cutlass/tools/library/scripts/library.py
Manish Gupta 6615010cd0
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>
2020-11-19 21:25:25 -08:00

538 lines
15 KiB
Python

#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import re
###################################################################################################
import enum
# The following block implements enum.auto() for Python 3.5 variants that don't include it such
# as the default 3.5.2 on Ubuntu 16.04.
#
# https://codereview.stackexchange.com/questions/177309/reimplementing-pythons-enum-auto-for-compatibility
try:
from enum import auto as enum_auto
except ImportError:
__cutlass_library_auto_enum = 0
def enum_auto() -> int:
global __cutlass_library_auto_enum
i = __cutlass_library_auto_enum
__cutlass_library_auto_enum += 1
return i
###################################################################################################
#
class GeneratorTarget(enum.Enum):
Library = enum_auto()
#
GeneratorTargetNames = {
GeneratorTarget.Library: 'library'
}
#
###################################################################################################
#
class DataType(enum.Enum):
b1 = enum_auto()
u4 = enum_auto()
u8 = enum_auto()
u16 = enum_auto()
u32 = enum_auto()
u64 = enum_auto()
s4 = enum_auto()
s8 = enum_auto()
s16 = enum_auto()
s32 = enum_auto()
s64 = enum_auto()
f16 = enum_auto()
bf16 = enum_auto()
f32 = enum_auto()
tf32 = enum_auto()
f64 = enum_auto()
cf16 = enum_auto()
cbf16 = enum_auto()
cf32 = enum_auto()
ctf32 = enum_auto()
cf64 = enum_auto()
cs4 = enum_auto()
cs8 = enum_auto()
cs16 = enum_auto()
cs32 = enum_auto()
cs64 = enum_auto()
cu4 = enum_auto()
cu8 = enum_auto()
cu16 = enum_auto()
cu32 = enum_auto()
cu64 = enum_auto()
invalid = enum_auto()
#
ShortDataTypeNames = {
DataType.s32: 'i',
DataType.f16: 'h',
DataType.f32: 's',
DataType.f64: 'd',
DataType.cf32: 'c',
DataType.cf64: 'z',
}
#
DataTypeNames = {
DataType.b1: "b1",
DataType.u4: "u4",
DataType.u8: "u8",
DataType.u16: "u16",
DataType.u32: "u32",
DataType.u64: "u64",
DataType.s4: "s4",
DataType.s8: "s8",
DataType.s16: "s16",
DataType.s32: "s32",
DataType.s64: "s64",
DataType.f16: "f16",
DataType.bf16: "bf16",
DataType.f32: "f32",
DataType.tf32: "tf32",
DataType.f64: "f64",
DataType.cf16: "cf16",
DataType.cbf16: "cbf16",
DataType.cf32: "cf32",
DataType.ctf32: "ctf32",
DataType.cf64: "cf64",
DataType.cu4: "cu4",
DataType.cu8: "cu8",
DataType.cu16: "cu16",
DataType.cu32: "cu32",
DataType.cu64: "cu64",
DataType.cs4: "cs4",
DataType.cs8: "cs8",
DataType.cs16: "cs16",
DataType.cs32: "cs32",
DataType.cs64: "cs64",
}
DataTypeTag = {
DataType.b1: "cutlass::uint1b_t",
DataType.u4: "cutlass::uint4b_t",
DataType.u8: "uint8_t",
DataType.u16: "uint16_t",
DataType.u32: "uint32_t",
DataType.u64: "uint64_t",
DataType.s4: "cutlass::int4b_t",
DataType.s8: "int8_t",
DataType.s16: "int16_t",
DataType.s32: "int32_t",
DataType.s64: "int64_t",
DataType.f16: "cutlass::half_t",
DataType.bf16: "cutlass::bfloat16_t",
DataType.f32: "float",
DataType.tf32: "cutlass::tfloat32_t",
DataType.f64: "double",
DataType.cf16: "cutlass::complex<cutlass::half_t>",
DataType.cbf16: "cutlass::complex<cutlass::bfloat16_t>",
DataType.cf32: "cutlass::complex<float>",
DataType.ctf32: "cutlass::complex<cutlass::tfloat32_t>",
DataType.cf64: "cutlass::complex<double>",
DataType.cu4: "cutlass::complex<cutlass::uint4b_t>",
DataType.cu8: "cutlass::complex<cutlass::uint8_t>",
DataType.cu16: "cutlass::complex<cutlass::uint16_t>",
DataType.cu32: "cutlass::complex<cutlass::uint32_t>",
DataType.cu64: "cutlass::complex<cutlass::uint64_t>",
DataType.cs4: "cutlass::complex<cutlass::int4b_t>",
