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gemm_operation.py
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#################################################################################################
#
# Copyright (c) 2017 - 2024 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.
#
#################################################################################################
"""
Utilities for emitting GEMM kernels
"""
import collections
import enum
import functools
import logging
import operator
import os.path
import shutil
try:
import builtins
if hasattr(builtins, "CUTLASS_IGNORE_PACKAGE") and CUTLASS_IGNORE_PACKAGE == True:
raise ImportError("Disabling attempt to import cutlass_library")
from cutlass_library.library import *
except ImportError:
from library import *
_LOGGER = logging.getLogger(__name__)
###################################################################################################
#
# Data structure modeling a GEMM operation
#
###################################################################################################
#
class GemmOperation:
#
def __init__(self, gemm_kind, arch, tile_description, A, B, C, element_epilogue, \
epilogue_functor = EpilogueFunctor.LinearCombination, swizzling_functor = SwizzlingFunctor.Identity8, D = None,
kernel_schedule = KernelScheduleType.ScheduleAuto, epilogue_schedule = EpilogueScheduleType.ScheduleAuto,
tile_scheduler = TileSchedulerType.Default
):
kinds_3x = {
GemmKind.Universal3x,
GemmKind.SparseUniversal3x,
}
self.is_3x = gemm_kind in kinds_3x
self.prefix = "3x" if self.is_3x else ""
self.operation_kind = OperationKind.Gemm
self.arch = arch
self.tile_description = tile_description
self.gemm_kind = gemm_kind
self.A = A
self.B = B
self.C = C
self.D = D
if self.D == None:
self.D = self.C
if not self.is_3x:
assert(kernel_schedule == KernelScheduleType.ScheduleAuto)
assert(epilogue_schedule == EpilogueScheduleType.ScheduleAuto)
self.kernel_schedule = kernel_schedule
self.epilogue_schedule = epilogue_schedule
self.element_epilogue = element_epilogue
self.epilogue_functor = epilogue_functor
if self.is_3x and epilogue_functor == EpilogueFunctor.LinearCombination:
self.epilogue_functor = EpilogueFunctor3x.LinearCombination
self.swizzling_functor = swizzling_functor
self.tile_scheduler = tile_scheduler
#
def is_complex(self):
complex_operators = [
MathOperation.multiply_add_complex,
MathOperation.multiply_add_complex_gaussian,
MathOperation.multiply_add_complex_fast_f32
]
return self.tile_description.math_instruction.math_operation in complex_operators
#
def is_mixed_input(self):
return self.A.element != self.B.element
#
def is_planar_complex(self):
return self.gemm_kind in (GemmKind.PlanarComplex, GemmKind.PlanarComplexArray)
#
def accumulator_type(self):
accum = self.tile_description.math_instruction.element_accumulator
if self.is_complex():
return get_complex_from_real(accum)
return accum
#
def short_math_name(self):
if self.tile_description.math_instruction.math_operation == MathOperation.multiply_add_complex_gaussian:
return "g%s" % ShortDataTypeNames[self.accumulator_type()]
return ShortDataTypeNames[self.accumulator_type()]
#
def core_name(self):
''' The basic operation kind is prefixed with a letter indicating the accumulation type. '''
inst_shape = ''
inst_operation = ''
intermediate_type = ''
math_operations_map = {
MathOperation.xor_popc: 'xor',
MathOperation.and_popc: 'and',
MathOperation.multiply_add_fast_accum: 'fastaccum',
}
tensor_ops = [
OpcodeClass.TensorOp,
OpcodeClass.WmmaTensorOp,
OpcodeClass.SparseTensorOp,
]
is_tensor_op = self.tile_description.math_instruction.opcode_class in tensor_ops
if is_tensor_op:
math_op = self.tile_description.math_instruction.math_operation
math_op_string = math_operations_map[math_op] if math_op in math_operations_map.keys() else ''
if self.is_3x:
inst_shape = "{0}x{1}x{2}".format(*tuple(self.tile_description.math_instruction.instruction_shape))
else:
inst_shape = "{0}{1}{2}".format(*tuple(self.tile_description.math_instruction.instruction_shape))
inst_shape += math_op_string
if self.tile_description.math_instruction.element_a != self.A.element and \
self.tile_description.math_instruction.element_a != self.tile_description.math_instruction.element_accumulator:
intermediate_type = DataTypeNames[self.tile_description.math_instruction.element_a]
return "%s%s%s%s" % (self.short_math_name(), inst_shape, intermediate_type, GemmKindNames[self.gemm_kind])
