CUTLASS 3.1 (#915)

Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
2023-04-14 20:19:34 -07:00
parent 9b8166e3f0
commit d572cc1aab
482 changed files with 37184 additions and 16419 deletions
--- a/test/python/backend/gemm/gemm_bf16_sm80.py
+++ b/test/python/backend/gemm/gemm_bf16_sm80.py
@@ -0,0 +1,128 @@
+#################################################################################################
+#
+# Copyright (c) 2017 - 2023 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.
+#
+#################################################################################################
+
+import cutlass.backend
+from cutlass.backend import *
+from cutlass.backend.test import *
+import unittest
+
+from cutlass.backend.test.gemm_testbed import test_all_gemm
+from cutlass.backend.utils.device import device_cc
+
+
+@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
+class GemmBF16TensorOpSm80(unittest.TestCase):
+    def SM80_Device_Gemm_bf16n_bf16n_f32t_tensor_op_f32_64x128x64_32x64x64(self):
+        math_inst = MathInstruction(
+            instruction_shape=[16, 8, 16],
+            element_a=cutlass_bindings.bfloat16, element_b=cutlass_bindings.bfloat16,
+            element_accumulator=cutlass_bindings.float32, opcode_class=cutlass_bindings.OpClass.TensorOp,
+            math_operation=MathOperation.multiply_add
+        )
+
+        tile_description = TileDescription(
+            threadblock_shape=[64, 128, 64],
+            stages=4, warp_count=[2, 2, 1],
+            math_instruction=math_inst
+        )
+
+        A = TensorDescription(
+            element=cutlass_bindings.bfloat16, layout=cutlass_bindings.ColumnMajor,
+            alignment=8
+        )
+        B = TensorDescription(
+            element=cutlass_bindings.bfloat16, layout=cutlass_bindings.ColumnMajor,
+            alignment=8
+        )
+        C = TensorDescription(
+            element=cutlass_bindings.float32, layout=cutlass_bindings.RowMajor,
+            alignment=4
+        )
+
+        epilogue_functor = LinearCombination(
+            C.element, C.alignment, 
+            math_inst.element_accumulator, cutlass_bindings.float32)
+        
+        swizzling_functor = cutlass_bindings.IdentitySwizzle1
+
+        operation = GemmOperationUniversal(
+            arch=80, tile_description=tile_description,
+            A=A, B=B, C=C, 
+            epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
+        )
+
+        self.assertTrue(test_all_gemm(operation, "universal"))
+    
+    def test_SM80_Device_Gemm_bf16t_bf16t_bf16t_tensor_op_f32_128x256x64_64x64x64(self):
+        math_inst = MathInstruction(
+            instruction_shape=[16, 8, 16],
+            element_a=cutlass_bindings.bfloat16, element_b=cutlass_bindings.bfloat16,
+            element_accumulator=cutlass_bindings.float32, opcode_class=cutlass_bindings.OpClass.TensorOp,
+            math_operation=MathOperation.multiply_add
+        )
+
+        tile_description = TileDescription(
+            threadblock_shape=[64, 128, 32],
+            stages=6, warp_count=[2, 2, 1],
+            math_instruction=math_inst
+        )
+
+        A = TensorDescription(
+            element=cutlass_bindings.bfloat16, layout=cutlass_bindings.RowMajor,
+            alignment=8
+        )
+        B = TensorDescription(
+            element=cutlass_bindings.bfloat16, layout=cutlass_bindings.RowMajor,
+            alignment=8
+        )
+        C = TensorDescription(
+            element=cutlass_bindings.bfloat16, layout=cutlass_bindings.RowMajor,
+            alignment=8
+        )
+
+        epilogue_functor = LinearCombination(
+            C.element, C.alignment, 
+            math_inst.element_accumulator, cutlass_bindings.float32)
+        
+        swizzling_functor = cutlass_bindings.IdentitySwizzle1
+
+        operation = GemmOperationUniversal(
+            arch=80, tile_description=tile_description,
+            A=A, B=B, C=C, 
+            epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
+        )
+
+        self.assertTrue(test_all_gemm(operation, "multistage"))
+
+if __name__ == '__main__':
+    cutlass.backend.get_memory_pool(2**30, 2**30)
+    unittest.main()