DataType.cs8: "cutlass::complex<cutlass::int8_t>",
DataType.cs16: "cutlass::complex<cutlass::int16_t>",
DataType.cs32: "cutlass::complex<cutlass::int32_t>",
DataType.cs64: "cutlass::complex<cutlass::int64_t>",
}
DataTypeSize = {
DataType.b1: 1,
DataType.u4: 4,
DataType.u8: 4,
DataType.u16: 16,
DataType.u32: 32,
DataType.u64: 64,
DataType.s4: 4,
DataType.s8: 8,
DataType.s16: 16,
DataType.s32: 32,
DataType.s64: 64,
DataType.f16: 16,
DataType.bf16: 16,
DataType.f32: 32,
DataType.tf32: 32,
DataType.f64: 64,
DataType.cf16: 32,
DataType.cbf16: 32,
DataType.cf32: 64,
DataType.ctf32: 32,
DataType.cf64: 128,
DataType.cu4: 8,
DataType.cu8: 16,
DataType.cu16: 32,
DataType.cu32: 64,
DataType.cu64: 128,
DataType.cs4: 8,
DataType.cs8: 16,
DataType.cs16: 32,
DataType.cs32: 64,
DataType.cs64: 128,
}
###################################################################################################
#
class ComplexTransform(enum.Enum):
none = enum_auto()
conj = enum_auto()
#
ComplexTransformTag = {
ComplexTransform.none: 'cutlass::ComplexTransform::kNone',
ComplexTransform.conj: 'cutlass::ComplexTransform::kConjugate',
}
#
RealComplexBijection = [
(DataType.f16, DataType.cf16),
(DataType.f32, DataType.cf32),
(DataType.f64, DataType.cf64),
]
#
def is_complex(data_type):
for r, c in RealComplexBijection:
if data_type == c:
return True
return False
#
def get_complex_from_real(real_type):
for r, c in RealComplexBijection:
if real_type == r:
return c
return DataType.invalid
#
def get_real_from_complex(complex_type):
for r, c in RealComplexBijection:
if complex_type == c:
return r
return DataType.invalid
#
class ComplexMultiplyOp(enum.Enum):
multiply_add = enum_auto()
gaussian = enum_auto()
###################################################################################################
#
class MathOperation(enum.Enum):
multiply_add = enum_auto()
multiply_add_saturate = enum_auto()
xor_popc = enum_auto()
multiply_add_fast_bf16 = enum_auto()
multiply_add_fast_f16 = enum_auto()
multiply_add_complex = enum_auto()
multiply_add_complex_gaussian = enum_auto()
#
MathOperationTag = {
MathOperation.multiply_add: 'cutlass::arch::OpMultiplyAdd',
MathOperation.multiply_add_saturate: 'cutlass::arch::OpMultiplyAddSaturate',
MathOperation.xor_popc: 'cutlass::arch::OpXorPopc',
MathOperation.multiply_add_fast_bf16: 'cutlass::arch::OpMultiplyAddFastBF16',
MathOperation.multiply_add_fast_f16: 'cutlass::arch::OpMultiplyAddFastF16',
MathOperation.multiply_add_complex: 'cutlass::arch::OpMultiplyAddComplex',
MathOperation.multiply_add_complex_gaussian: 'cutlass::arch::OpMultiplyAddGaussianComplex',
}
###################################################################################################
#
class LayoutType(enum.Enum):
ColumnMajor = enum_auto()
RowMajor = enum_auto()
ColumnMajorInterleaved2 = enum_auto()
RowMajorInterleaved2 = enum_auto()
ColumnMajorInterleaved32 = enum_auto()
RowMajorInterleaved32 = enum_auto()
ColumnMajorInterleaved64 = enum_auto()
RowMajorInterleaved64 = enum_auto()
TensorNHWC = enum_auto()
TensorNDHWC = enum_auto()
TensorNCHW = enum_auto()
TensorNGHWC = enum_auto()
TensorNC32HW32 = enum_auto()
TensorNC64HW64 = enum_auto()
TensorC32RSK32 = enum_auto()
TensorC64RSK64 = enum_auto()
#
LayoutTag = {
LayoutType.ColumnMajor: 'cutlass::layout::ColumnMajor',
LayoutType.RowMajor: 'cutlass::layout::RowMajor',
LayoutType.ColumnMajorInterleaved2: 'cutlass::layout::ColumnMajorInterleaved<2>',
LayoutType.RowMajorInterleaved2: 'cutlass::layout::RowMajorInterleaved<2>',
LayoutType.ColumnMajorInterleaved32: 'cutlass::layout::ColumnMajorInterleaved<32>',