# Generates a string representing the MMA instruction.
def extended_name(self):
''' Append data types if they differ from compute type. '''
if self.is_complex():
extended_name = "${core_name}"
else:
if self.is_mixed_input():
extended_name = "${core_name}_${element_a}_${element_b}"
if self.C.element != self.tile_description.math_instruction.element_accumulator:
extended_name = "${element_c}_" + extended_name
else:
extended_name = "${core_name}"
if self.C.element != self.tile_description.math_instruction.element_accumulator:
extended_name = "${element_c}_" + extended_name
if self.A.element != self.tile_description.math_instruction.element_accumulator:
extended_name += "_${element_a}"
extended_name = SubstituteTemplate(extended_name, {
'element_a': DataTypeNames[self.A.element],
'element_b': DataTypeNames[self.B.element],
'element_c': DataTypeNames[self.C.element],
'core_name': self.core_name()
})
return extended_name
def extended_name_3x(self):
'''Generates a string representing the MMA atom. Assumes accumulator type is C type.'''
extended_name = "{core_name}_{element_a}_{element_b}_{element_acc}_{element_c}_{element_d}".format(
element_a = DataTypeNames[self.A.element],
element_b = DataTypeNames[self.B.element],
element_acc = DataTypeNames[self.accumulator_type()],
element_c = DataTypeNames[self.C.element],
element_d = DataTypeNames[self.D.element],
core_name = self.core_name())
return extended_name
def datatype_name_3x(self):
'''Generates a string representing the MMA atom. Assumes accumulator type is C type.'''
datatype_name = "{element_a}_{element_b}_{element_acc}_{element_c}_{element_d}".format(
element_a = DataTypeNames[self.A.element],
element_b = DataTypeNames[self.B.element],
element_acc = DataTypeNames[self.accumulator_type()],
element_c = DataTypeNames[self.C.element],
element_d = DataTypeNames[self.D.element])
return datatype_name
# Generates a short string representing the AB layout tags (e.g. nt or tn)
def layout_name(self):
if self.is_complex() or self.is_planar_complex():
return "%s%s" % (
ShortComplexLayoutNames[(self.A.layout, self.A.complex_transform)],
ShortComplexLayoutNames[(self.B.layout, self.B.complex_transform)]
)
return "%s%s" % (ShortLayoutTypeNames[self.A.layout], ShortLayoutTypeNames[self.B.layout])
# Generates a short string representing the ABC layout tags (e.g. ntn or tnn)
def layout_name_3x(self):
if self.is_complex() or self.is_planar_complex():
return "{}{}{}".format(
ShortComplexLayoutNames[(self.A.layout, self.A.complex_transform)],
ShortComplexLayoutNames[(self.B.layout, self.B.complex_transform)],
ShortComplexLayoutNames[(self.C.layout, self.C.complex_transform)])
else:
return "{}{}{}".format(
ShortLayoutTypeNames[self.A.layout],
ShortLayoutTypeNames[self.B.layout],
ShortLayoutTypeNames[self.C.layout])
# Generates a short string representing underlying kernel schedule type
def kernel_schedule_name_3x(self):
return KernelScheduleSuffixes[self.kernel_schedule]
# Generates a short string representing underlying epilogue schedule type
def epilogue_schedule_name_3x(self):
return EpilogueScheduleSuffixes[self.epilogue_schedule]
# Generate a short string representing the operation class
def opcode_class_name(self):
return OpcodeClassNames[self.tile_description.math_instruction.opcode_class]
# Generates the full kernel function name
def procedural_name(self):
''' The full procedural name indicates architecture, extended name, tile size, and layout. '''
opcode_class_name = OpcodeClassNames[self.tile_description.math_instruction.opcode_class]
if self.arch >= 90:
kernel_name_template = "cutlass{p}_sm{ar}_{op}_{ex}{ct}{cs}_{l}_{s}_align{al}{t}{k}{e}"
return kernel_name_template.format(
p = self.prefix,
ar = self.arch,
op = opcode_class_name,
ex = self.extended_name_3x(),
ct = '_' + 'x'.join([str(i) for i in self.tile_description.tile_shape]) if self.tile_description.tile_shape[0] > 0 else "",
cs = '_' + 'x'.join([str(i) for i in self.tile_description.cluster_shape]),
l = self.tile_description.stages,
s = self.layout_name_3x(),
al = str(max(self.A.alignment, self.B.alignment)),
t = TileSchedulerSuffixes[self.tile_scheduler],
k = self.kernel_schedule_name_3x(),
e = self.epilogue_schedule_name_3x())
else:
threadblock = self.tile_description.procedural_name()
return "cutlass{p}_{op}_{ex}_{tb}_{l}_align{a}".format(
p = self.prefix,
op = opcode_class_name,
ex = self.extended_name(),
tb = threadblock,
l = self.layout_name(),
a = str(max(self.A.alignment, self.B.alignment)))
