CUTLASS 2.4 (Implicit GEMM convolution) (#147)
CUTLASS 2.4 (Implicit GEMM Convolution) Co-authored-by: Manish Gupta <manigupta@nvidia.com>, Haicheng Wu <haichengw@nvidia.com>, Dustyn Blasig <dblasig@nvidia.com>, Andrew Kerr <akerr@nvidia.com>
This commit is contained in:
Manish Gupta
co-authored by
Manish Gupta <manigupta@nvidia.com>, Haicheng Wu <haichengw@nvidia.com>, Dustyn Blasig <dblasig@nvidia.com>, Andrew Kerr <akerr@nvidia.com>
Manish Gupta <manigupta@nvidia.com>, Haicheng Wu <haichengw@nvidia.com>, Dustyn Blasig <dblasig@nvidia.com>, Andrew Kerr <akerr@nvidia.com>
parent
c2b80ad4e4
commit
6615010cd0
@@ -43,6 +43,7 @@
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#include "cutlass/epilogue/threadblock/output_tile_thread_map.h"
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#include "cutlass/arch/arch.h"
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#include "cutlass/arch/memory.h"
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#include "cutlass/epilogue/threadblock/predicated_tile_iterator_params.h"
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////////////////////////////////////////////////////////////////////////////////
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@@ -102,68 +103,20 @@ public:
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// Parameters struct
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//
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struct Params {
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//
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// Data members
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//
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LongIndex stride; ///< stride in bytes between rows
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LongIndex increment_row; ///< increment quantity (in bytes) to advance when moving between rows
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LongIndex increment_group; ///< increment quantity (in bytes) to advance when moving to the next group
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LongIndex increment_cluster; ///< increment quantity (in bytes) to advance when moving to the next cluster
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LongIndex advance_row; ///< amount to add to move to the next 'row' position
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LongIndex advance_group; ///< amount to add to move to the next 'group' position
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LongIndex advance_cluster; ///< amount to add to move to the next 'cluster' position
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LongIndex advance_tile; ///< amount to add to move to the next 'tile'
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//
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// Methods
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//
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/// Uses a non-template class
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struct Params : PredicatedTileIteratorParams {
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CUTLASS_HOST_DEVICE
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Status initialize(Index stride_) {
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stride = LongIndex(stride_);
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increment_row = stride * ThreadMap::Delta::kRow;
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increment_group = stride * ThreadMap::Delta::kGroup
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- stride * ThreadMap::Delta::kRow * (ThreadMap::Iterations::kRow - 1);
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increment_cluster = stride * ThreadMap::Delta::kCluster
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- stride * ThreadMap::Delta::kGroup * (ThreadMap::Iterations::kGroup - 1)
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- stride * ThreadMap::Delta::kRow * (ThreadMap::Iterations::kRow - 1);
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advance_row = stride * ThreadMap::Shape::kRow;
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advance_group = stride * (ThreadMap::Shape::kGroup - 1) * ThreadMap::Shape::kRow * ThreadMap::Count::kRow;
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advance_cluster =
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stride *
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ThreadMap::Count::kGroup * ThreadMap::Shape::kGroup * ThreadMap::Count::kRow * ThreadMap::Shape::kRow;;
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advance_tile =
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stride *
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ThreadMap::Shape::kGroup *
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ThreadMap::Shape::kRow *
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ThreadMap::Shape::kCluster *
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ThreadMap::Shape::kTile;
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return Status::kSuccess;
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}
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Params() { }
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CUTLASS_HOST_DEVICE
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Params() {
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initialize(0);
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}
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CUTLASS_HOST_DEVICE
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Params(Layout const &layout) {
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initialize(layout.stride(0) * int(sizeof(AccessType)) / kElementsPerAccess);
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Params(Layout const &layout):
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PredicatedTileIteratorParams(
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layout.stride(0) * int(sizeof(AccessType)) / kElementsPerAccess,
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make_OutputTileThreadMapDesc<ThreadMap>()
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)
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{
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}
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};
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@@ -207,7 +160,7 @@ private:
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//
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/// Parameters structure containing reference and precomputed state.
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Params params_;
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PredicatedTileIteratorParams params_;
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/// Byte-level pointer
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uint8_t *byte_pointer_;
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@@ -239,12 +192,13 @@ public:
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/// Constructor
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CUTLASS_DEVICE
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PredicatedTileIterator(
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Params const & params,
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PredicatedTileIteratorParams const & params,
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Element *pointer,
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TensorCoord extent,
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int thread_idx,
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TensorCoord threadblock_offset = TensorCoord()
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): params_(params)
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):
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params_(params)
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{
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TensorCoord thread_offset = ThreadMap::initial_offset(thread_idx) + threadblock_offset;
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@@ -745,6 +699,309 @@ public:
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};
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///////////////////////////////////////////////////////////////////////////////
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/// Tile iterator used to load output tile from shared memory in epilogue.
