forked from NVIDIA/cutlass
-
Notifications
You must be signed in to change notification settings - Fork 0
/
trmm_operation.py
407 lines (328 loc) · 14.2 KB
/
trmm_operation.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a TRMM operation
#
###################################################################################################
#
class TrmmOperation:
#
def __init__(self, trmm_kind, arch, tile_description, A, B, C, element_epilogue, \
epilogue_functor = EpilogueFunctor.LinearCombination, swizzling_functor = SwizzlingFunctor.Identity8):
self.operation_kind = OperationKind.Trmm
self.arch = arch
self.tile_description = tile_description
self.trmm_kind = trmm_kind
self.A = A
self.B = B
self.C = C
self.element_epilogue = element_epilogue
self.epilogue_functor = epilogue_functor
self.swizzling_functor = swizzling_functor
#
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
return False
#
def is_planar_complex(self):
# return self.trmm_kind in (TrmmKind.PlanarComplex, TrmmKind.PlanarComplexArray)
return False
#
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',
}
if self.tile_description.math_instruction.opcode_class == OpcodeClass.TensorOp or \
self.tile_description.math_instruction.opcode_class == OpcodeClass.WmmaTensorOp:
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 ''
inst_shape = "%d%d%d" % 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, TrmmKindNames[self.trmm_kind])
#
def extended_name(self):
''' Append data types if they differ from compute type. '''
if self.is_complex():
extended_name = "${core_name}"
else:
if self.C.element != self.tile_description.math_instruction.element_accumulator and \
self.A.element != self.tile_description.math_instruction.element_accumulator:
extended_name = "${element_c}_${core_name}_${element_a}"
elif self.C.element == self.tile_description.math_instruction.element_accumulator and \
self.A.element != self.tile_description.math_instruction.element_accumulator:
extended_name = "${core_name}_${element_a}"
else:
extended_name = "${core_name}"
extended_name = SubstituteTemplate(extended_name, {
'element_a': DataTypeNames[self.A.element],
'element_c': DataTypeNames[self.C.element],
'core_name': self.core_name()
})
return extended_name
#
def layout_name(self):
if self.is_complex() or self.is_planar_complex():
return "%s%s" % (
ShortComplexLayoutNames[(self.A.layout, self.A.complex_transform)],
ShortComplexLayoutNames[(self.B.layout, self.B.complex_transform)]
)
return "%s%s" % (ShortLayoutTypeNames[self.A.layout], ShortLayoutTypeNames[self.B.layout])
#
def side_mode_name(self):
return "%s" % (ShortSideModeNames[self.A.side_mode])
#
def fill_mode_name(self):
return "%s" % (ShortFillModeNames[self.A.fill_mode])
#
def diag_type_name(self):
return "%s" % (ShortDiagTypeNames[self.A.diag_type])
#
def procedural_name(self):
''' The full procedural name indicates architecture, extended name, tile size, and layout. '''
threadblock = self.tile_description.procedural_name()
opcode_class_name = OpcodeClassNames[self.tile_description.math_instruction.opcode_class]
alignment = max([self.C.alignment])
return SubstituteTemplate(
"cutlass_${opcode_class}_${extended_name}_${threadblock}_${layout}_${side_mode}_${fill_mode}_${diag_type}_align${alignment}",
{
'opcode_class': opcode_class_name,
'extended_name': self.extended_name(),
'threadblock': threadblock,
'layout': self.layout_name(),
'side_mode': self.side_mode_name(),
'fill_mode': self.fill_mode_name(),
'diag_type': self.diag_type_name(),
'alignment': "%d" % self.C.alignment,
}
)
#
def configuration_name(self):
''' The full procedural name indicates architecture, extended name, tile size, and layout. '''
return self.procedural_name()
###################################################################################################
#
# Emits single instances of a CUTLASS device-wide operator
#
###################################################################################################
#
class EmitTrmmUniversalInstance:
''' Responsible for emitting a CUTLASS template definition'''
def __init__(self):
self.trmm_template = """
// Trmm operator ${operation_name}
using Operation_${operation_name} =
typename cutlass::gemm::device::Trmm<
${element_a}, ${layout_a},
${side_mode}, ${fill_mode}, ${diag_type},
${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},
cutlass::epilogue::thread::ScaleType::OnlyAlphaScaling
>,
${swizzling_functor},
${stages},
${align_a},
${align_b},
${split_k_serial},
${math_operation}
>;
"""
self.trmm_complex_template = """
// Trmm operator ${operation_name}
using Operation_${operation_name} =
typename cutlass::gemm::device::Trmm<
${element_a}, ${layout_a},
${side_mode}, ${fill_mode}, ${diag_type},
${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},
cutlass::epilogue::thread::ScaleType::OnlyAlphaScaling