#
def configuration_name(self):
''' The full procedural name indicates architecture, extended name, tile size, and layout. '''
return self.procedural_name()
def __hash__(self):
return hash(self.configuration_name())
def __eq__(self, other):
return self.configuration_name() == other.configuration_name()
###################################################################################################
#
# Data structure modeling a grouped GEMM operation
#
###################################################################################################
#
class GroupedGemmOperation(GemmOperation):
#
def __init__(self, gemm_kind, arch, tile_description, A, B, C, element_epilogue, \
epilogue_functor = EpilogueFunctor.LinearCombination, swizzling_functor = SwizzlingFunctor.Identity8, \
scheduler_mode = GroupScheduleMode.Device):
super().__init__(gemm_kind, arch, tile_description, A, B, C, element_epilogue, \
epilogue_functor, swizzling_functor)
self.scheduler_mode = scheduler_mode
#
def procedural_name(self):
''' The full procedural name indicates architecture, extended name, tile size, and layout. '''
base = super().procedural_name()
return SubstituteTemplate(
base + "_schedule${schedule}",
{
'schedule': ShortGroupScheduleModeNames[self.scheduler_mode]
})
###################################################################################################
#
# Emits single instances of a CUTLASS device-wide operator
#
###################################################################################################
#
class EmitGemmInstance:
''' Responsible for emitting a CUTLASS template definition'''
def __init__(self, operation_suffix = ''):
self.operation_suffix = operation_suffix
self.includes = []
self.gemm_template = """
// Gemm operator ${operation_name}
using Operation_${operation_name} = cutlass::gemm::device::Gemm<
${element_a}, ${layout_a},
${element_b}, ${layout_b},
${element_c}, ${layout_c},
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
${epilogue_functor}<
${element_c},
${epilogue_vector_length},
${element_accumulator},
${element_epilogue}
>,
${swizzling_functor},
${stages},
${align_a},
${align_b},
false,
${math_operation}
${residual}
>;
"""
self.gemm_complex_template = """
// Gemm operator ${operation_name}
using Operation_${operation_name} = cutlass::gemm::device::GemmComplex<
${element_a}, ${layout_a},
${element_b}, ${layout_b},
${element_c}, ${layout_c},
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
${epilogue_functor}<
${element_c},
${epilogue_vector_length},
${element_accumulator},
${element_epilogue}
>,
${swizzling_functor},
${stages},
${transform_a},
${transform_b},
${math_operation}
${residual}
>;
"""
#
def instance_template(self):
return """
${compile_guard_start}
manifest.append(new ${gemm_kind}<Operation_${operation_name}>("${operation_name}"));
${compile_guard_end}
"""
#
def emit(self, operation):
warp_shape = [operation.tile_description.threadblock_shape[idx] // operation.tile_description.warp_count[idx] for idx in range(3)]
epilogue_vector_length = int(min(operation.C.alignment * DataTypeSize[operation.C.element], 128) / DataTypeSize[operation.C.element])
residual = ''
values = {
'operation_name': operation.procedural_name(),
'element_a': DataTypeTag[operation.A.element],
'layout_a': LayoutTag[operation.A.layout],
'element_b': DataTypeTag[operation.B.element],
'layout_b': LayoutTag[operation.B.layout],
'element_c': DataTypeTag[operation.C.element],
'layout_c': LayoutTag[operation.C.layout],
'element_accumulator': DataTypeTag[operation.accumulator_type()],
'opcode_class': OpcodeClassTag[operation.tile_description.math_instruction.opcode_class],
'arch': "cutlass::arch::Sm%d" % operation.arch,
'threadblock_shape_m': str(operation.tile_description.threadblock_shape[0]),
'threadblock_shape_n': str(operation.tile_description.threadblock_shape[1]),
'threadblock_shape_k': str(operation.tile_description.threadblock_shape[2]),
'warp_shape_m': str(warp_shape[0]),
'warp_shape_n': str(warp_shape[1]),
'warp_shape_k': str(warp_shape[2]),
'instruction_shape_m': str(operation.tile_description.math_instruction.instruction_shape[0]),
'instruction_shape_n': str(operation.tile_description.math_instruction.instruction_shape[1]),
'instruction_shape_k': str(operation.tile_description.math_instruction.instruction_shape[2]),
'epilogue_vector_length': str(epilogue_vector_length),
'element_epilogue': str(DataTypeTag[operation.element_epilogue]),
'epilogue_functor': EpilogueFunctorTag[operation.epilogue_functor],
