Commit Graph

5 Commits

Author SHA1 Message Date
Binyang Li
eeea00b298 Support python wheel build (#787)
## Support Python wheel build

This PR modernizes the Python packaging for MSCCL++ by defining
dependencies and optional extras in `pyproject.toml`, enabling proper
wheel builds with `pip install ".[cuda12]"`.

### Changes

**`pyproject.toml`**
- Add `dependencies` (numpy, blake3, pybind11, sortedcontainers)
- Add `optional-dependencies` for platform-specific CuPy (`cuda11`,
`cuda12`, `cuda13`, `rocm6`), `benchmark`, and `test` extras
- Bump minimum Python version from 3.8 to 3.10

**`test/deploy/setup.sh`**
- Use `pip install ".[<platform>,benchmark,test]"` instead of separate
`pip install -r requirements_*.txt` + `pip install .` steps
- Add missing CUDA 13 case

**`docs/quickstart.md`**
- Update install instructions to use extras (e.g., `pip install
".[cuda12]"`)
- Document all available extras and clarify that `rocm6` builds CuPy
from source
- Update Python version references to 3.10

**`python/csrc/CMakeLists.txt`**, **`python/test/CMakeLists.txt`**
- Update `find_package(Python)` from 3.8 to 3.10

### Notes
- The `requirements_*.txt` files are kept for Docker base image builds
where only dependencies (not the project itself) should be installed.
- CuPy is intentionally not in base dependencies — users must specify a
platform extra to get the correct pre-built wheel (or source build for
ROCm).

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-16 21:24:45 -07:00
Binyang Li
a707273701 Torch integration (#692)
Reorganize current native algorithm implementation and DSL algorithm
implementation.
Provide unified API for DSL algo and native algo and provide interface
to tune the algo
Provide interface for pytorch integration with native API and DSL

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: chhwang <8018170+chhwang@users.noreply.github.com>
2026-01-21 20:32:24 -08:00
Binyang Li
5acac93dbc Integrate MSCCL++ DSL to torch workload (#620)
Provides two integration ways for MSCCL++ DSL.
1. Integrate with customized communication group
2. Integrate with NCCL API

Introduce new Python APIs to make it work:
```python
mscclpp.compile # compile dsl to json based execution plan
mscclpp.ExecutionPlanRegistry.register_plan(plan) # register the compiled plan to executionPlanRegistery
mscclpp.ExecutionPlanRegistry.set_selector(selector) # set the selector, the selector will return the best execution plan based on collection, message size, world size....
```
Fix #556

---------

Co-authored-by: Caio Rocha <caiorocha@microsoft.com>
Co-authored-by: Changho Hwang <changhohwang@microsoft.com>
2025-10-29 15:39:00 -07:00
Binyang Li
be6a941fba New DSL implementation (#579)
The PR contains following changes:
Python side:
- Channel based DSL implementation: decouple channel with chunk.
- Users create channel explicitly, only need local_rank, remote_rank and
channel_type
- Adjust executor json file, add remote_buffer fields, different op can
use different channel and remote buffers combination.
- Reimplement operation fusion, data dependency check mechanism
- Add new op such as semaphore, pipeline 
- Clean code and enhance document
C++ side: 
- Support new execution file json format
- Support semaphore and pipeline operation
- code clean, support non-zero copy scenario

---------

Co-authored-by: Caio Rocha <caiorocha@microsoft.com>
Co-authored-by: Changho Hwang <changhohwang@microsoft.com>
2025-08-09 00:36:20 -07:00
Changho Hwang
1a7cb98e3a v0.4.3 (#279) 2024-03-27 11:53:09 -07:00