blob: 11728c03efec6d91d5e2c76bc7e4dff452c505e3 [file] [log] [blame]
# Copyright 2022 The IREE Authors
#
# Licensed under the Apache License v2.0 with LLVM Exceptions.
# See https://llvm.org/LICENSE.txt for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
# End-to-end matrix multiplication tests.
load("//build_tools/bazel:iree_trace_runner_test.bzl", "iree_generated_trace_runner_test")
package(
features = ["layering_check"],
licenses = ["notice"], # Apache 2.0
)
py_binary(
name = "generate_e2e_matmul_tests",
srcs = ["generate_e2e_matmul_tests.py"],
)
###########################################################################
##
## LLVMCPU backend
##
###########################################################################
# LLVMCPU, non-data-tiling, no microkernels
[iree_generated_trace_runner_test(
name = "e2e_matmul_nondt_%s_%s_%s" % (lhs_rhs_type, acc_type, size),
compiler_flags = [
"--iree-opt-data-tiling=false",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=%s" % lhs_rhs_type,
"--acc_type=%s" % acc_type,
"--shapes=%s" % size,
],
tags = [
# f16/bf16 trigger internal LLVM assertion errors on riscv and wasm.
"noriscv",
"nowasm",
] if (lhs_rhs_type == "f16" or lhs_rhs_type == "bf16") else [],
target_backends_and_drivers = [
("llvm-cpu", "local-task"),
],
target_cpu_features_variants = ["default"] +
# Widening matmuls fail to lower for SVE.
(["arm_64:sve:+sve"] if lhs_rhs_type == acc_type else []),
trace_runner = "//tools:iree-e2e-matmul-test",
) for (lhs_rhs_type, acc_type) in [
("i8", "i32"),
("f32", "f32"),
("f16", "f16"),
("f16", "f32"),
# TODO(#15258): enable bf16 tests when that bug is fixed.
# ("bf16", "bf16"),
# ("bf16", "f32"),
] for size in [
"small",
"large",
]]
X86_64_AVX2 = [
"+avx",
"+avx2",
"+fma",
"+f16c",
]
X86_64_AVX512 = X86_64_AVX2 + [
"+avx512f",
"+avx512vl",
"+avx512cd",
"+avx512bw",
"+avx512dq",
]
X86_64_AVX512_VNNI = X86_64_AVX512 + [
"+avx512vnni",
]
X86_64_AVX512_BF16 = X86_64_AVX512 + [
"+avx512bf16",
]
# LLVMCPU, data-tiling + microkernels.
# TODO(#15241, #15215): also test data-tiling alone without microkernels. This currently
# fails (#15241), which needs to be resolved to unblock data-tiling-by-default (#15215).
[iree_generated_trace_runner_test(
name = "e2e_matmul_dt_uk_%s_%s_%s" % (lhs_rhs_type, acc_type, size),
compiler_flags = [
"--iree-opt-data-tiling",
"--iree-llvmcpu-enable-microkernels",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=%s" % lhs_rhs_type,