'swizzling_functor': SwizzlingFunctorTag[operation.swizzling_functor],
'stages': str(operation.tile_description.stages),
'align_a': str(operation.A.alignment),
'align_b': str(operation.B.alignment),
'transform_a': ComplexTransformTag[operation.A.complex_transform],
'transform_b': ComplexTransformTag[operation.B.complex_transform],
'math_operation': MathOperationTag[operation.tile_description.math_instruction.math_operation],
'residual': residual
}
template = self.gemm_complex_template if operation.is_complex() else self.gemm_template
return SubstituteTemplate(template, values)
###################################################################################################
class EmitSparseGemmInstance:
''' Responsible for emitting a CUTLASS template definition'''
def __init__(self, operation_suffix = ''):
self.operation_suffix = operation_suffix
self.includes = []
self.gemm_template = """
// Gemm operator ${operation_name}
using Operation_${operation_name} = cutlass::gemm::device::SparseGemm<
${element_a}, ${layout_a},
${element_b}, ${layout_b},
${element_c}, ${layout_c},
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
${epilogue_functor}<
${element_c},
${epilogue_vector_length},
${element_accumulator},
${element_epilogue}
>,
${swizzling_functor},
${stages},
${align_a},
${align_b},
false,
${math_operation}
${residual}
>;
"""
#
def instance_template(self):
return """
${compile_guard_start}
manifest.append(new ${gemm_kind}<Operation_${operation_name}>("${operation_name}"));
${compile_guard_end}
"""
#
def emit(self, operation):
warp_shape = [operation.tile_description.threadblock_shape[idx] // operation.tile_description.warp_count[idx] for idx in range(3)]
epilogue_vector_length = int(min(operation.C.alignment * DataTypeSize[operation.C.element], 128) / DataTypeSize[operation.C.element])
residual = ''
values = {
'operation_name': operation.procedural_name(),
'element_a': DataTypeTag[operation.A.element],
'layout_a': LayoutTag[operation.A.layout],
'element_b': DataTypeTag[operation.B.element],
'layout_b': LayoutTag[operation.B.layout],
'element_c': DataTypeTag[operation.C.element],
'layout_c': LayoutTag[operation.C.layout],
'element_accumulator': DataTypeTag[operation.accumulator_type()],
'opcode_class': OpcodeClassTag[operation.tile_description.math_instruction.opcode_class],
'arch': "cutlass::arch::Sm%d" % operation.arch,
'threadblock_shape_m': str(operation.tile_description.threadblock_shape[0]),
'threadblock_shape_n': str(operation.tile_description.threadblock_shape[1]),
'threadblock_shape_k': str(operation.tile_description.threadblock_shape[2]),
'warp_shape_m': str(warp_shape[0]),
'warp_shape_n': str(warp_shape[1]),
'warp_shape_k': str(warp_shape[2]),
'instruction_shape_m': str(operation.tile_description.math_instruction.instruction_shape[0]),
'instruction_shape_n': str(operation.tile_description.math_instruction.instruction_shape[1]),
'instruction_shape_k': str(operation.tile_description.math_instruction.instruction_shape[2]),
'epilogue_vector_length': str(epilogue_vector_length),
'element_epilogue': str(DataTypeTag[operation.element_epilogue]),
'epilogue_functor': EpilogueFunctorTag[operation.epilogue_functor],
'swizzling_functor': SwizzlingFunctorTag[operation.swizzling_functor],
'stages': str(operation.tile_description.stages),
'align_a': str(operation.A.alignment),
'align_b': str(operation.B.alignment),
'transform_a': ComplexTransformTag[operation.A.complex_transform],
'transform_b': ComplexTransformTag[operation.B.complex_transform],
'math_operation': MathOperationTag[operation.tile_description.math_instruction.math_operation],
'residual': residual
}
template = self.gemm_template
return SubstituteTemplate(template, values)
###################################################################################################
#
class EmitGemmUniversalInstance:
''' Responsible for emitting a CUTLASS template definition'''
def __init__(self, operation_suffix = ''):
self.operation_suffix = operation_suffix
self.includes = [
"cutlass/cutlass.h",
"cutlass/numeric_types.h",
"cutlass/arch/arch.h",
"cutlass/arch/mma.h",
"cutlass/layout/matrix.h",
"cutlass/gemm/device/gemm.h",
"cutlass/gemm/device/gemm_universal_adapter.h",
"cutlass/gemm/kernel/default_gemm_universal.h",
]
self.builtin_epilogue_functor_template = """
${epilogue_functor}<
${element_c},
${epilogue_vector_length},
${element_accumulator},
${element_epilogue}
>
"""
self.gemm_template = """
// Gemm operator ${operation_name}
