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
|
# This script generates all variants of wmma builtins, verifies that clang calls
# correct LLVM instrinsics, and checks that availability of specific builtins is
# constrained by the correct PTX version and the target GPU variant.
# Dummy test run to avoid lit warnings.
# RUN: echo "This is not a real test. It's a generator for builtins-nvpts-mma.cu" >/dev/null
from __future__ import print_function
import argparse
from collections import defaultdict
from itertools import product
from string import Template
class MMAFrag:
def __init__(self, geom, frag, ptx_elt_type):
self.geom = geom
self.frag = frag
self.ptx_type = ptx_elt_type;
def __repr__(self):
return "%s:%s:%s" % (self.geom, self.frag, self.ptx_type)
class MMAOp:
def __init__(self, a, b, c, d):
self.a = a
self.b = b
self.c = c
self.d = d
def __repr__(self):
return ("{A:%s, B:%s, C:%s, D:%s}" % (self.a, self.b, self.c, self.d ))
def make_mma_ops(geoms, types_a, types_b, types_c, types_d):
ops = []
for geom, type_a, type_c in product( geoms, types_a, types_c):
for type_b, type_d in product(types_b if types_b else [type_a],
types_d if types_d else [type_c]):
ops.append(MMAOp(MMAFrag(geom, "a", type_a),
MMAFrag(geom, "b", type_b),
MMAFrag(geom, "c", type_c),
MMAFrag(geom, "d", type_d)))
return ops
def make_ldst_ops(geoms, frags, types):
return [MMAFrag(geom, frag, ptx_type) for (geom, frag, ptx_type)
in product(geoms, frags, types)]
def get_mma_ops():
return (make_mma_ops(["m16n16k16", "m32n8k16", "m8n32k16"],
["f16"], [], ["f16", "f32"], ["f16", "f32"]) +
make_mma_ops(["m16n16k16", "m32n8k16", "m8n32k16"],
["s8", "u8"], [], ["s32"], []) +
make_mma_ops(["m8n8k32"],
["s4", "u4"], [], ["s32"], []) +
make_mma_ops(["m8n8k128"],
["b1"], [], ["s32"], []))
def get_ldst_ops():
return (make_ldst_ops(["m16n16k16", "m32n8k16", "m8n32k16"],
["a", "b"], ["f16", "u8", "s8"]) +
make_ldst_ops(["m16n16k16", "m32n8k16", "m8n32k16"],
["c", "d"], ["f16", "f32", "s32"]) +
make_ldst_ops(["m8n8k32"], ["a", "b"], ["s4","u4"]) +
make_ldst_ops(["m8n8k128"], ["a", "b"], ["b1"]) +
make_ldst_ops(["m8n8k32", "m8n8k128"], ["c", "d"], ["s32"]))
def is_geom_supported(geom):
# geometries for FP and ints.
if geom in ["m8n32k16", "m32n8k16"]:
return ptx_version >= 61
# geometries for sub-ints.
if geom in ["m8n8k32", "m8n8k128"]:
return ptx_version >= 63 and gpu_arch >= 75
if geom == "m16n16k16":
return ptx_version >= 60
assert(False) # Unexpected geometry.
def is_type_supported(ptx_type):
if ptx_type in ["s8", "u8", "s32"]:
return ptx_version >= 63 and gpu_arch >= 72
if ptx_type in ["s4", "u4", "b1"]:
return ptx_version >= 63 and gpu_arch >= 75
return ptx_version >= 60 and gpu_arch >= 70
def is_mma_variant_supported(op, layout_a, layout_b, satf):
if not (is_type_supported(op.a.ptx_type)
and is_geom_supported(op.a.geom)):
return False
# sub-integer require row/col layout, and no satf.
if op.a.ptx_type in ["s4", "u4", "b1"]:
if op.a.ptx_type == "b1" and satf:
return False
return layout_a == "row" and layout_b == "col"
return True
def is_ldst_variant_supported(frag, layout):
if not (is_type_supported(frag.ptx_type)
and is_geom_supported(frag.geom)):
return False
if frag.ptx_type in ["s4", "u4", "b1"]:
