def test_cpu_matmul():
expected = [
[],
[
'b0 = sch.get_block(name="C", func_name="main")',
"l1, l2, l3 = sch.get_loops(block=b0)",
"v4, v5 = sch.sample_perfect_tile(loop=l3, n=2, max_innermost_factor=64)",
"l6, l7 = sch.split(loop=l3, factors=[v4, v5], preserve_unit_iters=True)",
"b8 = sch.rfactor(loop=l7, factor_axis=2)",
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.random_compute_producer", ann_val=1)',
],
[
'b0 = sch.get_block(name="C", func_name="main")',
"l1, l2, l3 = sch.get_loops(block=b0)",
"v4, v5 = sch.sample_perfect_tile(loop=l3, n=2, max_innermost_factor=64)",
"l6, l7 = sch.split(loop=l3, factors=[v4, v5], preserve_unit_iters=True)",
"b8 = sch.rfactor(loop=l6, factor_axis=2)",
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.random_compute_producer", ann_val=1)',
],
]
target = Target("llvm --num-cores=32")
ctx = _create_context(
create_prim_func(te_workload.matmul(
n=4,
m=4,
k=512,
)),
target=target,
rule=add_rfactor(target=target),
)
spaces = ctx.space_generator.generate_design_space(mod=ctx.mod)
assert len(spaces) == 3
check_trace(spaces, expected)
def test_cpu_matmul():
expected = [
[
'b0 = sch.get_block(name="C", func_name="main")',
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.tiling_structure", ann_val="SSRSRS")',
"l1, l2, l3 = sch.get_loops(block=b0)",
"v4, v5, v6, v7 = sch.sample_perfect_tile(loop=l1, n=4, max_innermost_factor=64)",
"l8, l9, l10, l11 = sch.split(loop=l1, factors=[v4, v5, v6, v7])",
"v12, v13, v14, v15 = sch.sample_perfect_tile(loop=l2, n=4, max_innermost_factor=64)",
"l16, l17, l18, l19 = sch.split(loop=l2, factors=[v12, v13, v14, v15])",
"v20, v21 = sch.sample_perfect_tile(loop=l3, n=2, max_innermost_factor=64)",
"l22, l23 = sch.split(loop=l3, factors=[v20, v21])",
"sch.reorder(l8, l16, l9, l17, l22, l10, l18, l23, l11, l19)",
'b24 = sch.cache_write(block=b0, write_buffer_index=0, storage_scope="global")',
"sch.reverse_compute_at(block=b24, loop=l17, preserve_unit_loops=1)",
],
[
'b0 = sch.get_block(name="C", func_name="main")',
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.tiling_structure", ann_val="SSRSRS")',
"l1, l2, l3 = sch.get_loops(block=b0)",
"v4, v5, v6, v7 = sch.sample_perfect_tile(loop=l1, n=4, max_innermost_factor=64)",
"l8, l9, l10, l11 = sch.split(loop=l1, factors=[v4, v5, v6, v7])",
"v12, v13, v14, v15 = sch.sample_perfect_tile(loop=l2, n=4, max_innermost_factor=64)",
"l16, l17, l18, l19 = sch.split(loop=l2, factors=[v12, v13, v14, v15])",
"v20, v21 = sch.sample_perfect_tile(loop=l3, n=2, max_innermost_factor=64)",
"l22, l23 = sch.split(loop=l3, factors=[v20, v21])",
"sch.reorder(l8, l16, l9, l17, l22, l10, l18, l23, l11, l19)",
'b24 = sch.cache_write(block=b0, write_buffer_index=0, storage_scope="global")',
"sch.reverse_compute_at(block=b24, loop=l16, preserve_unit_loops=1)",
],
[
'b0 = sch.get_block(name="C", func_name="main")',
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.tiling_structure", ann_val="SSRSRS")',