using ${operation_name}_base =
typename cutlass::gemm::kernel::DefaultGemmUniversal<
${element_b}, ${layout_b}, ${transform_b}, ${align_b}, // transposed B operand
${element_a}, ${layout_a}, ${transform_a}, ${align_a}, // transposed A operand
${element_c}, ${layout_c},
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
${epilogue_functor},
${swizzling_functor},
${stages},
${math_operation}
>::GemmKernel;
// Define named type
struct ${operation_name}${operation_suffix} :
public ${operation_name}_base { };
"""
self.gemm_template_interleaved = """
// Gemm operator ${operation_name}
using ${operation_name}_base =
typename cutlass::gemm::kernel::DefaultGemmUniversal<
${element_a}, ${layout_a}, ${transform_a}, ${align_a},
${element_b}, ${layout_b}, ${transform_b}, ${align_b},
${element_c}, ${layout_c},
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
${epilogue_functor},
${swizzling_functor},
${stages},
${math_operation}
>::GemmKernel;
// Define named type
struct ${operation_name}${operation_suffix} :
public ${operation_name}_base { };
"""
#
def instance_template(self):
return """
${compile_guard_start}
manifest.append(new ${gemm_kind}<
cutlass::gemm::device::GemmUniversalAdapter<${operation_name}>
>("${operation_name}"));
${compile_guard_end}
"""
#
def emit(self, operation):
threadblock_shape = operation.tile_description.threadblock_shape
warp_count = operation.tile_description.warp_count
warp_shape = [threadblock_shape[idx] // warp_count[idx] for idx in range(3)]
transpose_layouts = {
LayoutType.ColumnMajor: LayoutType.RowMajor,
LayoutType.RowMajor: LayoutType.ColumnMajor
}
if operation.A.layout in transpose_layouts.keys() and \
operation.B.layout in transpose_layouts.keys() and \
operation.C.layout in transpose_layouts.keys():
instance_layout_A = transpose_layouts[operation.A.layout]
instance_layout_B = transpose_layouts[operation.B.layout]
instance_layout_C = transpose_layouts[operation.C.layout]
gemm_template = self.gemm_template
else:
instance_layout_A, instance_layout_B, instance_layout_C = \
(operation.A.layout, operation.B.layout, operation.C.layout)
gemm_template = self.gemm_template_interleaved
#
# Support built-in epilogue functors or user-defined functions
if isinstance(operation.epilogue_functor, enum.Enum):
epilogue_vector_length = \
min(operation.C.alignment * DataTypeSize[operation.C.element], 128) // DataTypeSize[operation.C.element]
values = {
'epilogue_vector_length': str(epilogue_vector_length),
'element_epilogue': str(DataTypeTag[operation.element_epilogue]),
'epilogue_functor': EpilogueFunctorTag[operation.epilogue_functor],
}
epilogue_functor = SubstituteTemplate(self.builtin_epilogue_functor_template, values)
else:
epilogue_functor = self.epilogue_functor.emit_declaration()
#
values = {
'operation_name': operation.procedural_name(),
'operation_suffix': self.operation_suffix,
'element_a': DataTypeTag[operation.A.element],
'layout_a': LayoutTag[instance_layout_A],
'element_b': DataTypeTag[operation.B.element],
'layout_b': LayoutTag[instance_layout_B],
'element_c': DataTypeTag[operation.C.element],
'layout_c': LayoutTag[instance_layout_C],
'element_accumulator': DataTypeTag[operation.accumulator_type()],
'opcode_class': OpcodeClassTag[operation.tile_description.math_instruction.opcode_class],
'arch': "cutlass::arch::Sm%d" % operation.arch,
'threadblock_shape_m': str(operation.tile_description.threadblock_shape[0]),
'threadblock_shape_n': str(operation.tile_description.threadblock_shape[1]),
'threadblock_shape_k': str(operation.tile_description.threadblock_shape[2]),
'warp_shape_m': str(warp_shape[0]),
'warp_shape_n': str(warp_shape[1]),
'warp_shape_k': str(warp_shape[2]),
'instruction_shape_m': str(operation.tile_description.math_instruction.instruction_shape[0]),
'instruction_shape_n': str(operation.tile_description.math_instruction.instruction_shape[1]),
'instruction_shape_k': str(operation.tile_description.math_instruction.instruction_shape[2]),
'epilogue_functor': epilogue_functor,
'swizzling_functor': SwizzlingFunctorTag[operation.swizzling_functor],
'stages': str(operation.tile_description.stages),
'align_a': str(operation.A.alignment),
'align_b': str(operation.B.alignment),
'transform_a': ComplexTransformTag[operation.A.complex_transform],
'transform_b': ComplexTransformTag[operation.B.complex_transform],
'math_operation': MathOperationTag[operation.tile_description.math_instruction.math_operation]
}
return SubstituteTemplate(gemm_template, values)