# sub-integer require sm_75 and ptx63, row/col layout for a/b.
return ((frag.frag == "a" and layout == "row")
or (frag.frag == "b" and layout == "col")
or frag.frag in ["c", "d"])
return True
def get_builtin_prefix(frag):
prefix = None
if frag.geom in ["m16n16k16", "m32n8k16", "m8n32k16"]:
if frag.ptx_type in ["f16", "f32"]:
prefix = "__hmma"
else:
prefix = "__imma"
elif frag.geom == "m8n8k32":
prefix = "__imma" # sub-integers
elif frag.geom == "m8n8k128":
prefix = "__bmma"
assert prefix
return prefix
def get_ldst_builtin_name(frag):
prefix = get_builtin_prefix(frag)
if prefix == "__hmma":
suffix = "" if frag.frag in ["a","b"] else frag.ptx_type
elif prefix in ["__imma", "__bmma"]:
suffix = "" if frag.frag in ["c"] else frag.ptx_type
if suffix == "s32":
suffix = "i32"
if frag.frag == "d":
ifrag = "c"
op = "st"
else:
ifrag = frag.frag
op = "ld"
name = "%s_%s_%s_%s%s" % (prefix, frag.geom, op, ifrag,
"_" + suffix if suffix else "")
return name
def get_mma_builtin_name(op):
prefix = get_builtin_prefix(op.a)
if prefix == "__hmma":
suffix = op.d.ptx_type + op.c.ptx_type
else:
suffix = op.a.ptx_type
name = "%s_%s_mma%s_%s" % (prefix, op.a.geom,
"_xor_popc" if op.a.ptx_type == "b1" else "",
suffix)
return name
def get_required_sm(frag):
if frag.ptx_type in ["u4", "s4", "b1"]:
return 75
if frag.ptx_type in ["s8", "u8"]:
return 72
if frag.ptx_type == "s32":
if frag.geom in ["m8n8k32", "m8n8k128"]: # s4/u4/b1
return 75
else: # s8/u8
return 72
if frag.ptx_type in ["f16", "f32"]:
return 70
assert(False)
def get_required_ptx(frag):
if frag.ptx_type in ["f16", "f32"]:
return 60 if frag.geom == "m16n16k16" else 61
return 63
def gen_wmma_ldst_tests(results):
load_template = """
// CHECK${check_suffix}: call {{.*}} @${intrinsic}
// expected-error-re@+1 {{'${builtin}' needs target feature sm_${min_sm}{{.*}},ptx${min_ptx}{{.*}}}}
${builtin}(${dst}, ${src}, ldm, ${blayout});
""".rstrip()
intrinsic_template = "llvm.nvvm.wmma.${geom}.${op}.${frag}.${ilayout}.stride.${itype}"
for frag, layout in sorted(product(get_ldst_ops(), ["row","col"]), key=str):
if not is_ldst_variant_supported(frag, layout):
continue
is_fp = frag.ptx_type == "f32"
min_sm = get_required_sm(frag)
min_ptx = get_required_ptx(frag)
params = {
"check_suffix" : "_PTX%d_SM%d" % (min_ptx, min_sm),
"builtin" : get_ldst_builtin_name(frag),
"min_ptx" : min_ptx,
"min_sm" : min_sm,
"dst": "fdst" if is_fp else "dst",
"src": "fsrc" if is_fp else "src",
"blayout" : 0 if layout == "row" else 1,
"intrinsic" : Template(intrinsic_template).substitute({
"frag" : frag.frag,
"geom" : frag.geom,
"ilayout" : layout,
"itype" : frag.ptx_type,
"op" : "store" if frag.frag == "d" else "load",
})
}
results[(min_ptx,min_sm)] += Template(load_template).substitute(params)
return results
def mma_signature(op):
if op.a.ptx_type in ["s8", "u8", "s4", "u4", "b1"]:
# int and sub-int ops are identified by input type.
return op.a.ptx_type
else:
