Generalize the asm kernel pattern. (#8248)

This makes MMTCustomKernelPattern generic in what kernel it's
generating, in a way that should suffice for the next few kernels that
we need to add (first motivation: float32/aarch64).

MMTCustomKernelPattern now takes the kernel-specific details from a
MMTKernel struct, including the asm code and information about the shape
and data types. The inline asm constraints string becomes
auto-generated.

All this automation had the effect of making it "too magical" for the
inline asm to continue to refer to its register operands by fixed
indices like "$12" as the llvm inline asm syntax allows, so we introduce
a pre-processing step allowing us to write kernels using placeholders
like "$(lhs:0)" for the 0-th register of the LHS, and that gets
"allocated" as the pre-processed code and the constraints string get
co-generated.

This makes for a self-contained way to describe kernels. The current
aarch64 +dotprod i8 kernel becomes:

```
// i8*i8->i32 kernel for Aarch64 NEON +dotprod
MMTKernel MMTKernel_8x4x8_i8i8i32_Aarch64Dotprod_InlineAsm() {
  MMTKernel kernel;
  kernel.arch = CustomKernelTargetArch::Aarch64;
  kernel.m0 = 8;
  kernel.k0 = 4;
  kernel.n0 = 8;
  kernel.lhsType = MMTKernel::ScalarType::I8;
  kernel.rhsType = MMTKernel::ScalarType::I8;
  kernel.accType = MMTKernel::ScalarType::I32;
  kernel.registerBitWidth = PowerOfTwo(128);
  kernel.implAsm = R"ASM(
      sdot $(acc:0).4s, $(rhs:0).16b, $(lhs:0).4b[0]
      sdot $(acc:1).4s, $(rhs:1).16b, $(lhs:0).4b[0]
      sdot $(acc:2).4s, $(rhs:0).16b, $(lhs:0).4b[1]
      sdot $(acc:3).4s, $(rhs:1).16b, $(lhs:0).4b[1]
      sdot $(acc:4).4s, $(rhs:0).16b, $(lhs:0).4b[2]
      sdot $(acc:5).4s, $(rhs:1).16b, $(lhs:0).4b[2]
      sdot $(acc:6).4s, $(rhs:0).16b, $(lhs:0).4b[3]
      sdot $(acc:7).4s, $(rhs:1).16b, $(lhs:0).4b[3]
      sdot $(acc:8).4s, $(rhs:0).16b, $(lhs:1).4b[0]
      sdot $(acc:9).4s, $(rhs:1).16b, $(lhs:1).4b[0]
      sdot $(acc:10).4s, $(rhs:0).16b, $(lhs:1).4b[1]
      sdot $(acc:11).4s, $(rhs:1).16b, $(lhs:1).4b[1]
      sdot $(acc:12).4s, $(rhs:0).16b, $(lhs:1).4b[2]
      sdot $(acc:13).4s, $(rhs:1).16b, $(lhs:1).4b[2]
      sdot $(acc:14).4s, $(rhs:0).16b, $(lhs:1).4b[3]
      sdot $(acc:15).4s, $(rhs:1).16b, $(lhs:1).4b[3]
    )ASM";
  return kernel;
}
```
2 files changed
tree: 44082ff396ff2ce6d69f0e5dcd42f9715d1fa275
  1. .github/
  2. benchmarks/
  3. bindings/
  4. build_tools/
  5. colab/
  6. docs/
  7. experimental/
  8. integrations/
  9. iree/
  10. llvm-external-projects/
  11. scripts/
  12. third_party/
  13. .bazelignore
  14. .bazelrc
  15. .bazelversion
  16. .clang-format
  17. .gitignore
  18. .gitmodules
  19. .pylintrc
  20. .style.yapf
  21. .yamllint.yml
  22. AUTHORS
  23. BUILD.bazel
  24. CMakeLists.txt
  25. configure_bazel.py
  26. CONTRIBUTING.md
  27. LICENSE
  28. README.md
  29. WORKSPACE
README.md

IREE: Intermediate Representation Execution Environment

IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.

See our website for project details, user guides, and instructions on building from source.

Project Status

IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!

Communication Channels

Related Project Channels

  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

Build Status

CI SystemBuild SystemPlatformArchitectureConfiguration / ComponentStatus
KokoroBazelLinuxx86-64kokoro status bazel/linux/x86-swiftshader/core
KokoroCMake & BazelLinuxx86-64 (swiftshader)Integrationskokoro status cmake-bazel/linux/x86-swiftshader
KokoroCMake & BazelLinuxx86-64 (turing)Integrationskokoro status cmake-bazel/linux/x86-turing
KokoroCMakeLinuxx86-64 (swiftshader)kokoro status cmake/linux/x86-swiftshader
KokoroCMakeLinuxx86-64 (swiftshader)asankokoro status cmake/linux/x86-swiftshader-asan
KokoroCMakeLinuxx86-64 (turing)kokoro status cmake/linux/x86-turing
KokoroCMakeAndroidarm64-v8aRuntime (build only)kokoro status cmake/android/arm64-v8a
KokoroCMakeBare Metalrisc-v-32Runtimekokoro status cmake/baremetal/riscv32
KokoroCMakeLinuxrisc-v-64Runtimekokoro status cmake/linux/riscv64
BuildkiteCMakeAndroidarm64-v8aRuntimebuildkite status iree-android-arm64-v8a
BuildKiteCMakeAndroidarm64-v8aRuntime Benchmarksbuildkite status iree-benchmark
BuildKiteCMakeLinuxx86-64Tracing + Standalone Runtimebuildkite status iree-build-configurations

Architecture Overview

IREE Architecture

See our website for more information.

Presentations and Talks

  • 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
  • 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
  • 2020-03-18: Interactive HAL IR Walkthrough (recording)
  • 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.