| commit | fe571e4d5efde141ec437cb4699307df67a38b9c | [log] [tgz] |
|---|---|---|
| author | Benjamin Maxwell <benjamin.maxwell@arm.com> | Mon Jun 24 19:05:55 2024 +0100 |
| committer | GitHub <noreply@github.com> | Mon Jun 24 11:05:55 2024 -0700 |
| tree | 6d585275ed1944445fb0a93201bc3c4c44a6a9a7 | |
| parent | 024c48b23c0e8721d94e544fa78bcfd291afa439 [diff] |
[LLVMCPU][ArmSME] Rework how Arm streaming mode is set on dispatches (#17646) Previously, when the `+sme` feature flag was set Armv9 streaming SVE mode would be enabled for all dispatch regions lowered with the following experts: - `CPUBufferOpsTileAndVectorize` - `CPUConvTileAndDecomposeExpert` - `CPUDoubleTilingExpert` This was not ideal as meant streaming mode could be added to dispatch regions that made no use of scalable vectors, where the (possibly) larger streaming vector length provides no benefit, and there may be a cost due to other overheads. There was also a flag `--iree-experimental-llvmcpu-arm-force-ssve` which contrary to its name _did not_ force streaming SVE mode. What this flag did do was disable tiling for 2D scalable ArmSME operations, then rely on something else later on setting the streaming mode (but it did not control it). The patch aims to add clearer and more directed ways to enable streaming mode. First, streaming mode is no longer set in any lowering experts (it's a fairly low-level concept, that does not need to be configured early in the pipeline). Second, the old `--iree-experimental-llvmcpu-arm-force-ssve` flag is removed. Now to control tiling for ArmSME and using streaming mode there are two new flags. `iree-llvmcpu-disable-arm-sme-tiling`: This disables tiling for ArmSME (i.e. using 2D scalable tile sizes), even when the `+sme` feature flag is set. This results in operations instead being tiled for SVE or Neon (depending on the configuration). `iree-llvmcpu-force-arm-streaming`: This enables Arm streaming mode for any dispatch regions that contain scalable vectors. It ignores dispatches that don't contain scalable vectors as enabling streaming mode would provide no benefit. ci-extra: build_test_all_arm64 --------- Signed-off-by: Benjamin Maxwell <benjamin.maxwell@arm.com>
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.
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!
See our website for more information.
Community meeting recordings: IREE YouTube channel
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.