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///
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/// Satisfies: ReadableTileIterator | InterleavedMaskedTileIterator | ForwardTileIterator
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///
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template <
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typename ThreadMap_, ///< Thread map (conept: OutputTileThreadMap)
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typename Element_, ///< Element data type
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int InterleavedN ///< Number of Interleaved N
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>
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class InterleavedConvPredicatedTileIterator {
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public:
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using ThreadMap = ThreadMap_;
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using Element = Element_;
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using Layout = layout::TensorNCxHWx<InterleavedN>;
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using TensorRef = TensorRef<Element, Layout>;
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using ConstTensorRef = typename TensorRef::ConstTensorRef;
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using Index = typename Layout::Index;
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using LongIndex = typename Layout::LongIndex;
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using TensorCoord = Tensor4DCoord;
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static int const kElementsPerAccess = ThreadMap::kElementsPerAccess;
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static int const kThreads = ThreadMap::kThreads;
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static int const kIterations = ThreadMap::Iterations::kCount;
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/// Fragment object
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using Fragment = Array<Element, ThreadMap::kElementsPerAccess>;
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/// Memory access size
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using AccessType = AlignedArray<Element, ThreadMap::kElementsPerAccess>;
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//
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// Parameters struct
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//
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struct Params {
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//
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// Data members
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//
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LongIndex stride_col; ///< stride in bytes between columns
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LongIndex stride_row; ///< stride in bytes between rows
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//
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// Methods
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//
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CUTLASS_HOST_DEVICE
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Status initialize(typename Layout::Stride stride_) {
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stride_col = stride_[1];
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stride_row = stride_[2];
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return Status::kSuccess;
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}
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CUTLASS_HOST_DEVICE
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Params() {
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initialize(cutlass::make_Coord(0, 0, 0));
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}
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CUTLASS_HOST_DEVICE
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Params(Layout const &layout) {
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initialize(layout.stride());
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}
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};
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/// Mask object
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struct Mask {
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static int const kCount =
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(ThreadMap::Iterations::kRow < 8) ? 8 : ThreadMap::Iterations::kRow;
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/// Predicate state
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bool predicates[kCount];
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//
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// Mask
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//
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CUTLASS_HOST_DEVICE
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Mask() {
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enable();
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}
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///< Efficiently disables all accesses guarded by mask
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CUTLASS_HOST_DEVICE void clear() {
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < kCount; ++i) {
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predicates[i] = false;
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}
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}
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///< CUTLASS_HOST_DEVICE enables all accesses guarded by mask
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CUTLASS_DEVICE void enable() {
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < kCount; ++i) {
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predicates[i] = true;
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}
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}
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};
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private:
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//
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// Data members
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//
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/// Parameters structure containing reference and precomputed state.
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Params params_;
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/// Byte-level pointer
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uint8_t *byte_pointer_;
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/// Array of boolean values to contain steady-state predicates
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Mask mask_;
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/// Extent of the matrix tile in columns
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Index extent_col_;
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/// Extent of the matrix tile in rows
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Index extent_row_;
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/// Extent of the matrix tile in pq
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Index extent_pq_;
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/// A thread's starting row position (assuming steady-state predicates have
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/// been computed)
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Index thread_start_row_;
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/// A thread's starting column position (assuming steady-state predicates have
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/// been computed)
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Index thread_start_col_;
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/// Internal iteration counter
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LongIndex iteration_row_;
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LongIndex iteration_col_;
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uint32_t pq_mul_;
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uint32_t pq_shr_;
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private:
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//
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// Methods
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//
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public:
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//
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// Methods
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//
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/// Constructor
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CUTLASS_DEVICE
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InterleavedConvPredicatedTileIterator(
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Params const & params,
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Element *pointer,
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TensorCoord extent,
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int thread_idx,
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MatrixCoord threadblock_offset
