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