>,
${swizzling_functor},
${stages},
${align_a},
${align_b},
${split_k_serial},
${math_operation},
${transform_a}
>;
"""
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)]
epilogue_vector_length = int(min(operation.C.alignment * DataTypeSize[operation.C.element], 128) / DataTypeSize[operation.C.element])
values = {
'operation_name': operation.procedural_name(),
'element_a': DataTypeTag[operation.A.element],
'layout_a': LayoutTag[operation.A.layout],
'side_mode' : SideModeTag[operation.A.side_mode],
'fill_mode': FillModeTag[operation.A.fill_mode],
'diag_type' : DiagTypeTag[operation.A.diag_type],
'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(1), # TRMM A's alignment is always 1 for no padding to work until we make zfill work with variable bytes
'align_b': str(operation.B.alignment),
'split_k_serial': 'false',
'math_operation': MathOperationTag[operation.tile_description.math_instruction.math_operation],
'transform_a': ComplexTransformTag[operation.A.complex_transform]
}
trmm_template = self.trmm_complex_template if operation.is_complex() else self.trmm_template
return SubstituteTemplate(trmm_template, values)
###################################################################################################
###################################################################################################
#
# Emitters functions for all targets
#
###################################################################################################
class EmitTrmmConfigurationLibrary:
def __init__(self, operation_path, configuration_name):
self.configuration_name = configuration_name
self.configuration_path = os.path.join(operation_path, "%s.cu" % configuration_name).replace('\\', '/')
self.instance_emitter = {
TrmmKind.Universal: EmitTrmmUniversalInstance,
}
self.trmm_kind_wrappers = {
TrmmKind.Universal: 'TrmmOperation',
}
self.instance_template = {
TrmmKind.Universal: """
${compile_guard_start}
manifest.append(new ${trmm_kind}<
Operation_${operation_name}
>("${operation_name}"));
${compile_guard_end}
"""
}
self.header_template = """
/*
Generated by trmm_operation.py - Do not edit.
*/
///////////////////////////////////////////////////////////////////////////////////////////////////
#include "cutlass/cutlass.h"
#include "cutlass/library/library.h"
#include "cutlass/library/manifest.h"
#include "library_internal.h"
#include "trmm_operation.h"
///////////////////////////////////////////////////////////////////////////////////////////////////
"""
self.initialize_function_template = """
///////////////////////////////////////////////////////////////////////////////////////////////////
namespace cutlass {
namespace library {
///////////////////////////////////////////////////////////////////////////////////////////////////
void initialize_${configuration_name}(Manifest &manifest) {
"""
self.epilogue_template = """
}
///////////////////////////////////////////////////////////////////////////////////////////////////
} // namespace library
} // namespace cutlass
///////////////////////////////////////////////////////////////////////////////////////////////////
"""
def __enter__(self):
self.configuration_file = open(self.configuration_path, "w")
self.configuration_file.write(self.header_template)
self.instance_definitions = []
self.instance_wrappers = []
self.operations = []
return self
def emit(self, operation):
emitter = self.instance_emitter[operation.trmm_kind]()
self.operations.append(operation)
self.instance_definitions.append(emitter.emit(operation))
self.instance_wrappers.append(SubstituteTemplate(self.instance_template[operation.trmm_kind], {
'configuration_name': self.configuration_name,
'operation_name': operation.procedural_name(),
'trmm_kind': self.trmm_kind_wrappers[operation.trmm_kind],
'compile_guard_start': SubstituteTemplate(self.wmma_guard_start, {'sm_number': str(operation.arch)}) \
if operation.tile_description.math_instruction.opcode_class == OpcodeClass.WmmaTensorOp else "",
'compile_guard_end': "#endif" \
if operation.tile_description.math_instruction.opcode_class == OpcodeClass.WmmaTensorOp else ""
}))
def __exit__(self, exception_type, exception_value, traceback):
# Write instance definitions in top-level namespace
for instance_definition in self.instance_definitions:
self.configuration_file.write(instance_definition)
# Add wrapper objects within initialize() function
self.configuration_file.write(SubstituteTemplate(self.initialize_function_template, {
'configuration_name': self.configuration_name
}))
for instance_wrapper in self.instance_wrappers:
self.configuration_file.write(instance_wrapper)
self.configuration_file.write(self.epilogue_template)
self.configuration_file.close()
###################################################################################################