LayoutType.RowMajorInterleaved32: 'cutlass::layout::RowMajorInterleaved<32>',
LayoutType.ColumnMajorInterleaved64: 'cutlass::layout::ColumnMajorInterleaved<64>',
LayoutType.RowMajorInterleaved64: 'cutlass::layout::RowMajorInterleaved<64>',
LayoutType.TensorNHWC: 'cutlass::layout::TensorNHWC',
LayoutType.TensorNDHWC: 'cutlass::layout::TensorNDHWC',
LayoutType.TensorNCHW: 'cutlass::layout::TensorNCHW',
LayoutType.TensorNGHWC: 'cutlass::layout::TensorNGHWC',
LayoutType.TensorNC32HW32: 'cutlass::layout::TensorNCxHWx<32>',
LayoutType.TensorC32RSK32: 'cutlass::layout::TensorCxRSKx<32>',
LayoutType.TensorNC64HW64: 'cutlass::layout::TensorNCxHWx<64>',
LayoutType.TensorC64RSK64: 'cutlass::layout::TensorCxRSKx<64>',
}
#
TransposedLayout = {
LayoutType.ColumnMajor: LayoutType.RowMajor,
LayoutType.RowMajor: LayoutType.ColumnMajor,
LayoutType.ColumnMajorInterleaved2: LayoutType.RowMajorInterleaved2,
LayoutType.RowMajorInterleaved2: LayoutType.ColumnMajorInterleaved2,
LayoutType.ColumnMajorInterleaved32: LayoutType.RowMajorInterleaved32,
LayoutType.RowMajorInterleaved32: LayoutType.ColumnMajorInterleaved32,
LayoutType.ColumnMajorInterleaved64: LayoutType.RowMajorInterleaved64,
LayoutType.RowMajorInterleaved64: LayoutType.ColumnMajorInterleaved64,
LayoutType.TensorNHWC: LayoutType.TensorNHWC
}
#
ShortLayoutTypeNames = {
LayoutType.ColumnMajor: 'n',
LayoutType.ColumnMajorInterleaved32: 'n2',
LayoutType.ColumnMajorInterleaved32: 'n32',
LayoutType.ColumnMajorInterleaved64: 'n64',
LayoutType.RowMajor: 't',
LayoutType.RowMajorInterleaved2: 't2',
LayoutType.RowMajorInterleaved32: 't32',
LayoutType.RowMajorInterleaved64: 't64',
LayoutType.TensorNHWC: 'nhwc',
LayoutType.TensorNDHWC: 'ndhwc',
LayoutType.TensorNCHW: 'nchw',
LayoutType.TensorNGHWC: 'nghwc',
LayoutType.TensorNC32HW32: 'nc32hw32',
LayoutType.TensorNC64HW64: 'nc64hw64',
LayoutType.TensorC32RSK32: 'c32rsk32',
LayoutType.TensorC64RSK64: 'c64rsk64'
}
#
ShortComplexLayoutNames = {
(LayoutType.ColumnMajor, ComplexTransform.none): 'n',
(LayoutType.ColumnMajor, ComplexTransform.conj): 'c',
(LayoutType.RowMajor, ComplexTransform.none): 't',
(LayoutType.RowMajor, ComplexTransform.conj): 'h'
}
###################################################################################################
#
class OpcodeClass(enum.Enum):
Simt = enum_auto()
TensorOp = enum_auto()
WmmaTensorOp = enum_auto()
OpcodeClassNames = {
OpcodeClass.Simt: 'simt',
OpcodeClass.TensorOp: 'tensorop',
OpcodeClass.WmmaTensorOp: 'wmma_tensorop',
}
OpcodeClassTag = {
OpcodeClass.Simt: 'cutlass::arch::OpClassSimt',
OpcodeClass.TensorOp: 'cutlass::arch::OpClassTensorOp',
OpcodeClass.WmmaTensorOp: 'cutlass::arch::OpClassWmmaTensorOp',
}
###################################################################################################
#
class OperationKind(enum.Enum):
Gemm = enum_auto()
Conv2d = enum_auto()
Conv3d = enum_auto()
#
OperationKindNames = {
OperationKind.Gemm: 'gemm'
, OperationKind.Conv2d: 'conv2d'
, OperationKind.Conv3d: 'conv3d'
}
#
class Target(enum.Enum):
library = enum_auto()
ArchitectureNames = {
50: 'maxwell',
60: 'pascal',
61: 'pascal',
70: 'volta',
75: 'turing',
80: 'ampere',
}
###################################################################################################
#
def SubstituteTemplate(template, values):
text = template
changed = True
while changed:
changed = False
for key, value in values.items():
regex = "\\$\\{%s\\}" % key
newtext = re.sub(regex, value, text)
if newtext != text:
changed = True
text = newtext
return text
###################################################################################################
#
class GemmKind(enum.Enum):
