423 lines
17 KiB
Plaintext
423 lines
17 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: BSD-3-Clause
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* 3. Neither the name of the copyright holder nor the names of its
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* contributors may be used to endorse or promote products derived from
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* this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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#include "cutlass_unit_test.h"
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#include <iostream>
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#include <thrust/host_vector.h>
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#include <thrust/device_vector.h>
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#include <cute/tensor.hpp>
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using namespace cute;
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template <class ElementType, class SmemLayout>
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struct SharedStorage
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{
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cute::array_aligned<ElementType, cute::cosize_v<SmemLayout>> smem;
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};
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#if CUDA_12_0_SM90_FEATURES_SUPPORTED
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template <class T, class TiledCopy, class CTA_Tiler, class GmemLayout, class SmemLayout>
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__global__ void
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tma_test_device_cute(T const* g_in, T* g_out,
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CUTE_GRID_CONSTANT TiledCopy const tma, CTA_Tiler cta_tiler,
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GmemLayout gmem_layout, SmemLayout smem_layout)
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{
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CUTE_STATIC_ASSERT_V(product_each(shape(cta_tiler)) == product_each(shape(smem_layout)));
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// Use Shared Storage structure to allocate and distribute aligned SMEM addresses
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extern __shared__ char shared_memory[];
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using SharedStorage = SharedStorage<T, SmemLayout>;
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SharedStorage& shared_storage = *reinterpret_cast<SharedStorage*>(shared_memory);
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// Construct SMEM tensor
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Tensor sB = make_tensor(make_smem_ptr(shared_storage.smem.data()), smem_layout); // (CTA_TILE_M,CTA_TILE_N,...)
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// TMA requires special handling of strides to deal with coord codomain mapping
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// Represent the full tensors -- get these from TMA
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Tensor mA = make_tensor(make_gmem_ptr(g_in), gmem_layout);
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Tensor mB = tma.get_tma_tensor(shape(gmem_layout));
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constexpr int R = rank_v<CTA_Tiler>;
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Tensor gA = local_tile(mA, cta_tiler, repeat<R>(_)); // (CTA_TILE_M,CTA_TILE_N,...REST_M,REST_N,...)
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Tensor gB = local_tile(mB, cta_tiler, repeat<R>(_)); // (CTA_TILE_M,CTA_TILE_N,...REST_M,REST_N,...)
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//
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// Prepare the TMA_STORE
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//
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auto cta_tma = tma.get_slice(Int<0>{}); // CTA slice
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Tensor tBsB_x = cta_tma.partition_S(sB); // (TMA,TMA_M,TMA_N)
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Tensor tBgB_x = cta_tma.partition_D(gB); // (TMA,TMA_M,TMA_N,REST_M,REST_N)
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#if 0
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if (thread0()) {
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print(tma);
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print("TILE : "); print(cta_tiler); print("\n");
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print(" mB : "); print( mB.data()); print(" o "); print( mB.layout()); print("\n");
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print(" gB : "); print( gB.data()); print(" o "); print( gB.layout()); print("\n");
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print("tBgB_x: "); print(tBgB_x.data()); print(" o "); print(tBgB_x.layout()); print("\n");
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print(" sB : "); print( sB.data()); print(" o "); print( sB.layout()); print("\n");
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print("tBsB_x: "); print(tBsB_x.data()); print(" o "); print(tBsB_x.layout()); print("\n");
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}
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#endif
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//
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// Perform the TMA_STORE
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//
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// INPUT: Group the CTA_TILE_X modes and REST_X modes for input
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Tensor tAgA = group_modes<0,R>(group_modes<R,rank(gA)>(gA)); // (CTA_TILE, REST)
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// OUTPUT: Group the REST_X modes and the TMA_X modes to easily iterate through the tiles
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Tensor tBgB = group_modes<1,rank(tBgB_x)>(tBgB_x); // (TMA,REST)
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Tensor tBsB = group_modes<1,rank(tBsB_x)>(tBsB_x); // (TMA,REST)
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static_assert(size<1>(tBsB) == 1);
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#if 0
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if (thread0()) {
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print("tAgA : "); print(tAgA.data()); print(" o "); print(tAgA.layout()); print("\n");
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print("tBsB : "); print(tBsB.data()); print(" o "); print(tBsB.layout()); print("\n");
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print("tBgB : "); print(tBgB.data()); print(" o "); print(tBgB.layout()); print("\n");
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}
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#endif
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// Loop over the TMA stages, using smem as our buffer
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for (int stage = 0; stage < size<1>(tBgB); ++stage)
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{
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//
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// Read in trivially gmem -> smem