###################################################################################################
class EmitGemmUniversal3xInstance:
''' Responsible for emitting a CUTLASS 3.x template definition'''
def __init__(self, operation_suffix = ''):
self.operation_suffix = operation_suffix
self.includes = [
"cutlass/cutlass.h",
"cutlass/gemm/gemm.h",
"cutlass/numeric_types.h",
"cutlass/gemm/kernel/gemm_universal.hpp",
"cutlass/gemm/collective/collective_builder.hpp",
"cutlass/epilogue/collective/collective_builder.hpp",
]
self.builtin_epilogue_functor_template = """
${epilogue_functor}<
${element_d},
${element_epilogue},
${element_c},
${element_epilogue}
>
"""
self.gemm_template = """
using ${operation_name}_epilogue =
typename cutlass::epilogue::collective::CollectiveBuilder<
${arch}, ${opcode_class_epi},
cute::Shape<cute::_${tile_shape_epi_m}, cute::_${tile_shape_epi_n}, cute::_${tile_shape_epi_k}>,
cute::Shape<${cluster_shape_m}, ${cluster_shape_n}, ${cluster_shape_k}>,
${epi_tile_mn},
${element_accumulator}, ${element_epilogue},
${element_c}, ${layout_c}, ${align_c},
${element_d}, ${layout_d}, ${align_d},
${epilogue_schedule},
${epilogue_functor}
>::CollectiveOp;
using ${operation_name}_mainloop =
typename cutlass::gemm::collective::CollectiveBuilder<
${arch}, ${opcode_class_main},
${element_a}, ${layout_a}, ${align_a},
${element_b}, ${layout_b}, ${align_b},
${element_accumulator},
cute::Shape<cute::_${tile_shape_main_m}, cute::_${tile_shape_main_n}, cute::_${tile_shape_main_k}>,
cute::Shape<${cluster_shape_m}, ${cluster_shape_n}, ${cluster_shape_k}>,
${stages},
${kernel_schedule}
>::CollectiveOp;
// Gemm operator ${operation_name}
using ${operation_name}_base = cutlass::gemm::kernel::GemmUniversal<
cute::Shape<int,int,int,int>,
${operation_name}_mainloop,
${operation_name}_epilogue,
${tile_scheduler}>;
// Define named type
struct ${operation_name} :
public ${operation_name}_base { };
"""
#
def instance_template(self):
return """
${compile_guard_start}
{
using GemmKernel = cutlass::gemm::device::GemmUniversalAdapter<${operation_name}>;
manifest.append(
new ${gemm_kind}<GemmKernel>("${operation_name}"));
}
${compile_guard_end}
"""
#
def emit(self, operation):
_LOGGER.debug("*** EmitGemmConfigurationLibrary::emit(operation)")
_LOGGER.debug("*** operation.procedural_name(): " + operation.procedural_name())
_LOGGER.debug("*** tile_shape: " + str(operation.tile_description.tile_shape))
_LOGGER.debug("*** warp_count: " + str(operation.tile_description.warp_count))
opcode_class_main = operation.tile_description.math_instruction.opcode_class
opcode_class_epi = opcode_class_main
tile_shape = operation.tile_description.tile_shape
instruction_shape = operation.tile_description.math_instruction.instruction_shape
cluster_m = operation.tile_description.cluster_shape[0]
cluster_n = operation.tile_description.cluster_shape[1]
tile_shape_main_m, tile_shape_main_n, tile_shape_main_k = tile_shape
tile_shape_epi_m, tile_shape_epi_n, tile_shape_epi_k = tile_shape
# account for static/dynamic cluster shapes
cta_m = tile_shape[0] // cluster_m if cluster_m > 0 else tile_shape[0]
cta_n = tile_shape[1] // cluster_n if cluster_n > 0 else tile_shape[1]
# stage count set to zero indicates builder automatic stage selection
if operation.tile_description.stages > 0:
stage_count_string = f"cutlass::gemm::collective::StageCount<{str(operation.tile_description.stages)}>"
else:
stage_count_string = f"cutlass::gemm::collective::StageCountAutoCarveout<static_cast<int>(sizeof(typename {str(operation.procedural_name())}_epilogue::SharedStorage))>"
epi_tile_mn = "cutlass::epilogue::collective::EpilogueTileAuto"
instance_layout_A, instance_layout_B, instance_layout_C , instance_layout_D = \
(operation.A.layout, operation.B.layout, operation.C.layout, operation.D.layout)
# 3.0 profiler integration only supports trivial epilogues for now
epilogue_vector_length = 1
# Support built-in epilogue functors or user-defined functions
if isinstance(operation.epilogue_functor, enum.Enum):
values = {
'element_epilogue': str(DataTypeTag[operation.element_epilogue]),
'epilogue_functor': EpilogueFunctor3xTag[operation.epilogue_functor],
}
epilogue_functor = SubstituteTemplate(self.builtin_epilogue_functor_template, values)
else:
epilogue_functor = self.epilogue_functor.emit_declaration()
#
# Cutlass3x complex kernels' ElementA(B) is a tuple in collective mainloop builder, e.g. cute::tuple<Element, Transform>, Transform : cute::identity / cute::conjugate.
