fb335f6a5f
CUTLASS 2.0 Substantially refactored for - Better performance, particularly for native Turing Tensor Cores - Robust and durable templates spanning the design space - Encapsulated functionality embodying modern C++11 programming techniques - Optimized containers and data types for efficient, generic, portable device code Updates to: - Quick start guide - Documentation - Utilities - CUTLASS Profiler Native Turing Tensor Cores - Efficient GEMM kernels targeting Turing Tensor Cores - Mixed-precision floating point, 8-bit integer, 4-bit integer, and binarized operands Coverage of existing CUTLASS functionality: - GEMM kernels targeting CUDA and Tensor Cores in NVIDIA GPUs - Volta Tensor Cores through native mma.sync and through WMMA API - Optimizations such as parallel reductions, threadblock rasterization, and intra-threadblock reductions - Batched GEMM operations - Complex-valued GEMMs Note: this commit and all that follow require a host compiler supporting C++11 or greater.
236 lines
9.1 KiB
Python
236 lines
9.1 KiB
Python
#
|
|
# \file generator.py
|
|
#
|
|
# \brief Generates the CUTLASS Library's instances
|
|
#
|
|
|
|
import enum
|
|
import os.path
|
|
import shutil
|
|
import argparse
|
|
|
|
from library import *
|
|
from manifest import *
|
|
from gemm_operation import *
|
|
###################################################################################################
|
|
|
|
#
|
|
def CudaToolkitVersionSatisfies(semantic_ver_string, major, minor, patch = 0):
|
|
if semantic_ver_string == '':
|
|
cuda_version = [10, 2, 0]
|
|
else:
|
|
cuda_version = [int(x) for x in semantic_ver_string.split('.')]
|
|
|
|
return cuda_version >= [major, minor, patch]
|
|
|
|
###################################################################################################
|
|
|
|
#
|
|
def GenerateSM50(manifest, args):
|
|
|
|
min_cc = 50
|
|
max_cc = 1024
|
|
stages = 2
|
|
|
|
# single-precision
|
|
inst = MathInstruction([1, 1, 1], DataType.f32, DataType.f32, DataType.f32, OpcodeClass.Simt)
|
|
tile_descriptions = [
|
|
TileDescription([128, 128, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 256, 8], stages, [2, 4, 1], inst, min_cc, max_cc),
|
|
TileDescription([256, 128, 8], stages, [4, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 64, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 32, 8], stages, [4, 1, 1], inst, min_cc, max_cc),
|
|
TileDescription([32, 128, 8], stages, [1, 4, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
GenerateGemmSimt(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
GenerateGemmSimt(GemmKind.Batched, manifest, tile_descriptions, min_cc)
|
|
|
|
# double precision
|
|
inst = MathInstruction([1, 1, 1], DataType.f64, DataType.f64, DataType.f64, OpcodeClass.Simt)
|
|
tile_descriptions = [
|
|
TileDescription([128, 128, 8], stages, [4, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 64, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 32, 8], stages, [4, 1, 1], inst, min_cc, max_cc),
|
|
TileDescription([32, 128, 8], stages, [1, 4, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
GenerateGemmSimt(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
GenerateGemmSimt(GemmKind.Batched, manifest, tile_descriptions, min_cc)
|
|
|
|
###################################################################################################
|
|
|
|
#
|
|
def GenerateSM60(manifest, args):
|
|
|
|
min_cc = 60
|
|
max_cc = 1024
|
|
stages = 2
|
|
|
|
math_instructions = [
|
|
MathInstruction([1, 1, 1], DataType.f16, DataType.f16, DataType.f16, OpcodeClass.Simt),
|
|
]
|
|
|
|
tile_descriptions = []
|
|
|
|
for inst in math_instructions:
|
|
tile_descriptions += [
|
|
TileDescription([256, 256, 8], stages, [4, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 256, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 128, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, 8], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([32, 128, 8], stages, [1, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 32, 8], stages, [2, 1, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
GenerateGemmSimt(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
|
|
###################################################################################################
|
|
|
|
#
|
|
def GenerateSM61(manifest, args):
|
|
|
|
min_cc = 61
|
|
max_cc = 1024
|
|
stages = 2
|
|
|
|
math_instructions = [
|
|
MathInstruction([1, 1, 4], DataType.s8, DataType.s8, DataType.s32, OpcodeClass.Simt),
|
|
]
|
|
|
|
tile_descriptions = []
|
|
|
|
for inst in math_instructions:
|
|
tile_descriptions += [
|
|
TileDescription([128, 256, 32], stages, [2, 4, 1], inst, min_cc, max_cc),
|
|
TileDescription([256, 128, 32], stages, [4, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 128, 32], stages, [2, 4, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, 32], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 64, 32], stages, [4, 1, 1], inst, min_cc, max_cc),
|
|
TileDescription([32, 128, 32], stages, [1, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 32, 32], stages, [2, 1, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