"l1, l2, l3 = sch.get_loops(block=b0)",
"v4, v5, v6, v7 = sch.sample_perfect_tile(loop=l1, n=4, max_innermost_factor=64)",
"l8, l9, l10, l11 = sch.split(loop=l1, factors=[v4, v5, v6, v7])",
"v12, v13, v14, v15 = sch.sample_perfect_tile(loop=l2, n=4, max_innermost_factor=64)",
"l16, l17, l18, l19 = sch.split(loop=l2, factors=[v12, v13, v14, v15])",
"v20, v21 = sch.sample_perfect_tile(loop=l3, n=2, max_innermost_factor=64)",
"l22, l23 = sch.split(loop=l3, factors=[v20, v21])",
"sch.reorder(l8, l16, l9, l17, l22, l10, l18, l23, l11, l19)",
],
]
target = Target("llvm")
ctx = _create_context(
create_prim_func(
te_workload.matmul(
n=512,
m=512,
k=512,
)
),
target=target,
rule=multi_level_tiling(target=target),
)
spaces = ctx.space_generator.generate_design_space(mod=ctx.mod)
assert len(spaces) == 3
check_trace(spaces, expected)
def test_cuda_matmul():
# pylint: disable=line-too-long
expected = [
[
'b0 = sch.get_block(name="C", func_name="main")',
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.tiling_structure", ann_val="SSSRRSRS")',
"l1, l2, l3 = sch.get_loops(block=b0)",
"v4, v5, v6, v7, v8 = sch.sample_perfect_tile(loop=l1, n=5, max_innermost_factor=64)",
"l9, l10, l11, l12, l13 = sch.split(loop=l1, factors=[v4, v5, v6, v7, v8])",
"v14, v15, v16, v17, v18 = sch.sample_perfect_tile(loop=l2, n=5, max_innermost_factor=64)",
"l19, l20, l21, l22, l23 = sch.split(loop=l2, factors=[v14, v15, v16, v17, v18])",
"v24, v25, v26 = sch.sample_perfect_tile(loop=l3, n=3, max_innermost_factor=64)",
"l27, l28, l29 = sch.split(loop=l3, factors=[v24, v25, v26])",
"sch.reorder(l9, l19, l10, l20, l11, l21, l27, l28, l12, l22, l29, l13, l23)",
"l30 = sch.fuse(l9, l19)",
'sch.bind(loop=l30, thread_axis="blockIdx.x")',
"l31 = sch.fuse(l10, l20)",
'sch.bind(loop=l31, thread_axis="vthread.x")',
"l32 = sch.fuse(l11, l21)",
'sch.bind(loop=l32, thread_axis="threadIdx.x")',
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.thread_extent_low_inclusive", ann_val=32)',
'sch.annotate(block_or_loop=b0, ann_key="meta_schedule.thread_extent_high_inclusive", ann_val=1024)',
'b33 = sch.cache_write(block=b0, write_buffer_index=0, storage_scope="local")',
"sch.reverse_compute_at(block=b33, loop=l32, preserve_unit_loops=1)",
'b34 = sch.cache_read(block=b0, read_buffer_index=1, storage_scope="shared")',
"sch.compute_at(block=b34, loop=l27, preserve_unit_loops=1)",
"l35, l36, l37, l38, l39, l40 = sch.get_loops(block=b34)",
"l41 = sch.fuse(l39, l40)",
"v42 = sch.sample_categorical(candidates=[1, 2, 3, 4], probs=[0.25, 0.25, 0.25, 0.25])",
'sch.annotate(block_or_loop=b34, ann_key="meta_schedule.cooperative_fetch", ann_val=v42)',
'b43 = sch.cache_read(block=b0, read_buffer_index=2, storage_scope="shared")',
"sch.compute_at(block=b43, loop=l27, preserve_unit_loops=1)",
"l44, l45, l46, l47, l48, l49 = sch.get_loops(block=b43)",
"l50 = sch.fuse(l48, l49)",
"v51 = sch.sample_categorical(candidates=[1, 2, 3, 4], probs=[0.25, 0.25, 0.25, 0.25])",