"--acc_type=%s" % acc_type,
"--shapes=%s" % size,
],
tags = ([
# "--shapes=large" can cause timeouts on sanitizers.
"noasan",
"notsan",
] if size == "large" else []) + ([
# "--shapes=large" can cause timeouts on RISC-V emulator.
# f16/bf16 trigger internal LLVM assertion errors on riscv and wasm.
"noriscv",
"nowasm",
] if (lhs_rhs_type == "f16" or lhs_rhs_type == "bf16") else []),
target_backends_and_drivers = [
("llvm-cpu", "local-task"),
],
target_cpu_features_variants = ["default"] +
([
"arm_64:dotprod:+dotprod",
"arm_64:i8mm:+i8mm",
"x86_64:avx512vnni:" + ",".join(X86_64_AVX512_VNNI),
] if lhs_rhs_type == "i8" and acc_type == "i32" else [
"x86_64:avx2:" + ",".join(X86_64_AVX2),
"x86_64:avx512:" + ",".join(X86_64_AVX512),
] if lhs_rhs_type == "f32" and acc_type == "f32" else [
"x86_64:avx2:" + ",".join(X86_64_AVX2),
"x86_64:avx512:" + ",".join(X86_64_AVX512),
"arm_64:fullfp16:+fullfp16",
] if lhs_rhs_type == "f16" and acc_type == "f16" else [
"x86_64:avx2:" + ",".join(X86_64_AVX2),
"x86_64:avx512:" + ",".join(X86_64_AVX512),
"arm_64:fp16fml:+fp16fml",
] if lhs_rhs_type == "f16" and acc_type == "f32" else [
"x86_64:avx2:" + ",".join(X86_64_AVX2),
"x86_64:avx512:" + ",".join(X86_64_AVX512),
"x86_64:avx512bf16:" + ",".join(X86_64_AVX512_BF16),
"arm_64:bf16:+bf16",
] if lhs_rhs_type == "bf16" and acc_type == "bf16" else [
"x86_64:avx2:" + ",".join(X86_64_AVX2),
"x86_64:avx512:" + ",".join(X86_64_AVX512),
"x86_64:avx512bf16:" + ",".join(X86_64_AVX512_BF16),
"arm_64:bf16:+bf16",
] if lhs_rhs_type == "bf16" and acc_type == "f32" else []),
trace_runner = "//tools:iree-e2e-matmul-test",
) for (lhs_rhs_type, acc_type) in [
("i8", "i32"),
("f32", "f32"),
("f16", "f16"),
("f16", "f32"),
("bf16", "bf16"),
("bf16", "f32"),
] for size in [
"small",
"large",
]]
# Some e2e testing for --iree-codegen-enable-vector-padding=false.
iree_generated_trace_runner_test(
name = "e2e_matmul_nondt_f32_small_no_padding",
compiler_flags = [
"--iree-codegen-enable-vector-padding=false",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f32",
"--shapes=small",
],
target_backends_and_drivers = [
("llvm-cpu", "local-task"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
###########################################################################
##
## VMVX backend
##
###########################################################################
# VMVX, data-tiling + microkernels.
[iree_generated_trace_runner_test(
name = "e2e_matmul_dt_uk_%s_small" % lhs_rhs_type,
compiler_flags = [
"--iree-vmvx-enable-microkernels",
"--iree-opt-data-tiling",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=%s" % lhs_rhs_type,
"--shapes=small",
],
target_backends_and_drivers = [
("vmvx", "local-task"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
) for lhs_rhs_type in [
"i8",
"f32",
]]
###########################################################################
##
## CUDA backend
##
###########################################################################
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f32_gpu_large_LLVMGPUMatmulSimt",
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f32",
"--shapes=gpu_large_aligned",
"--compilation_info=LLVMGPUMatmulSimt",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-nvidia",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
