CUTLASS 2.6.1 - functional and performance enhancements to strided DGRAD, fixes, and tuning
* cutlass 2.6 update * remove debug prints * cutlass 2.6.1 (minor update) * Updated CHANGELOG. * Minor edit to readme to indicate patch version. * Minor edit to readme. Co-authored-by: Haicheng Wu <haichengw@nvidia.com>, Andrew Kerr <akerr@nvidia.com>
This commit is contained in:
co-authored by
Haicheng Wu <haichengw@nvidia.com>, Andrew Kerr <akerr@nvidia.com>
parent
a01feb93d9
commit
6c2f8f2fb8
@@ -186,12 +186,6 @@ public:
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GemmUniversalConfiguration const &config = *static_cast<GemmUniversalConfiguration const *>(host_workspace);
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GemmUniversalArguments const &args = *static_cast<GemmUniversalArguments const *>(arguments);
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ElementCompute alpha;
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ElementCompute beta;
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alpha = *static_cast<ElementCompute const *>(args.alpha);
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beta = *static_cast<ElementCompute const *>(args.beta);
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TensorRefA ref_A{static_cast<ElementA *>(const_cast<void *>(args.A)), LayoutA(int(config.lda))};
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TensorRefB ref_B{static_cast<ElementB *>(const_cast<void *>(args.B)), LayoutB(int(config.ldb))};
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TensorRefC ref_C{static_cast<ElementC *>(const_cast<void *>(args.C)), LayoutC(int(config.ldc))};
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@@ -212,16 +206,16 @@ public:
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InnerProductOp
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>(
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config.problem_size,
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alpha,
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*static_cast<ElementCompute const *>(args.alpha),
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ref_A,
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kTransformA,
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ref_B,
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kTransformB,
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beta,
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*static_cast<ElementCompute const *>(args.beta),
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ref_C,
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ref_D,
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ElementAccumulator(),
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config.batch_count,
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((config.mode == library::GemmUniversalMode::kBatched) ? config.batch_count : 1),
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args.batch_stride_A,
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args.batch_stride_B,
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args.batch_stride_C,
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@@ -245,16 +239,16 @@ public:
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InnerProductOp
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>(
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config.problem_size,
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alpha,
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*static_cast<ElementCompute const *>(args.alpha),
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ref_A,
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kTransformA,
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ref_B,
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kTransformB,
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beta,
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*static_cast<ElementCompute const *>(args.beta),
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ref_C,
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ref_D,
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ElementAccumulator(),
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config.batch_count,
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((config.mode == library::GemmUniversalMode::kBatched) ? config.batch_count : 1),
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args.batch_stride_A,
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args.batch_stride_B,
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args.batch_stride_C,
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@@ -263,7 +257,7 @@ public:
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return Status::kSuccess;
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}
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return Status::kErrorNotSupported;
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}
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};
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