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//
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for (int i = threadIdx.x; i < size(sB); i += blockDim.x) {
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sB(i) = tAgA(i,stage);
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}
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__syncthreads();
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//
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// Perform the TMA_STORE
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//
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if (threadIdx.x == 0) {
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copy(tma, tBsB(_,0), tBgB(_,stage));
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}
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tma_store_wait<0>();
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__syncthreads();
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}
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}
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template <class T, class GMEM_Layout, class SMEM_Layout, class CTA_Tile>
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void
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test_tma_store(GMEM_Layout const& gmem_layout,
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SMEM_Layout const& smem_layout,
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CTA_Tile const& cta_tile)
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{
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thrust::host_vector<T> h_in(cosize(gmem_layout));
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for (int i = 0; i < h_in.size(); ++i) { h_in[i] = T(i % 13); }
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thrust::device_vector<T> d_in = h_in;
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thrust::device_vector<T> d_out(h_in.size(), T(-1));
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Tensor gA = make_tensor(d_out.data().get(), gmem_layout);
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auto tma = make_tma_copy(SM90_TMA_STORE{}, gA, smem_layout, cta_tile, Int<1>{});
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//print(tma);
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int smem_size = int(sizeof(SharedStorage<T, decltype(smem_layout)>));
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tma_test_device_cute<<<1, 128, smem_size>>>(
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thrust::raw_pointer_cast(d_in.data()),
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thrust::raw_pointer_cast(d_out.data()),
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tma, cta_tile,
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gmem_layout,
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smem_layout);
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thrust::host_vector<T> h_out = d_out;
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Tensor hA_in = make_tensor(h_in.data(), gmem_layout);
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Tensor hA_out = make_tensor(h_out.data(), gmem_layout);
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for (int i = 0; i < size(gmem_layout); ++i) {
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EXPECT_EQ(hA_in(i), hA_out(i));
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}
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}
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template <class T, class GMEM_Layout, class SMEM_Layout>
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void
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test_tma_store(GMEM_Layout const& gmem_layout,
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SMEM_Layout const& smem_layout)
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{
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return test_tma_store<T>(gmem_layout, smem_layout, product_each(shape(smem_layout)));
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}
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TEST(SM90_CuTe_Hopper, Tma_Load_1D)
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{
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Layout smem_layout = Layout<_256, _1>{};
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{
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Layout gmem_layout = smem_layout;
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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{
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Layout gmem_layout = make_layout(128, GenColMajor{});
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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}
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TEST(SM90_CuTe_Hopper, Tma_Store_32x32_Col)
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{
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Layout smem_layout = Layout<Shape<_32,_32>, Stride<_1,_32>>{};
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{
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Layout gmem_layout = smem_layout;
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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{
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Layout gmem_layout = make_layout(make_shape(32,32), GenColMajor{});
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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{
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Layout gmem_layout = make_layout(make_shape(32,32), make_stride(Int<1>{}, 1024));
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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}
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TEST(SM90_CuTe_Hopper, Tma_Store_32x32_Row)
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{
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Layout smem_layout = Layout<Shape<_32,_32>, Stride<_32,_1>>{};
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{
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Layout gmem_layout = smem_layout;
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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{
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Layout gmem_layout = make_layout(make_shape(32,32), GenRowMajor{});
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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{
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Layout gmem_layout = make_layout(make_shape(32,32), make_stride(1024, Int<1>{}));
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test_tma_store<int8_t>(gmem_layout, smem_layout);
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test_tma_store<half_t>(gmem_layout, smem_layout);
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test_tma_store< float>(gmem_layout, smem_layout);
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test_tma_store<double>(gmem_layout, smem_layout);
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}
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}
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template <class T, template <typename> typename SWIZZLE_ATOM>
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void
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test_tma_store_swizzle_atom_mn()
