4db6a6140e
* ex42: Fused MHA imported from xFormers * Remove std:: references * Support K>128 in the example * Support causal option * Support different head size for V, and different seqlength for KV * Update FLOPS counter * Remove bit_cast * fix build: Replace M_LOG2E * Add doc * Revert "Remove bit_cast" This reverts commit 9662fa86bb7c57c1a015ac0bf52cb52940fbbf80. * Explicit casts to int32_t for windows build Co-authored-by: danthe3rd <danthe3rd>
159 lines
4.8 KiB
C++
159 lines
4.8 KiB
C++
/*! \file
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\brief Cutlass provides helper template functions to figure out the right
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datastructures to instanciate to run a GEMM with various parameters (see
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`cutlass/gemm/threadblock/default_mma.h`). However, due to template
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instanciation priority rules, it will only create an MmaMultiStage with
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kStages=3 (otherwise creates an MmePipelined - which is not compatible with
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FastF32). kStages=3 uses too much shared memory and we want to use kStages=2,
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so we just copy-pasted some code from `default_mma.h` and
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`default_mma_core.h` files and wrapped this template to allow our usecase.
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This is really only for the FastF32 case - aka using TensorCores with fp32.
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*/
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#include "cutlass/gemm/threadblock/default_mma.h"
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#include "cutlass/gemm/threadblock/default_mma_core_simt.h"
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#include "cutlass/gemm/threadblock/default_mma_core_sm70.h"
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#include "cutlass/gemm/threadblock/default_mma_core_sm75.h"
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#include "cutlass/gemm/threadblock/default_mma_core_sm80.h"
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namespace cutlass {
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namespace gemm {
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namespace threadblock {
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template <
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/// Element type for A matrix operand
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typename ElementA,
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/// Layout type for A matrix operand
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typename LayoutA,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for B matrix operand
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typename ElementB,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Layout type for C and D matrix operand
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typename LayoutC,
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/// Operator class tag
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typename OperatorClass,
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/// Tag indicating architecture to tune for
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typename ArchTag,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Instruction-level tile size (concept: GemmShape)
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typename InstructionShape,
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/// Number of stages used in the pipelined mainloop
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int Stages,
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/// Operation perfomed by GEMM
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typename Operator,
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typename Enable_ = void>
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struct FindDefaultMma {
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static constexpr bool AccumulatorsInRowMajor = false;
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static constexpr SharedMemoryClearOption SharedMemoryClear =
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SharedMemoryClearOption::kNone;
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using DefaultMma = cutlass::gemm::threadblock::DefaultMma<
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ElementA,
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LayoutA,
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kAlignmentA,
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ElementB,
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LayoutB,
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kAlignmentB,
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ElementAccumulator,
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LayoutC,
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OperatorClass,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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Stages,
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Operator,
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AccumulatorsInRowMajor,
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SharedMemoryClear>;
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};
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/// Specialization for sm80 / FastF32 / multistage with kStages=2
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template <
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typename ElementA_,
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/// Layout type for A matrix operand
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typename LayoutA_,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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typename ElementB_,
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/// Layout type for B matrix operand
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typename LayoutB_,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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typename ElementAccumulator,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Instruction-level tile size (concept: GemmShape)
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typename InstructionShape,
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int kStages,
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typename Operator>
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struct FindDefaultMma<
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ElementA_,
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LayoutA_,
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kAlignmentA,
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ElementB_,
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LayoutB_,
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kAlignmentB,
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ElementAccumulator,
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layout::RowMajor,
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arch::OpClassTensorOp,
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arch::Sm80,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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kStages,
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Operator,
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typename cutlass::platform::enable_if<(kAlignmentA > 1)>::type> {
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using LayoutC = layout::RowMajor;
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using OperatorClass = arch::OpClassTensorOp;
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using ArchTag = arch::Sm80;
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using DefaultMma_ = cutlass::gemm::threadblock::DefaultMma<
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ElementA_,
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LayoutA_,
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kAlignmentA,
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ElementB_,
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LayoutB_,
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kAlignmentB,
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ElementAccumulator,
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LayoutC,
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OperatorClass,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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3,
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Operator>;
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struct DefaultMma : DefaultMma_ {
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using MmaCore_ = typename DefaultMma_::MmaCore;
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// Define the threadblock-scoped multistage matrix multiply
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using ThreadblockMma = cutlass::gemm::threadblock::MmaMultistage<
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typename MmaCore_::Shape,
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typename DefaultMma_::IteratorA,
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typename MmaCore_::SmemIteratorA,
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MmaCore_::kCacheOpA,
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typename DefaultMma_::IteratorB,
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typename MmaCore_::SmemIteratorB,
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MmaCore_::kCacheOpB,
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ElementAccumulator,
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LayoutC,
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typename MmaCore_::MmaPolicy,
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kStages>;
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};
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};
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} // namespace threadblock
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} // namespace gemm
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} // namespace cutlass
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