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):
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params_(params) {
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MatrixCoord thread_offset = ThreadMap::initial_offset(thread_idx) + threadblock_offset;
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extent_col_ = extent.c();
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extent_pq_ = extent.h() * extent.w();
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extent_row_ = extent.n() * extent_pq_;
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find_divisor(pq_mul_, pq_shr_, extent_pq_);
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thread_start_row_ = thread_offset.row();
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thread_start_col_ = thread_offset.column();
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// Initialize predicates
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CUTLASS_PRAGMA_UNROLL
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for (int r = 0; r < ThreadMap::Iterations::kRow; ++r) {
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mask_.predicates[r] =
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((thread_offset.row() + ThreadMap::Delta::kRow * r) < extent_row_);
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}
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// Initialize pointer
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byte_pointer_ = reinterpret_cast<uint8_t *>(pointer) +
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((thread_start_col_ / InterleavedN) * params_.stride_col +
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(thread_start_col_ % InterleavedN)) *
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sizeof_bits<Element>::value / 8;
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// Initialize internal state counter
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iteration_row_ = iteration_col_ = 0;
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}
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/// Adds a pointer offset in units of Element
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CUTLASS_HOST_DEVICE
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void add_pointer_offset(LongIndex pointer_offset) {
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byte_pointer_ += pointer_offset * sizeof_bits<Element>::value / 8;
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}
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/// Loads a fragment from memory
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CUTLASS_DEVICE
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void load(Fragment &frag) {
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int col_offset = iteration_col_ * ThreadMap::Delta::kColumn;
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bool col_guard = ((thread_start_col_ + col_offset) < extent_col_);
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bool guard = col_guard && mask_.predicates[iteration_row_];
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int n, pq_rem;
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fast_divmod(n, pq_rem,
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thread_start_row_ + iteration_row_ * ThreadMap::Delta::kRow,
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extent_pq_, pq_mul_, pq_shr_);
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uint8_t *byte_pointer =
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byte_pointer_ + (n * params_.stride_row + pq_rem * InterleavedN) *
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sizeof_bits<Element>::value / 8;
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AccessType *frag_ptr = reinterpret_cast<AccessType *>(&frag);
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AccessType const *memory_pointer =
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reinterpret_cast<AccessType const *>(byte_pointer);
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cutlass::arch::global_load<
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AccessType,
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sizeof(AccessType)
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>(
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*frag_ptr,
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(void *)memory_pointer,
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guard);
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}
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/// Stores a fragment to memory
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CUTLASS_DEVICE
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void store(Fragment const &frag) {
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int col_offset = iteration_col_ * ThreadMap::Delta::kColumn;
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bool col_guard = ((thread_start_col_ + col_offset) < extent_col_);
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bool guard = col_guard && mask_.predicates[iteration_row_];
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int n, pq_rem;
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fast_divmod(n, pq_rem,
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thread_start_row_ + iteration_row_ * ThreadMap::Delta::kRow,
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extent_pq_, pq_mul_, pq_shr_);
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uint8_t *byte_pointer =
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byte_pointer_ + (n * params_.stride_row + pq_rem * InterleavedN) *
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sizeof_bits<Element>::value / 8;
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AccessType const *frag_ptr = reinterpret_cast<AccessType const *>(&frag);
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AccessType *memory_pointer = reinterpret_cast<AccessType *>(byte_pointer);
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if (guard) {
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*memory_pointer = *frag_ptr;
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}
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}
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/// Overrides the internal iteration index
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CUTLASS_HOST_DEVICE
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void set_iteration_index(int iteration) {
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iteration_row_ = iteration % ThreadMap::Iterations::kRow;
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iteration_col_ = iteration / ThreadMap::Iterations::kRow;
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}
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/// Advances to the next position to load or store
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CUTLASS_HOST_DEVICE
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InterleavedConvPredicatedTileIterator &operator++() {
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++iteration_row_;
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if (iteration_row_ == ThreadMap::Iterations::kRow) {
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iteration_row_ = 0;
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++iteration_col_;
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byte_pointer_ += params_.stride_col;
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if (iteration_col_ == ThreadMap::Iterations::kColumn) {
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iteration_col_ = 0;
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}
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}
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return *this;
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}
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///< Efficiently disables all accesses guarded by mask
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CUTLASS_DEVICE void clear_mask() {
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mask_.clear();
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}
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///< Efficiently enables all accesses guarded by mask
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CUTLASS_DEVICE void enable_mask() {
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mask_.enable();
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}
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///< Sets the mask
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CUTLASS_DEVICE void get_mask(Mask &mask) {
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return mask_;
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}
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///< Sets the mask
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CUTLASS_DEVICE void set_mask(Mask const &mask) {
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mask_ = mask;
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}
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};
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///////////////////////////////////////////////////////////////////////////////
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} // namespace threadblock
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