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{
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auto smem_layout = SWIZZLE_ATOM<T>{};
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Layout gmem_layout = make_layout(shape(smem_layout), GenColMajor{});
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return test_tma_store<T>(gmem_layout, smem_layout, product_each(shape(smem_layout)));
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}
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template <class T, template <typename> typename SWIZZLE_ATOM>
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void
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test_tma_store_swizzle_atom_k()
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{
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auto smem_layout = SWIZZLE_ATOM<T>{};
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Layout gmem_layout = make_layout(shape(smem_layout), GenRowMajor{});
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return test_tma_store<T>(gmem_layout, smem_layout, product_each(shape(smem_layout)));
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}
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TEST(SM90_CuTe_Hopper, Tma_Store_Swizzle_Atoms)
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{
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test_tma_store_swizzle_atom_mn<int8_t, GMMA::Layout_MN_SW128_Atom>();
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test_tma_store_swizzle_atom_mn<half_t, GMMA::Layout_MN_SW128_Atom>();
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test_tma_store_swizzle_atom_mn< float, GMMA::Layout_MN_SW128_Atom>();
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test_tma_store_swizzle_atom_mn<double, GMMA::Layout_MN_SW128_Atom>();
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test_tma_store_swizzle_atom_mn<int8_t, GMMA::Layout_MN_SW64_Atom>();
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test_tma_store_swizzle_atom_mn<half_t, GMMA::Layout_MN_SW64_Atom>();
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test_tma_store_swizzle_atom_mn< float, GMMA::Layout_MN_SW64_Atom>();
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test_tma_store_swizzle_atom_mn<double, GMMA::Layout_MN_SW64_Atom>();
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test_tma_store_swizzle_atom_mn<int8_t, GMMA::Layout_MN_SW32_Atom>();
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test_tma_store_swizzle_atom_mn<half_t, GMMA::Layout_MN_SW32_Atom>();
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test_tma_store_swizzle_atom_mn< float, GMMA::Layout_MN_SW32_Atom>();
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test_tma_store_swizzle_atom_mn<double, GMMA::Layout_MN_SW32_Atom>();
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test_tma_store_swizzle_atom_mn<int8_t, GMMA::Layout_MN_INTER_Atom>();
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test_tma_store_swizzle_atom_mn<half_t, GMMA::Layout_MN_INTER_Atom>();
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test_tma_store_swizzle_atom_mn< float, GMMA::Layout_MN_INTER_Atom>();
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test_tma_store_swizzle_atom_mn<double, GMMA::Layout_MN_INTER_Atom>();
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test_tma_store_swizzle_atom_k<int8_t, GMMA::Layout_K_SW128_Atom>();
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test_tma_store_swizzle_atom_k<half_t, GMMA::Layout_K_SW128_Atom>();
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test_tma_store_swizzle_atom_k< float, GMMA::Layout_K_SW128_Atom>();
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test_tma_store_swizzle_atom_k<double, GMMA::Layout_K_SW128_Atom>();
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test_tma_store_swizzle_atom_k<int8_t, GMMA::Layout_K_SW64_Atom>();
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test_tma_store_swizzle_atom_k<half_t, GMMA::Layout_K_SW64_Atom>();
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test_tma_store_swizzle_atom_k< float, GMMA::Layout_K_SW64_Atom>();
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test_tma_store_swizzle_atom_k<double, GMMA::Layout_K_SW64_Atom>();
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test_tma_store_swizzle_atom_k<int8_t, GMMA::Layout_K_SW32_Atom>();
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test_tma_store_swizzle_atom_k<half_t, GMMA::Layout_K_SW32_Atom>();
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test_tma_store_swizzle_atom_k< float, GMMA::Layout_K_SW32_Atom>();
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test_tma_store_swizzle_atom_k<double, GMMA::Layout_K_SW32_Atom>();
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test_tma_store_swizzle_atom_k<int8_t, GMMA::Layout_K_INTER_Atom>();
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test_tma_store_swizzle_atom_k<half_t, GMMA::Layout_K_INTER_Atom>();
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test_tma_store_swizzle_atom_k< float, GMMA::Layout_K_INTER_Atom>();
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test_tma_store_swizzle_atom_k<double, GMMA::Layout_K_INTER_Atom>();
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}
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template <class T, template <typename> typename SWIZZLE_ATOM>
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void
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test_tma_store_swizzle_tile_mn()
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{
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auto smem_layout = tile_to_shape(SWIZZLE_ATOM<T>{}, Shape<_128,_128>{});
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Layout gmem_layout = make_layout(make_shape(int(size<0>(smem_layout)), int(size<1>(smem_layout))), GenColMajor{});
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return test_tma_store<T>(gmem_layout, smem_layout, product_each(shape(smem_layout)));
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}
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template <class T, template <typename> typename SWIZZLE_ATOM>
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void
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test_tma_store_swizzle_tile_k()
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{
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auto smem_layout = tile_to_shape(SWIZZLE_ATOM<T>{}, Shape<_128,_128>{});
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Layout gmem_layout = make_layout(make_shape(int(size<0>(smem_layout)), int(size<1>(smem_layout))), GenRowMajor{});
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return test_tma_store<T>(gmem_layout, smem_layout, product_each(shape(smem_layout)));
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}
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TEST(SM90_CuTe_Hopper, Tma_Store_Swizzle_Tiles)
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{
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// Other T-types use too much smem
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test_tma_store_swizzle_tile_mn<int8_t, GMMA::Layout_MN_SW128_Atom>();
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test_tma_store_swizzle_tile_mn<half_t, GMMA::Layout_MN_SW128_Atom>();