'sch.annotate(block_or_loop=b43, ann_key="meta_schedule.cooperative_fetch", ann_val=v51)',
]
]
# pylint: enable=line-too-long
target = Target("cuda --max_threads_per_block=1024 --thread_warp_size=32", host="llvm")
ctx = _create_context(
create_prim_func(
te_workload.matmul(
n=512,
m=512,
k=512,
)
),
target=target,
rule=multi_level_tiling(target=target),
)
spaces = ctx.space_generator.generate_design_space(mod=ctx.mod)
assert len(spaces) == 1
check_trace(spaces, expected)
def test_rewrite_cooperative_fetch():
mod = create_prim_func(te_workload.matmul(n=512, m=512, k=512))
target = _target()
ctx = _create_context(mod, target)
sch = tir.Schedule(mod, debug_mask="all")
# fmt: off
# pylint: disable=line-too-long,invalid-name
b0 = sch.get_block(name="C", func_name="main")
b1 = sch.cache_write(block=b0, write_buffer_index=0, storage_scope="local")
l2, l3, l4 = sch.get_loops(block=b0)
v5, v6, v7, v8, v9 = sch.sample_perfect_tile(loop=l2, n=5, max_innermost_factor=64, decision=[1, 16, 1, 2, 16])
l10, l11, l12, l13, l14 = sch.split(loop=l2, factors=[v5, v6, v7, v8, v9])
v15, v16, v17, v18, v19 = sch.sample_perfect_tile(loop=l3, n=5, max_innermost_factor=64, decision=[16, 1, 8, 2, 2])
l20, l21, l22, l23, l24 = sch.split(loop=l3, factors=[v15, v16, v17, v18, v19])
v25, v26, v27 = sch.sample_perfect_tile(loop=l4, n=3, max_innermost_factor=64, decision=[1, 16, 32])
l28, l29, l30 = sch.split(loop=l4, factors=[v25, v26, v27])
sch.reorder(l10, l20, l11, l21, l12, l22, l28, l29, l13, l23, l30, l14, l24)
l31 = sch.fuse(l10, l20)
sch.bind(loop=l31, thread_axis="blockIdx.x")
l32 = sch.fuse(l11, l21)
sch.bind(loop=l32, thread_axis="vthread.x")
l33 = sch.fuse(l12, l22)
sch.bind(loop=l33, thread_axis="threadIdx.x")
b34 = sch.cache_read(block=b0, read_buffer_index=0, storage_scope="shared")
sch.compute_at(block=b34, loop=l28, preserve_unit_loops=True)
_, _, _, _, l39, l40 = sch.get_loops(block=b34)
l41 = sch.fuse(l39, l40)
_, v43 = sch.sample_perfect_tile(loop=l41, n=2, max_innermost_factor=4, decision=[262144, 1])
sch.annotate(block_or_loop=b34, ann_key="meta_schedule.cooperative_fetch", ann_val=v43)
b44 = sch.cache_read(block=b0, read_buffer_index=1, storage_scope="shared")
sch.compute_at(block=b44, loop=l28, preserve_unit_loops=True)
_, _, _, _, l49, l50 = sch.get_loops(block=b44)
l51 = sch.fuse(l49, l50)
_, v53 = sch.sample_perfect_tile(loop=l51, n=2, max_innermost_factor=4, decision=[8192, 2])
sch.annotate(block_or_loop=b44, ann_key="meta_schedule.cooperative_fetch", ann_val=v53)
sch.reverse_compute_at(block=b1, loop=l33, preserve_unit_loops=True)
# pylint: enable=line-too-long,invalid-name
# fmt: on
sch.enter_postproc()
assert ctx.postprocs[0].apply(sch)
tvm.ir.assert_structural_equal(sch.mod, AfterRewrite0)
def test_get_auto_tensorize_mapping_info_matmul(n, m, k, expected):
matmul = create_prim_func(
te_workload.matmul(n, m, k, in_dtype="float16", out_dtype="float32"))
check_index_map(matmul, "C", WMMA_SYNC_16x16x16_f16f16f32_INTRIN, expected)