GenerateGemmSimt(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
|
|
###################################################################################################
|
|
|
|
#
|
|
def GenerateSM70(manifest, args):
|
|
|
|
min_cc = 70
|
|
max_cc = 75
|
|
stages = 2
|
|
k_groups = 8
|
|
|
|
math_instructions = [
|
|
MathInstruction([8, 8, 4], DataType.f16, DataType.f16, DataType.f16, OpcodeClass.TensorOp),
|
|
MathInstruction([8, 8, 4], DataType.f16, DataType.f16, DataType.f32, OpcodeClass.TensorOp),
|
|
]
|
|
|
|
tile_descriptions = []
|
|
|
|
for inst in math_instructions:
|
|
kblock = k_groups * inst.instruction_shape[2]
|
|
tile_descriptions += [
|
|
TileDescription([256, 128, kblock], stages, [4, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 256, kblock], stages, [2, 4, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 128, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 64, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 64, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
if CudaToolkitVersionSatisfies(args.cuda_version, 10, 1):
|
|
GenerateGemmTensorOp(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
GenerateGemmTensorOp(GemmKind.Batched, manifest, tile_descriptions, min_cc)
|
|
|
|
# wmma tensor op SM70 Gemm kernels
|
|
stages = 2
|
|
k_groups = 2
|
|
|
|
math_instructions = [
|
|
MathInstruction([16, 16, 16], DataType.f16, DataType.f16, DataType.f16, OpcodeClass.WmmaTensorOp),
|
|
MathInstruction([16, 16, 16], DataType.f16, DataType.f16, DataType.f32, OpcodeClass.WmmaTensorOp),
|
|
]
|
|
|
|
tile_descriptions = []
|
|
|
|
for inst in math_instructions:
|
|
kblock = k_groups * inst.instruction_shape[2]
|
|
tile_descriptions += [
|
|
TileDescription([128, 128, kblock], stages, [2, 4, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 64, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 64, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
GenerateGemmWmmaTensorOp(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
|
|
###################################################################################################
|
|
|
|
#
|
|
def GenerateSM75(manifest, args):
|
|
|
|
min_cc = 75
|
|
max_cc = 1024
|
|
stages = 2
|
|
k_groups = 4
|
|
|
|
math_instructions = [
|
|
MathInstruction([16, 8, 8], DataType.f16, DataType.f16, DataType.f16, OpcodeClass.TensorOp),
|
|
MathInstruction([16, 8, 8], DataType.f16, DataType.f16, DataType.f32, OpcodeClass.TensorOp),
|
|
MathInstruction([8, 8, 16], DataType.s8, DataType.s8, DataType.s32, OpcodeClass.TensorOp),
|
|
MathInstruction([8, 8, 32], DataType.s4, DataType.s4, DataType.s32, OpcodeClass.TensorOp)
|
|
]
|
|
|
|
tile_descriptions = []
|
|
|
|
for inst in math_instructions:
|
|
kblock = k_groups * inst.instruction_shape[2]
|
|
tile_descriptions += [
|
|
TileDescription([256, 128, kblock], stages, [4, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 256, kblock], stages, [2, 4, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 128, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 128, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([128, 64, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
TileDescription([64, 64, kblock], stages, [2, 2, 1], inst, min_cc, max_cc),
|
|
]
|
|
|
|
if CudaToolkitVersionSatisfies(args.cuda_version, 10, 2):
|
|
GenerateGemmTensorOp(GemmKind.Gemm, manifest, tile_descriptions, min_cc)
|
|
GenerateGemmTensorOp(GemmKind.Batched, manifest, tile_descriptions, min_cc)
|
|
|
|
|
|
###################################################################################################
|
|
###################################################################################################
|
|
|
|
if __name__ == "__main__":
|
|
|
|
parser = argparse.ArgumentParser(description="Generates device kernel registration code for CUTLASS Kernels")
|
|
parser.add_argument("--operations", default="gemm", help="Specifies the operation to generate (gemm, all)")
|
|
parser.add_argument("--build-dir", default=".", required=False, help="CUTLASS top-level build directory")
|
|
parser.add_argument("--curr-build-dir", default=".", help="CUTLASS current build directory. cmake files will be emitted in this directory")
|
|
parser.add_argument("--generator-target", default='library', help="Target of CUTLASS Library Generator.")
|
|
parser.add_argument("--architectures", default='50 60 61 75', help="Target compute architectures")
|
|
parser.add_argument("--kernels", default='', help='Comma delimited list to filter kernels by name.')
|
|
parser.add_argument("--cuda-version", default="10.2.0", help="Semantic version string of CUDA Toolkit")
|
|
|
|
|
|
args = parser.parse_args()
|
|
|
|
manifest = Manifest(args)
|
|
|
|
GenerateSM50(manifest, args)
|
|
GenerateSM60(manifest, args)
|
|
GenerateSM61(manifest, args)
|
|
GenerateSM70(manifest, args)
|
|
GenerateSM75(manifest, args)
|
|
if 'library' in args.generator_target.split(','):
|
|
manifest.emit(GeneratorTarget.Library)
|
|
|
|
#
|
|
###################################################################################################
|