# Testing Ampere + TensorCore path.
# WMMA TensorCore(F32): wmma.161616.f32.tf32
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f32_gpu_large_LLVMGPUMatmulTensorCore",
compiler_flags = [
"--iree-hal-cuda-llvm-target-arch=sm_80",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f32",
"--shapes=gpu_large_aligned",
"--compilation_info=LLVMGPUMatmulTensorCore",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-sm80",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f32_gpu_large_unaligned",
compiler_flags = [
"--iree-hal-cuda-llvm-target-arch=sm_80",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f32",
"--shapes=gpu_large",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-sm80",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f16_gpu_large_unaligned",
compiler_flags = [
"--iree-hal-cuda-llvm-target-arch=sm_80",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f16",
"--shapes=gpu_large",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-sm80",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
# MMA.SYNC TensorCore(F32): mma.sync.1688.f32.t32
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f32_gpu_large_mma_sync_LLVMGPUMatmulTensorCoreMmaSync",
compiler_flags = [
"--iree-hal-cuda-llvm-target-arch=sm_80",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f32",
"--shapes=gpu_large_aligned",
"--compilation_info=LLVMGPUMatmulTensorCoreMmaSync",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-sm80",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
# WMMA TensorCore(F16): wmma.161616.f16.f16
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f16_gpu_large_LLVMGPUMatmulTensorCore",
compiler_flags = [
"--iree-hal-cuda-llvm-target-arch=sm_80",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f16",
"--shapes=gpu_large_aligned",
"--compilation_info=LLVMGPUMatmulTensorCore",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-sm80",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
# MMA.SYNC TensorCore(F16): mma.sync.161616.f16.f16
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f16_gpu_large_mma_sync_LLVMGPUMatmulTensorCoreMmaSync",
compiler_flags = [
"--iree-hal-cuda-llvm-target-arch=sm_80",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f16",
"--shapes=gpu_large_aligned",
"--compilation_info=LLVMGPUMatmulTensorCoreMmaSync",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-sm80",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)
[iree_generated_trace_runner_test(
name = "e2e_matmul_direct_%s_large_split_k" % lhs_rhs_type,
compiler_flags = [
"--iree-flow-split-matmul-reduction=4",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=%s" % lhs_rhs_type,
"--shapes=large",
],
tags = [
# CUDA cuInit fails with sanitizer on.
"noasan",
"nomsan",
"notsan",
"noubsan",
"requires-gpu-nvidia",
# "--shapes=large" can cause timeouts on riscv emulator.
"noriscv",
],
target_backends_and_drivers = [
("cuda", "cuda"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
) for lhs_rhs_type in [
"f32",
]]
###########################################################################
##
## Vulkan backend
##
###########################################################################
[iree_generated_trace_runner_test(
name = "e2e_matmul_direct_{0}_gpu_large_valhall".format(lhs_rhs_type),
compiler_flags = [
"--iree-vulkan-target-triple=valhall-unknown-android31",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=%s" % lhs_rhs_type,
"--shapes=gpu_large_aligned",
"--compilation_info=SPIRVVectorizeMali",
],
tags = [
# Nvidia GPUs support a superset of Valhall features
"requires-gpu-nvidia",
"vulkan_uses_vk_khr_shader_float16_int8",
],
target_backends_and_drivers = [
("vulkan-spirv", "vulkan"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
) for lhs_rhs_type in [
"i8",
"f16",
"f32",
]]
[iree_generated_trace_runner_test(
name = "e2e_matmul_direct_{0}_gpu_large_ampere".format(lhs_rhs_type),
compiler_flags = [
"--iree-vulkan-target-triple=ampere-unknown-linux",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=%s" % lhs_rhs_type,
"--shapes=gpu_large_aligned",
"--compilation_info=SPIRVVectorizeNVIDIA",
],
tags = [
"requires-gpu-sm80",
"vulkan_uses_vk_khr_shader_float16_int8",
],
target_backends_and_drivers = [
("vulkan-spirv", "vulkan"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
) for lhs_rhs_type in [
"i8",
"f16",
"f32",
]]
iree_generated_trace_runner_test(
name = "e2e_matmul_direct_f16_gpu_large_rdna3",
compiler_flags = [
"--iree-vulkan-target-triple=rdna3-unknown-linux",
],
generator = ":generate_e2e_matmul_tests",
generator_args = [
"--lhs_rhs_type=f16",
"--shapes=gpu_large_aligned",
"--compilation_info=SPIRVCooperativeMatrixVectorize",
],
runner_args = [
"--require_exact_results=false",
],
tags = [
"requires-gpu",
"requires-gpu-rdna3",
"vulkan_uses_vk_khr_shader_float16_int8",
],
target_backends_and_drivers = [
("vulkan-spirv", "vulkan"),
],
trace_runner = "//tools:iree-e2e-matmul-test",
)