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[Determinism] Enable environment var to use cusparse spmm deterministic algorithm #7310

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merged 8 commits into from
Apr 19, 2024
Merged

[Determinism] Enable environment var to use cusparse spmm deterministic algorithm #7310

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fdc5108
Enable environment var to use cusparse spmm deterministic algorithm
TristonC Apr 16, 2024
a8ae77c
Apply lint with clang-format
TristonC Apr 17, 2024
371b90b
Merge branch 'master' into issue_7241
frozenbugs Apr 18, 2024
1e5c18d
Merge branch 'master' into issue_7241
frozenbugs Apr 18, 2024
871fb50
Merge branch 'master' into issue_7241
frozenbugs Apr 18, 2024
68c0496
Lint with original format
TristonC Apr 18, 2024
1fedbb0
Merge branch 'issue_7241' of https://github.com/TristonC/dgl into iss…
TristonC Apr 18, 2024
037cd4e
Merge branch 'master' into issue_7241
TristonC Apr 18, 2024
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28 changes: 15 additions & 13 deletions src/array/cuda/spmm.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,8 @@
*/
#include <dgl/array.h>

#include <cstdlib>

#include "../../runtime/cuda/cuda_common.h"
#include "./functor.cuh"
#include "./ge_spmm.cuh"
Expand All @@ -21,13 +23,15 @@
* @note use cusparse if the reduce operator is `sum` and there is
* no broadcast, use dgl's kernel in other cases.
*/
template <int XPU, typename IdType, typename DType>

Check warning on line 26 in src/array/cuda/spmm.cu

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CLANGFORMAT format 

See https://clang.llvm.org/docs/ClangFormat.html.
Run `lintrunner -a` to apply this patch.
void SpMMCsr(
const std::string& op, const std::string& reduce, const BcastOff& bcast,
const CSRMatrix& csr, NDArray ufeat, NDArray efeat, NDArray out,
std::vector<NDArray> out_aux) {
void SpMMCsr(const std::string& op, const std::string& reduce,
const BcastOff& bcast, const CSRMatrix& csr, NDArray ufeat,
NDArray efeat, NDArray out, std::vector<NDArray> out_aux) {
bool is_scalar_efeat = efeat.NumElements() == csr.indices->shape[0];
bool use_efeat = op != "copy_lhs";
bool use_deterministic_alg_only = false;
if (NULL != std::getenv("USE_DETERMINISTIC_ALG"))
use_deterministic_alg_only = true;

if (reduce == "sum") {
bool more_nnz = (csr.indices->shape[0] > csr.num_rows * csr.num_cols);
Expand All @@ -37,10 +41,9 @@
for (int i = 1; i < ufeat->ndim; ++i) x_length *= ufeat->shape[i];
CusparseCsrmm2<DType, IdType>(
ufeat->ctx, csr, static_cast<DType*>(ufeat->data), nullptr,
static_cast<DType*>(out->data), x_length);
} else if (
op == "mul" && is_scalar_efeat &&
cusparse_available<DType, IdType>(more_nnz)) {
static_cast<DType*>(out->data), x_length, use_deterministic_alg_only);
} else if (op == "mul" && is_scalar_efeat &&
cusparse_available<DType, IdType>(more_nnz)) {
// cusparse
int64_t x_length = 1;
for (int i = 1; i < ufeat->ndim; ++i) x_length *= ufeat->shape[i];
Expand All @@ -50,7 +53,7 @@
CusparseCsrmm2<DType, IdType>(
ufeat->ctx, csr, static_cast<DType*>(ufeat->data),
static_cast<DType*>(efeat->data), static_cast<DType*>(out->data),
x_length);
x_length, use_deterministic_alg_only);
} else { // general kernel
SWITCH_OP(op, Op, {
cuda::SpMMCsr<IdType, DType, Op, cuda::reduce::Sum<IdType, DType> >(
Expand All @@ -76,10 +79,9 @@
* @brief CUDA implementation of g-SpMM on Coo format.
*/
template <int XPU, typename IdType, typename DType>
void SpMMCoo(
const std::string& op, const std::string& reduce, const BcastOff& bcast,
const COOMatrix& coo, NDArray ufeat, NDArray efeat, NDArray out,
std::vector<NDArray> out_aux) {
void SpMMCoo(const std::string& op, const std::string& reduce,
const BcastOff& bcast, const COOMatrix& coo, NDArray ufeat,
NDArray efeat, NDArray out, std::vector<NDArray> out_aux) {
if (reduce == "sum") {
SWITCH_OP(op, Op, {
cuda::SpMMCoo<IdType, DType, Op, cuda::reduce::Sum<IdType, DType, true> >(
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