[WIP]Unit tests for Kernels that perform BF16 x BF16 = MXFP8 and MXFP8 x MXFP8 = BF16

test/unit/gemm/device/sm100_blockscaled_tensorop_gemm/CMakeLists.txt

@@ -83,6 +83,16 @@ cutlass_test_unit_gemm_device_add_executable(
   mxf8_mxf8_void_f8_nt_layout.cu
 )
 
+cutlass_test_unit_gemm_device_add_executable(
+  cutlass_test_unit_gemm_device_bstensorop_sm100_mxf8xmxf8_bf16
+
+  BATCH_SOURCES ON
+  BATCH_SIZE 1
+
+  mxf8_mxf8_void_bf16_tn_layout.cu
+)
+
+
 cutlass_test_unit_gemm_device_add_executable(
   cutlass_test_unit_gemm_device_bstensorop_sm100_mxf6xmxf8
 

test/unit/gemm/device/sm100_blockscaled_tensorop_gemm/mxf8_mxf8_void_bf16_tn_layout.cu

@@ -0,0 +1,128 @@
+/***************************************************************************************************
+ * Copyright (c) 2024 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-License-Identifier: BSD-3-Clause
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ *
+ * 1. Redistributions of source code must retain the above copyright notice, this
+ * list of conditions and the following disclaimer.
+ *
+ * 2. Redistributions in binary form must reproduce the above copyright notice,
+ * this list of conditions and the following disclaimer in the documentation
+ * and/or other materials provided with the distribution.
+ *
+ * 3. Neither the name of the copyright holder nor the names of its
+ * contributors may be used to endorse or promote products derived from
+ * this software without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+ * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+ * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+ * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+ * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+ * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ **************************************************************************************************/
+
+#include <iostream>
+
+#include "cutlass/cutlass.h"
+#include "cute/tensor.hpp"
+#include "cute/atom/mma_atom.hpp"
+
+#include "cutlass/numeric_types.h"
+
+#include "cutlass/gemm/device/gemm_universal_adapter.h"
+#include "cutlass/gemm/kernel/gemm_universal.hpp"
+#include "cutlass/gemm/collective/collective_builder.hpp"
+
+#include "cutlass/epilogue/dispatch_policy.hpp"
+#include "cutlass/epilogue/collective/collective_builder.hpp"
+
+#include "cutlass/epilogue/thread/activation.h"
+#include "../../../common/cutlass_unit_test.h"
+
+#include "../gemm_testbed_3x.hpp"
+
+using namespace cute;
+
+
+#if defined(CUTLASS_ARCH_MMA_SM100_SUPPORTED)
+
+TEST(SM100Only_Device_Gemm_ue8m0xe4m3t_ue8m0xe4m3n_void_bf16t_bstensorop_f32, 128x128x256_4x4x1_1sm_auto) {
+  // Describe A and B tensors
+  using ElementA = cutlass::mx_float8_t<cutlass::float_e4m3_t>;
+  constexpr int AlignA = 16;
+  using GmemLayoutA = cutlass::layout::RowMajor;
+  using ElementB = cutlass::mx_float8_t<cutlass::float_e4m3_t>;
+  constexpr int AlignB = 16;
+  using GmemLayoutB = cutlass::layout::ColumnMajor;
+
+  // Describe C and D tensors
+  using ElementC = void;
+  constexpr int AlignC = 8;
+  using GmemLayoutC = cutlass::layout::RowMajor;
+  using ElementD = cutlass::bfloat16_t;
+  constexpr int AlignD = 8;
+  using GmemLayoutD = cutlass::layout::RowMajor;
+
+  // Mma's accumulator type
+  using ElementAccumulator = float;
+  // Epilogue computation's precision type
+  using ElementCompute = float;
+
+  // Tile and cluster shapes
+  // Collective MMA takes tile shape of the MMA operation as input
+  using MmaTileShape_MNK = Shape<_128,_128,_256>;
+  // Cluster size for multicast
+  using ClusterShape_MNK = Shape<_4,_4,_1>;
+
+  //
+  // Construct CollectiveEpilogue
+  //
+
+  using CollectiveEpilogue = typename cutlass::epilogue::collective::CollectiveBuilder<
+      cutlass::arch::Sm100, cutlass::arch::OpClassBlockScaledTensorOp,      // Arch and Tensorop spec
+      MmaTileShape_MNK, ClusterShape_MNK,                                   // Mma instruction tile shape, cluster shape
+      cutlass::epilogue::collective::EpilogueTileAuto,                      // Epilogue subtile shape. Auto will find a suitable tile shape
+      ElementAccumulator, ElementCompute,                                   // Mma instr's accumulator type and compute precision for epilogue
+      ElementC, GmemLayoutC, AlignC,                                        // C tensor description
+      ElementD, GmemLayoutD, AlignD,                                        // D tensor description
+      cutlass::epilogue::collective::EpilogueScheduleAuto                   // Epilogue schedule policy
+    >::CollectiveOp;
+
+  //
+  // Construct CollectiveMainloop
+  //
+
+  using CollectiveMainloop = typename cutlass::gemm::collective::CollectiveBuilder<
+      cutlass::arch::Sm100, cutlass::arch::OpClassBlockScaledTensorOp,      // Arch and Tensorop spec
+      ElementA, GmemLayoutA, AlignA,                                        // A tensor elem type, layout and alignment requirement
+      ElementB, GmemLayoutB, AlignB,                                        // B tensor elem type, layout and alignment requirement
+      ElementAccumulator,                                                   // Mma instruction accumulator type
+      MmaTileShape_MNK, ClusterShape_MNK,                                   // Mma instruction tile shape, cluster shape
+      // Epilogue's SMEM usage that needs to be subtracted from overall SMEM capacity 
+      cutlass::gemm::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename CollectiveEpilogue::SharedStorage))>,
+      cutlass::gemm::collective::KernelScheduleAuto    // Kernel schedule policy. Auto or using targeted scheduling policy - underlying selection is KernelTmaWarpSpecialized1SmMxf4Sm100
+    >::CollectiveOp;
+
+  // Create Gemm Kernel using CollectiveEpilogue and CollectiveMainloop created by the builders
+  using GemmKernel = cutlass::gemm::kernel::GemmUniversal<
+      Shape<int,int,int,int>,
+      CollectiveMainloop,
+      CollectiveEpilogue
+    >;
+
+  using Gemm = cutlass::gemm::device::GemmUniversalAdapter<GemmKernel>;
+  // Run tests
+  auto pass = test::gemm::device::TestAll<Gemm>();
+  // Check results
+  EXPECT_TRUE(pass);
+}
+
+#endif

test/unit/gemm/device/sm100_tensorop_gemm/CMakeLists.txt

@@ -67,6 +67,15 @@ cutlass_test_unit_gemm_device_add_executable(
   s8_s8_void_s32.cu
   s8_s8_s32_s32_fusion.cu
 )
+
+cutlass_test_unit_gemm_device_add_executable(
+  cutlass_test_unit_gemm_device_tensorop_sm100_bf16xbf16_epilogue
+
+  BATCH_SOURCES ON
+  BATCH_SIZE 1
+
+  bf16_bf16_f32_e4m3_ue8m0_epilogue.cu
+)
 endif()
 
 add_subdirectory(narrow_precision)