## Summary
- **Add `fp8_e4m3b15` datatype**: A software-defined FP8 type with 4
exponent bits, 3 mantissa bits, and bias=15 (max finite value: 0.9375).
Implemented entirely in software with no HW dependency, using
Triton-style bit manipulation through fp16 as intermediate for efficient
conversion.
- **Add mixed-precision accumulation for allreduce**: All allreduce
algorithm variants (packet, NVLS packet, fullmesh, RSAG zero-copy, and
others) now support a configurable `accumDtype` parameter, enabling FP8
inputs to be reduced in float16 or float32 for higher accuracy.
- **Propagate `accumDtype` through the full API**: The new parameter is
threaded from `Algorithm::execute()` → `NativeAlgorithm` → `KernelFunc`
→ dispatch → CUDA kernels, with `DataType::AUTO` as the default
(resolves to input dtype at runtime).
- **Add FP8 accumulation correctness tests**: New `test_fp8_accum.py`
validates that higher-precision accumulation produces results at least
as accurate as native FP8 accumulation across multiple algorithms and
sizes. Skipped on CUDA SM < 89 (pre-Hopper); runs on HIP/ROCm.
- **Add `test_fp8_accum.py` to CI**: Azure Pipeline `ut.yml` now runs
FP8 accumulation tests alongside existing pytests.
- **NCCL shim logging cleanup**: Migrated `printf`-style `WARN`/`INFO`
calls to streaming-style logging.
## Key files
| Area | Files |
|------|-------|
| New datatype + vector ops | `include/mscclpp/gpu_data_types.hpp` |
| Accumulation reduce helpers | `src/core/include/reduce_kernel.hpp` |
| Algorithm API (`accumDtype`) | `include/mscclpp/algorithm.hpp`,
`src/core/algorithm.cc` |
| Allreduce kernels | `src/ext/collectives/allreduce/*.cu` |
| Dispatch + common | `src/ext/collectives/include/allreduce/common.hpp`
|
| Python bindings | `python/csrc/algorithm.cpp`,
`python/mscclpp/_core/algorithm.py` |
| Tests | `python/test/test_fp8_accum.py` |
| CI | `.azure-pipelines/templates/ut.yml` |
## Test plan
- [x] CI passes on H100 (CUDA SM 90) — full FP8 E4M3 + E4M3B15
accumulation tests
- [x] CI passes on A100 (CUDA SM 80) — FP8 tests correctly skipped
- [x] CI passes on MI300X (ROCm) — FP8 tests run via HIP
- [x] Existing `test_mscclpp.py` tests continue to pass
- [x] NCCL shim builds and runs correctly with new `accumDtype` defaults
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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>