element_a = DataTypeTag[operation.A.element] if not operation.is_complex() else f"cute::tuple<{str(DataTypeTag[operation.A.element])},{str(ComplexTransformTag3x[operation.A.complex_transform])}>"
element_b = DataTypeTag[operation.B.element] if not operation.is_complex() else f"cute::tuple<{str(DataTypeTag[operation.B.element])},{str(ComplexTransformTag3x[operation.B.complex_transform])}>"
epilogue_schedule_type = EpilogueScheduleTag[operation.epilogue_schedule]
values = {
'operation_name': operation.procedural_name(),
'operation_suffix': self.operation_suffix,
'element_a': element_a,
'layout_a': LayoutTag[instance_layout_A],
'element_b': element_b,
'layout_b': LayoutTag[instance_layout_B],
'element_c': DataTypeTag[operation.C.element],
'layout_c': LayoutTag[instance_layout_C],
'element_d': DataTypeTag[operation.D.element],
'layout_d': LayoutTag[instance_layout_D],
'element_accumulator': DataTypeTag[operation.accumulator_type()],
'opcode_class_main': OpcodeClassTag[opcode_class_main],
'opcode_class_epi': OpcodeClassTag[opcode_class_epi],
'arch': "cutlass::arch::Sm%d" % operation.arch,
'tile_shape_epi_m': str(tile_shape_epi_m),
'tile_shape_epi_n': str(tile_shape_epi_n),
'tile_shape_epi_k': str(tile_shape_epi_k),
'tile_shape_main_m': str(tile_shape_main_m),
'tile_shape_main_n': str(tile_shape_main_n),
'tile_shape_main_k': str(tile_shape_main_k),
'cluster_shape_m': 'cute::_' + str(operation.tile_description.cluster_shape[0]) if operation.tile_description.cluster_shape[0] > 0 else "int",
'cluster_shape_n': 'cute::_' + str(operation.tile_description.cluster_shape[1]) if operation.tile_description.cluster_shape[1] > 0 else "int",
'cluster_shape_k': 'cute::_' + str(operation.tile_description.cluster_shape[2]) if operation.tile_description.cluster_shape[2] > 0 else "int",
'instruction_shape_m': str(instruction_shape[0]),
'instruction_shape_n': str(instruction_shape[1]),
'instruction_shape_k': str(instruction_shape[2]),
'kernel_schedule' : str(KernelScheduleTag[operation.kernel_schedule]),
'epilogue_schedule' : str(epilogue_schedule_type),
'epi_tile_mn' : epi_tile_mn,
'epilogue_functor': epilogue_functor,
'stages': stage_count_string,
'align_a': str(operation.A.alignment),
'align_b': str(operation.B.alignment),
'align_c': str(operation.C.alignment),
'align_d': str(operation.C.alignment),
'transform_a': ComplexTransformTag[operation.A.complex_transform],
'transform_b': ComplexTransformTag[operation.B.complex_transform],
'math_operation': MathOperationTag[operation.tile_description.math_instruction.math_operation],
'epilogue_vector_length': str(epilogue_vector_length),
'element_epilogue': str(DataTypeTag[operation.element_epilogue]),
'tile_scheduler': str(TileSchedulerTag[operation.tile_scheduler]),
}
return SubstituteTemplate(self.gemm_template, values)
###################################################################################################
#
class EmitGemmPlanarComplexInstance:
''' Responsible for emitting a CUTLASS template definition'''
def __init__(self, operation_suffix = ''):
self.operation_suffix = operation_suffix
self.includes = []
self.template = """
// Gemm operator ${operation_name}
using Operation_${operation_name} = typename cutlass::gemm::kernel::DefaultGemmPlanarComplexUniversal<
${element_a}, ${layout_a}, ${transform_a}, ${alignment_a},
${element_b}, ${layout_b}, ${transform_b}, ${alignment_b},
${element_c}, cutlass::layout::RowMajor,
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
cutlass::epilogue::thread::LinearCombinationPlanarComplex<
${element_c},
${alignment_c},
${element_accumulator},
${element_epilogue}
>,
cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
${stages},
${math_operator}
>::GemmKernel;
struct ${operation_name} :
public Operation_${operation_name} { };