Gemm = enum_auto()
Sparse = enum_auto()
Universal = enum_auto()
PlanarComplex = enum_auto()
PlanarComplexArray = enum_auto()
#
GemmKindNames = {
GemmKind.Gemm: "gemm",
GemmKind.Sparse: "spgemm",
GemmKind.Universal: "gemm",
GemmKind.PlanarComplex: "gemm_planar_complex",
GemmKind.PlanarComplexArray: "gemm_planar_complex_array",
}
#
class EpilogueFunctor(enum.Enum):
LinearCombination = enum_auto()
LinearCombinationClamp = enum_auto()
#
EpilogueFunctorTag = {
EpilogueFunctor.LinearCombination: 'cutlass::epilogue::thread::LinearCombination',
EpilogueFunctor.LinearCombinationClamp: 'cutlass::epilogue::thread::LinearCombinationClamp',
}
#
class SwizzlingFunctor(enum.Enum):
Identity1 = enum_auto()
Identity2 = enum_auto()
Identity4 = enum_auto()
Identity8 = enum_auto()
#
SwizzlingFunctorTag = {
SwizzlingFunctor.Identity1: 'cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<1>',
SwizzlingFunctor.Identity2: 'cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<2>',
SwizzlingFunctor.Identity4: 'cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<4>',
SwizzlingFunctor.Identity8: 'cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<8>',
}
###################################################################################################
#
class ConvKind(enum.Enum):
Fprop = enum_auto()
Dgrad = enum_auto()
Wgrad = enum_auto()
#
ConvKindTag = {
ConvKind.Fprop: 'cutlass::conv::Operator::kFprop',
ConvKind.Dgrad: 'cutlass::conv::Operator::kDgrad',
ConvKind.Wgrad: 'cutlass::conv::Operator::kWgrad'
}
ConvKindNames = {
ConvKind.Fprop: 'fprop',
ConvKind.Dgrad: 'dgrad',
ConvKind.Wgrad: 'wgrad',
}
#
class IteratorAlgorithm(enum.Enum):
Analytic = enum_auto()
Optimized = enum_auto()
#
IteratorAlgorithmTag = {
IteratorAlgorithm.Analytic: 'cutlass::conv::IteratorAlgorithm::kAnalytic',
IteratorAlgorithm.Optimized: 'cutlass::conv::IteratorAlgorithm::kOptimized',
}
IteratorAlgorithmNames = {
IteratorAlgorithm.Analytic: 'analytic',
IteratorAlgorithm.Optimized: 'optimized',
}
#
class StrideSupport(enum.Enum):
Strided = enum_auto()
Unity = enum_auto()
#
StrideSupportTag = {
StrideSupport.Strided: 'cutlass::conv::StrideSupport::kStrided',
StrideSupport.Unity: 'cutlass::conv::StrideSupport::kUnity',
}
StrideSupportNames = {
StrideSupport.Strided: '',
StrideSupport.Unity: 'unity_stride',
}
###################################################################################################
#
class MathInstruction:
def __init__(self, instruction_shape, element_a, element_b, element_accumulator, opcode_class, math_operation = MathOperation.multiply_add):
self.instruction_shape = instruction_shape
self.element_a = element_a
self.element_b = element_b
self.element_accumulator = element_accumulator
self.opcode_class = opcode_class
self.math_operation = math_operation
#
class TileDescription:
def __init__(self, threadblock_shape, stages, warp_count, math_instruction, min_compute, max_compute):
self.threadblock_shape = threadblock_shape
self.stages = stages
self.warp_count = warp_count
self.math_instruction = math_instruction
self.minimum_compute_capability = min_compute
self.maximum_compute_capability = max_compute
def procedural_name(self):
return "%dx%d_%dx%d" % (self.threadblock_shape[0], self.threadblock_shape[1], self.threadblock_shape[2], self.stages)
#
class TensorDescription:
def __init__(self, element, layout, alignment = 1, complex_transform = ComplexTransform.none):
self.element = element
self.layout = layout
self.alignment = alignment
self.complex_transform = complex_transform
###################################################################################################