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test_tma_store_swizzle_tile_mn<int8_t, GMMA::Layout_MN_SW64_Atom>();
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test_tma_store_swizzle_tile_mn<half_t, GMMA::Layout_MN_SW64_Atom>();
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test_tma_store_swizzle_tile_mn<int8_t, GMMA::Layout_MN_SW32_Atom>();
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test_tma_store_swizzle_tile_mn<half_t, GMMA::Layout_MN_SW32_Atom>();
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test_tma_store_swizzle_tile_mn<int8_t, GMMA::Layout_MN_INTER_Atom>();
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test_tma_store_swizzle_tile_mn<half_t, GMMA::Layout_MN_INTER_Atom>();
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test_tma_store_swizzle_tile_k<int8_t, GMMA::Layout_K_SW128_Atom>();
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test_tma_store_swizzle_tile_k<half_t, GMMA::Layout_K_SW128_Atom>();
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test_tma_store_swizzle_tile_k<int8_t, GMMA::Layout_K_SW64_Atom>();
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test_tma_store_swizzle_tile_k<half_t, GMMA::Layout_K_SW64_Atom>();
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test_tma_store_swizzle_tile_k<int8_t, GMMA::Layout_K_SW32_Atom>();
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test_tma_store_swizzle_tile_k<half_t, GMMA::Layout_K_SW32_Atom>();
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test_tma_store_swizzle_tile_k<int8_t, GMMA::Layout_K_INTER_Atom>();
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test_tma_store_swizzle_tile_k<half_t, GMMA::Layout_K_INTER_Atom>();
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}
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// Tensor by-mode
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TEST(SM90_CuTe_Hopper, Tma_Store_Tensor)
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{
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// 3-mode TMA
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{
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Layout gmem_layout = make_layout(make_shape(128, 64, 5));
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auto cta_tile = Shape<_64, _32>{}; // GMEM Tiling:
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// Take 64-elem from m
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// Take 32-elem from k
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auto smem_layout = make_layout(Shape<_64,_32>{});
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test_tma_store<half_t>(gmem_layout, smem_layout, cta_tile);
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}
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// 4-mode TMA
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{
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Layout gmem_layout = make_layout(make_shape(make_shape(80,40),make_shape(32,12)));
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auto cta_tile = Shape<Shape<_16,_8>,Shape<_32,_2>>{}; // GMEM Tiling:
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// Take 16-elem from m0, 8-elem from m1,
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// Take 32-elem from k0, 2-elem from k1
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auto smem_layout = make_layout(Shape<_128,_64>{});
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test_tma_store<half_t>(gmem_layout, smem_layout, cta_tile);
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}
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// 5-mode TMA
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{
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Layout gmem_layout = make_layout(make_shape(make_shape(32,32,32),make_shape(32,12)));
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auto cta_tile = Shape<Shape<_16,_4,_2>,Shape<_16,_2>>{}; // GMEM Tiling:
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// Take 4-elem from m0, 4-elem from m1, 5-elem from m2
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// Take 32-elem from k0, 2-elem from k1
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auto smem_layout = make_layout(Shape<_128,_32>{});
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test_tma_store<half_t>(gmem_layout, smem_layout, cta_tile);
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}
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}
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// Tensor Multimode -- TMA with more than 5 modes in GMEM (packs residual modes into last TMA mode)
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TEST(SM90_CuTe_Hopper, Tma_Store_Tensor_Multimode)
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{
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{
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Layout gmem_layout = make_layout(make_shape(make_shape(32,3,2,2),make_shape(32,4,2)));
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auto cta_tile = Shape<Shape<_32>, Shape<_32,_2>>{}; // GMEM Tiling:
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// Take 32-elem from m0
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// Take 32-elem from k0, 2-elem from k1
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auto smem_layout = make_layout(Shape<_32,_64>{});
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test_tma_store<half_t>(gmem_layout, smem_layout, cta_tile);
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}
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|
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{
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Layout gmem_layout = make_layout(make_shape(make_shape(64,3,2,2),make_shape(32,4,2)));
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auto cta_tile = Shape<Shape<_32,_3>, Shape<_32,_2>>{}; // GMEM Tiling:
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// Take 32-elem from m0, 3-elem from m1
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// Take 32-elem from k0, 2-elem from k1
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auto smem_layout = make_layout(Shape<_96,_64>{});
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test_tma_store<half_t>(gmem_layout, smem_layout, cta_tile);
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}
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|
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{
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Layout gmem_layout = make_layout(make_shape(make_shape(64,3,2,3,2),make_shape(32,4,2,2)));
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auto cta_tile = Shape<Shape<_32>, Shape<_16,_2>>{}; // GMEM Tiling:
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// Take 32-elem from m0
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// Take 16-elem from k0, 2-elem from k1
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auto smem_layout = make_layout(Shape<_32,_32>{});
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test_tma_store<half_t>(gmem_layout, smem_layout, cta_tile);
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}
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}
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#endif
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