commit | 23666a604206fee145b5575f76d3a803f3448671 | [log] [tgz] |
---|---|---|
author | Nicolas Vasilache <nicolasvasilache@users.noreply.github.com> | Mon Jun 12 12:59:51 2023 +0200 |
committer | GitHub <noreply@github.com> | Mon Jun 12 10:59:51 2023 +0000 |
tree | 4ed7ed3aec2de0be634d287171c882ebf3c2534c | |
parent | 88920b4e90510cc647787e95de15be13c7a11e5b [diff] |
Add a new benchmark and document steps: Add a new unaligned matmul test that will exercise failsafes to avoid bad configurations (#14052) For future reference, here are the steps required to add a new matmul benchmark to IREE. Most are described in `build_tools/python/e2e_test_framework/models/README.md`, this is a more hand-holdey version to add specific matmul benchmarks as IREE currently adds them: Step 1. Add a new entry to model_groups.py Step 2. Generate uuid with python: ``` python import uuid uuid.uuid4() ``` Step 3. Add an entry and plug UUID in `build_tools/python/e2e_test_framework/unique_ids.py` Step 4. Run `echo "$(date +'%Y%m%d')_$(date +'%s')"` to get a date + timestamp. Step 5. Add an entry to `build_tools/python/e2e_test_framework/models/matmul.py` using the date + timestamp directory name. Step 6. Write the desired .mlir and generate an a .mlirbc with `iree-opt --emit-bytecode` Step 7. Upload the .mlirbc to the GCS directory `https://storage.googleapis.com/iree-model-artifacts/microbenchmarks/matmul/timestamp/` with timestamp created in Step 5. Step 8. Run `build_tools/scripts/generate_cmake_files.sh` Step 9. Commit everything.
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.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.