444fc
Fix CUDA team_shmem().get_shmem() errors caused by misaligned team_sh…
Dec 8, 2021
80a40ee
Fix crashes on empty arrays
Dec 8, 2021
7fcea13
Fix crashes on empty rows
Dec 8, 2021
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2 changes: 2 additions & 0 deletions src/sparse/KokkosSparse_spgemm_numeric.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -139,6 +139,8 @@ void spgemm_numeric(KernelHandle *handle,
"If you need this case please let kokkos-kernels developers know.\n");
}

if (m < 1 || n < 1 || k < 1) return;
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I do not recall the exact interface we provide so I just want to make sure that the short cut above does not create issues for something like: C=beta*C+alpha*A*B which would fail to compute C=beta*C if k==0.
I believe that we only implement C=alpha*A*B though?

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Correct, we don't support adding to an existing C, so this check is OK.


typedef typename KernelHandle::const_size_type c_size_t;
typedef typename KernelHandle::const_nnz_lno_t c_lno_t;
typedef typename KernelHandle::const_nnz_scalar_t c_scalar_t;
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6 changes: 5 additions & 1 deletion src/sparse/impl/KokkosSparse_spgemm_impl_kkmem.hpp
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Expand Up @@ -132,7 +132,7 @@ struct KokkosSPGEMM<HandleType, a_row_view_t_, a_lno_nnz_view_t_,
valuesC(valuesC_),
pEntriesC(entriesC_.data()),
pvaluesC(valuesC_.data()),
shared_memory_size(shared_memory_size_),
shared_memory_size(shared_memory_size_ / 8 * 8),
vector_size(vector_size_),
memory_space(mpool_),
// max_nnz(),
Expand Down Expand Up @@ -691,6 +691,8 @@ struct KokkosSPGEMM<HandleType, a_row_view_t_, a_lno_nnz_view_t_,

for (nnz_lno_t row_index = team_row_begin; row_index < team_row_end;
++row_index) {
if (row_mapA[row_index] == row_mapA[row_index + 1]) // skip empty A rows
continue;
#if 1
teamMember.team_barrier();
#endif
Expand Down Expand Up @@ -1019,6 +1021,8 @@ struct KokkosSPGEMM<HandleType, a_row_view_t_, a_lno_nnz_view_t_,
int vector_shift = thread_rank * vector_size + vector_rank;
for (nnz_lno_t row_index = team_row_begin; row_index < team_row_end;
++row_index) {
if (row_mapA[row_index] == row_mapA[row_index + 1]) // skip empty A rows
continue;
#if 1
teamMember.team_barrier();
#endif
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8 changes: 7 additions & 1 deletion unit_test/sparse/Test_Sparse_spgemm.hpp
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Expand Up @@ -276,7 +276,9 @@ void test_spgemm(lno_t m, lno_t k, lno_t n, size_type nnz, lno_t bandwidth,
run_spgemm<crsMat_t, device>(A, B, SPGEMM_DEBUG, output_mat2);

std::vector<SPGEMMAlgorithm> algorithms = {
SPGEMM_KK, SPGEMM_KK_MEMORY, SPGEMM_KK_SPEED, SPGEMM_KK_MEMSPEED};
SPGEMM_KK, SPGEMM_KK_LP, SPGEMM_KK_MEMORY /* alias SPGEMM_KK_MEMSPEED */,
SPGEMM_KK_SPEED /* alias SPGEMM_KK_DENSE */
};

#ifdef HAVE_KOKKOSKERNELS_MKL
algorithms.push_back(SPGEMM_MKL);
Expand Down Expand Up @@ -321,6 +323,8 @@ void test_spgemm(lno_t m, lno_t k, lno_t n, size_type nnz, lno_t bandwidth,
}
break;

case SPGEMM_KK: algo = "SPGEMM_KK"; break;
case SPGEMM_KK_LP: algo = "SPGEMM_KK_LP"; break;
case SPGEMM_KK_MEMSPEED: algo = "SPGEMM_KK_MEMSPEED"; break;
case SPGEMM_KK_SPEED: algo = "SPGEMM_KK_SPEED"; break;
case SPGEMM_KK_MEMORY: algo = "SPGEMM_KK_MEMORY"; break;
Expand Down Expand Up @@ -446,6 +450,8 @@ void test_issue402() {
test_spgemm<SCALAR, ORDINAL, OFFSET, DEVICE>(0, 12, 5, 0, 10, 0, true); \
test_spgemm<SCALAR, ORDINAL, OFFSET, DEVICE>(10, 10, 0, 0, 10, 10, false); \
test_spgemm<SCALAR, ORDINAL, OFFSET, DEVICE>(10, 10, 0, 0, 10, 10, true); \
test_spgemm<SCALAR, ORDINAL, OFFSET, DEVICE>(10, 10, 10, 0, 0, 0, false); \
test_spgemm<SCALAR, ORDINAL, OFFSET, DEVICE>(10, 10, 10, 0, 0, 0, true); \
test_issue402<SCALAR, ORDINAL, OFFSET, DEVICE>(); \
}

Expand Down