"""
#
def instance_template(self):
return """
${compile_guard_start}
manifest.append(new ${gemm_kind}<
cutlass::gemm::device::GemmUniversalAdapter<${operation_name}>
>("${operation_name}"));
${compile_guard_end}
"""
#
def emit(self, operation):
warp_shape = [operation.tile_description.threadblock_shape[idx] // operation.tile_description.warp_count[idx] for idx in range(3)]
# exchange and transpose A and B types, layouts, and complex transforms since the C layout is row-major
transposed_layout_A = TransposedLayout[operation.A.layout]
transposed_layout_B = TransposedLayout[operation.B.layout]
values = {
'operation_name': operation.procedural_name(),
'element_a': DataTypeTag[operation.B.element],
'layout_a': LayoutTag[transposed_layout_B],
'transform_a': ComplexTransformTag[operation.B.complex_transform],
'alignment_a': str(operation.B.alignment),
'element_b': DataTypeTag[operation.A.element],
'layout_b': LayoutTag[transposed_layout_A],
'transform_b': ComplexTransformTag[operation.A.complex_transform],
'alignment_b': str(operation.A.alignment),
'element_c': DataTypeTag[operation.C.element],
'layout_c': LayoutTag[operation.C.layout],
'element_accumulator': DataTypeTag[operation.tile_description.math_instruction.element_accumulator],
'opcode_class': OpcodeClassTag[operation.tile_description.math_instruction.opcode_class],
'arch': "cutlass::arch::Sm%d" % operation.arch,
'threadblock_shape_m': str(operation.tile_description.threadblock_shape[0]),
'threadblock_shape_n': str(operation.tile_description.threadblock_shape[1]),
'threadblock_shape_k': str(operation.tile_description.threadblock_shape[2]),
'warp_shape_m': str(warp_shape[0]),
'warp_shape_n': str(warp_shape[1]),
'warp_shape_k': str(warp_shape[2]),
'instruction_shape_m': str(operation.tile_description.math_instruction.instruction_shape[0]),
'instruction_shape_n': str(operation.tile_description.math_instruction.instruction_shape[1]),
'instruction_shape_k': str(operation.tile_description.math_instruction.instruction_shape[2]),
'alignment_c': str(operation.C.alignment),
'element_epilogue': str(DataTypeTag[operation.element_epilogue]),
'stages': str(operation.tile_description.stages),
'math_operator': 'cutlass::arch::OpMultiplyAdd'
}
return SubstituteTemplate(self.template, values)
###################################################################################################
#
class EmitGemmPlanarComplexArrayInstance:
''' Responsible for emitting a CUTLASS template definition'''
def __init__(self, operation_suffix = ''):
self.operation_suffix = operation_suffix
self.includes = []
self.template = """
// Gemm operator ${operation_name}
using Operation_${operation_name} = typename cutlass::gemm::kernel::DefaultGemmPlanarComplexUniversal<
${element_a}, ${layout_a}, ${transform_a}, ${alignment_a},
${element_b}, ${layout_b}, ${transform_b}, ${alignment_b},
${element_c}, cutlass::layout::RowMajor,
${element_accumulator},
${opcode_class},
${arch},
cutlass::gemm::GemmShape<${threadblock_shape_m}, ${threadblock_shape_n}, ${threadblock_shape_k}>,
cutlass::gemm::GemmShape<${warp_shape_m}, ${warp_shape_n}, ${warp_shape_k}>,
cutlass::gemm::GemmShape<${instruction_shape_m}, ${instruction_shape_n}, ${instruction_shape_k}>,
cutlass::epilogue::thread::LinearCombinationPlanarComplex<
${element_c},
${alignment_c},
${element_accumulator},
${element_epilogue}
>,
cutlass::gemm::threadblock::GemmIdentityThreadblockSwizzle<>,
${stages},
${math_operator}
>::GemmArrayKernel;
struct ${operation_name} : public Operation_${operation_name} { };
"""
#
def instance_template(self):
return """
${compile_guard_start}
manifest.append(new ${gemm_kind}<
cutlass::gemm::device::GemmUniversalAdapter<${operation_name}>
>("${operation_name}"));
${compile_guard_end}
"""
#