Based on the discussion in #700, this PR enables downloading pybind11 in
`setup.py` without `git submodule` instead of copy-pasting pybind11
code. The downloaded pybind11 will be in `~/.triton/pybind` (like
`llvm`).
This PR changes the `pybind11` source code management from copy-paste to
a package controlled by git-submodule.
See the discussion in #694 for details.
This is a more stable commit that produce bitwise identical code to earlier
versions. Using commits after this one may lead to slightly different numerics
I've been using this locally to find errors without running tests, and now that we're using autopep8, it passes with minimal suppressions. This is also what turned up the issues with the tutorials, which were fixed in #422.
- Fix meta-parameter usage on tutorials.
- Install tutorial dependencies on CI.
- Switch from `requirements-test.txt` to `extras_require` for test dependencies, and also use it for tutorial dependencies.
- Make some performance tests deterministic.
Run:
```
isort ./python
autopep8 -i --ignore E501,E701,E731 $(find ./python/ -name '*.py')
```
with an `.isort.cfg` and then clean up a few warts. This PR should be a no-op; the idea is that this is all boring whitespace changes, and any config file changes will be in a different change to make it easier to review.
This PR adds a BF16 data-type, along with FP32 <-> BF16 conversion instructions in the LLVM codegen. Other kinds of ops on bfloat16 are not yet supported.
This PR implements a major overhaul of the frontend for Triton, and replaces Triton-C by a pure Python API in which kernels are defined as @triton.jit decorated functions. The documentation and tutorials have also been updated to accommodate these changes.
See documentations for more information on the new API
The solution proposed in #77 can create namespace conflicts when triton and triton-nightly have both been pip installed. Therefore, this PR is moving nightly releases to pre-releases in the main triton index.
Recently there has been more and more report about installation issues:
- Installing Triton before upgrading pytorch can create some issues because Triton uses some torch headers
- llvm-10-dev not available on some platform; llvm-11-dev not available on e.g. Ubuntu.
absence of nightly builds
This PR should fix all these issues. Some CMake tricks are used to download and install llvm at build time. Triton Python bindings were modified to remove dependence on pytorch ops. Midnight CI job added to generate binary wheels for all Triton version and update them on pypi's new triton-nightly project.
This PR will also make it very easy to use LLVM forks in the future for whatever needs we have.
Before this commit, the benchmarking infrastructure used heterogeneous protocols between library (e.g., CUTLASS uses a C++ binary that reports mean TFLOPS; torch and triton use python call and report 10th, 50th and 90th quantiles). For the sake of uniformity and fair benchmark practices, this PR adds a python wrapper for auto-tuned CUTLASS matrix multiplication. Benchmarks have been rewritten to use this wrapper with `triton.testing.do_bench` rather than system calls to CUTLASS profiler. Importantly, this also ensures that all the matmuls are done on the *same* input data which should stabilize clock across providers.
Improved handling of asynchronous copy, scheduling and synchronization for A100. Now achieving CUTLASS-like performance on large square dense matrix multiplication tasks
This adds a bench functionality to the setup.py that can be used to run the benchmark suite and generates a bunch of csv files (and optionally plots)
python setup.py bench
python setup.py bench --with-plots
python setup.py bench --filter=cross_entropy