# the rest are FP ops identified by accumulator & result type.
return "%s.%s" % (op.d.ptx_type, op.c.ptx_type)
# Get numeric value for rowcol parameter of the builtin
# AFAICT it uses the encoding accepted by NVVM intrinsics:
# https://docs.nvidia.com/cuda/nvvm-ir-spec/index.html#nvvm-intrin-warp-level-matrix-mma
def get_ilayout(a, b):
return {
"row.row" : 0,
"row.col" : 1,
"col.row" : 2,
"col.col" : 3
}[a + "." + b]
def gen_wmma_mma_tests(results):
mma_template = """
// CHECK${check_suffix}: call {{.*}} @${intrinsic}
// expected-error-re@+1 {{'${builtin}' needs target feature sm_${min_sm}{{.*}},ptx${min_ptx}{{.*}}}}
${builtin}(${dst}, ${asrc}, ${asrc}, ${csrc}, ${ilayout}${maybe_isatf});
""".rstrip()
intrinsic_template = "llvm.nvvm.wmma.${geom}.mma.${alayout}.${blayout}.${intrinsic_signature}${satf}"
for op, alayout, blayout, satf in sorted(product( get_mma_ops(),
["row","col"],
["row","col"],
[".satfinite", ""]),
key=str):
if not is_mma_variant_supported(op, alayout, blayout, satf):
continue
a_is_fp = op.a.ptx_type == "f32"
c_is_fp = op.c.ptx_type == "f32"
d_is_fp = op.d.ptx_type == "f32"
min_sm = get_required_sm(op.a)
min_ptx = get_required_ptx(op.a)
if op.a.ptx_type == "b1": # .b1 MMA has no satf argument.
isatf_arg = ""
else:
isatf_arg = ", 1" if satf else ", 0"
params = {
"check_suffix" : "_PTX%d_SM%d" % (min_ptx, min_sm),
"builtin" : get_mma_builtin_name(op),
"min_ptx" : min_ptx,
"min_sm" : min_sm,
"dst": "fdst" if d_is_fp else "dst",
"asrc": "fsrc" if a_is_fp else "src",
"csrc": "fsrc" if c_is_fp else "src",
"ilayout" : get_ilayout(alayout, blayout),
"maybe_isatf" : isatf_arg,
"intrinsic" : Template(intrinsic_template).substitute({
"geom" : op.a.geom,
"alayout" : alayout,
"blayout" : blayout,
"intrinsic_signature" : mma_signature(op),
"satf" : satf,
})
}
results[(min_ptx, min_sm)] += Template(mma_template).substitute(params)
return results
def gen_tests():
results = gen_wmma_ldst_tests(defaultdict(str))
results = gen_wmma_mma_tests(results)
run_template = r"""
//
// *** DO NOT EDIT ***
//
// This test has been automatically generated by
// builtins-nvtx-mma.py --ptx=${ptx} --gpu-arch=${sm}
//
// Make sure we can handle all builtins available on sm_${sm} with PTX${ptx}
// ${run}: %clang_cc1 -triple nvptx64-unknown-unknown -target-cpu sm_${sm} \
// ${run}: -fcuda-is-device -target-feature +ptx${ptx} \
// ${run}: -DPTX=${ptx} -DSM=${sm} \
// ${run}: -S -emit-llvm -o - -x cuda %s \
// ${run}: | FileCheck -check-prefixes=${check_labels} %s
// Verify that all builtins have correct constraints.
// ${run}: %clang_cc1 -triple nvptx-unknown-unknown \
// ${run}: -target-cpu sm_60 -target-feature +ptx42 \
// ${run}: -DPTX=${ptx} -DSM=${sm} -fcuda-is-device -S -o /dev/null -x cuda \
// ${run}: -verify %s
"""
def supported_variants(ptx, sm, results):
return [(ptx_, sm_) for ptx_, sm_ in results if ptx_ <= ptx and sm_ <= sm]
print(Template(run_template).substitute({
"run" : "RUN", # To avoid lit misinterpreting the template
"ptx" : ptx_version,
"sm" : gpu_arch,
"check_labels" : ",".join(["CHECK_PTX%d_SM%d" % (ptx_, sm_)
for ptx_, sm_
in supported_variants(ptx_version, gpu_arch,
results)])
}))
print("""
#if !defined(CUDA_VERSION)
#define __device__ __attribute__((device))
#define __global__ __attribute__((global))
#define __shared__ __attribute__((shared))
#define __constant__ __attribute__((constant))
typedef unsigned long long uint64_t;
#endif
// CHECK-LABEL: test_wmma_buitins
__device__ void test_wmma_buitins(int *src, int *dst,
float *fsrc, float *fdst, int ldm) {
""");
for (ptx, sm), tests in sorted(results.items()):
print()
print("#if (PTX >= %d) && (SM >= %d)" % (ptx, sm))
print(tests)
print("#endif // (PTX >= %d) && (SM >= %d) "% (ptx, sm))
print("}")
parser = argparse.ArgumentParser()
parser.add_argument("--ptx", type=int, default=60)
parser.add_argument("--gpu-arch", type=int, default=70)
args = parser.parse_args()
ptx_version = args.ptx
gpu_arch = args.gpu_arch
gen_tests()
|