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
78ce9fac8d
Fix ci pipeline failure ( #729 )
2026-01-21 13:28:14 -05:00
Changho Hwang
8b8593ba51
Fix Python bindings and tests ( #690 )
...
Minimal fix to make things work. We need a more careful look at
preventing silent fallback of nanobind when it fails to (properly)
construct a C++ STL object with mscclpp instances.
2025-11-21 12:53:12 -08:00
Binyang Li
4f6f23dae3
Use smart pointer for IB structure ( #585 )
...
Change to use smart pointer for IB structure. Registered memory will own
ibMr, ibCtx will not held the reference
- Use smart pointer for IbQp and IbMr
- Update memoryChannel API, keep localRegisteredMemory
- Close fd when registedMemory released
---------
Co-authored-by: Changho Hwang <changhohwang@microsoft.com >
2025-08-06 10:01:58 -07:00
Binyang Li
658411ccc4
update pytest and python API to fix ut failure ( #598 )
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update pytest and python API to fix ut failure
2025-08-05 15:17:33 -07:00
Changho Hwang
3565bfdf6d
Renaming channels ( #436 )
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Renamed `ProxyChannel` to `PortChannel` and `SmChannel` to
`MemoryChannel`
2025-01-24 14:25:31 -08:00
Changho Hwang
34945fb107
Add GpuBuffer class ( #423 )
...
* Renamed and moved mem alloc functions into the `mscclpp::detail::`
namespace (now `mscclpp::detail::gpuCalloc*<T>()`)
* Deprecated constructor-calling mem alloc functions
(`mscclpp::makeShared*<T>()` and `mscclpp::makeUnique*<T>()`)
* Added a new `mscclpp::GpuBuffer<T>()` class that should be used in
general for allocating communication buffers
* Added a new `mscclpp.utils.GpuBuffer` Python class that inherits
`cupy.ndarray` and allocates using `mscclpp::gpuMemAlloc`
* Renamed `mscclpp::memcpyCuda*<T>()` functions into
`mscclpp::gpuMemcpy*<T>()` for name consistency
* A few fixes in NVLS memory allocation
* Tackled minor compiler warnings
2025-01-07 18:40:01 -08:00
Binyang Li
28a57b0610
NVLS support for msccl++ executor ( #375 )
...
- Support mote datatype for multicast operation
- Add new OP MULTI_LOAD_REDUCE_STORE to support NVLS
- Modify allocSharedPhysicalCuda, which return std::shared_ptr<T>
instead of std::shared_ptr<PhysicalCudaMemory>
- Add Python support for allocSharedPhysicalCuda
Test passed for `allreduce_nvls.json`
2024-11-20 06:43:28 +00:00
Roshan Dathathri
7ed13ec4b5
Auto-tune vector sizes for NVLS allreduce6 ( #338 )
...
Also fixes bugs in MscclppAllReduce6
Below is the performance when the algorithm is fixed to
MscclppAllReduce6 on 8 H100 GPUs connected with NVLink using CUDA 12.2.
Float16:
+-------------+-----------+--------------+-------------+----------------+-------------------+------------------+----------+
| Size (fp16) | Time (us) | AlgBW (GB/s) | Correctness | NCCL Time (us)
| NCCL AlgBW (GB/s) | NCCL Correctness | Speed Up |
+-------------+-----------+--------------+-------------+----------------+-------------------+------------------+----------+
| 2.0 KiB | 11.15 | 0.18 | PASS | 13.82 | 0.15 | PASS | 1.24 |
| 4.0 KiB | 11.15 | 0.37 | PASS | 14.74 | 0.28 | PASS | 1.32 |
| 8.0 KiB | 11.14 | 0.74 | PASS | 15.17 | 0.54 | PASS | 1.36 |
| 16.0 KiB | 11.16 | 1.47 | PASS | 15.77 | 1.04 | PASS | 1.41 |
| 32.0 KiB | 11.15 | 2.94 | PASS | 17.50 | 1.87 | PASS | 1.57 |
| 64.0 KiB | 11.18 | 5.86 | PASS | 17.64 | 3.71 | PASS | 1.58 |
| 128.0 KiB | 11.16 | 11.74 | PASS | 17.83 | 7.35 | PASS | 1.60 |
| 256.0 KiB | 11.21 | 23.38 | PASS | 18.00 | 14.57 | PASS | 1.60 |
| 512.0 KiB | 11.70 | 44.81 | PASS | 18.42 | 28.46 | PASS | 1.57 |
| 1.0 MiB | 13.64 | 76.87 | PASS | 20.23 | 51.83 | PASS | 1.48 |
| 2.0 MiB | 17.29 | 121.27 | PASS | 31.60 | 66.36 | PASS | 1.83 |
| 4.0 MiB | 25.26 | 166.02 | PASS | 38.74 | 108.26 | PASS | 1.53 |
| 8.0 MiB | 40.17 | 208.83 | PASS | 62.86 | 133.45 | PASS | 1.56 |
| 16.0 MiB | 70.92 | 236.56 | PASS | 113.36 | 147.99 | PASS | 1.60 |
| 32.0 MiB | 131.38 | 255.41 | PASS | 203.21 | 165.13 | PASS | 1.55 |
| 64.0 MiB | 253.39 | 264.84 | PASS | 342.12 | 196.15 | PASS | 1.35 |
| 128.0 MiB | 496.74 | 270.20 | PASS | 670.62 | 200.14 | PASS | 1.35 |
| 256.0 MiB | 982.42 | 273.24 | PASS | 1318.36 | 203.61 | PASS | 1.34 |
+-------------+-----------+--------------+-------------+----------------+-------------------+------------------+----------+
Float32:
+-------------+-----------+--------------+-------------+----------------+-------------------+------------------+----------+
| Size (fp32) | Time (us) | AlgBW (GB/s) | Correctness | NCCL Time (us)
| NCCL AlgBW (GB/s) | NCCL Correctness | Speed Up |
+-------------+-----------+--------------+-------------+----------------+-------------------+------------------+----------+
| 4.0 KiB | 11.04 | 0.37 | PASS | 14.79 | 0.28 | PASS | 1.34 |
| 8.0 KiB | 11.15 | 0.73 | PASS | 15.25 | 0.54 | PASS | 1.37 |
| 16.0 KiB | 11.12 | 1.47 | PASS | 15.87 | 1.03 | PASS | 1.43 |
| 32.0 KiB | 11.13 | 2.95 | PASS | 17.21 | 1.90 | PASS | 1.55 |
| 64.0 KiB | 11.11 | 5.90 | PASS | 17.37 | 3.77 | PASS | 1.56 |
| 128.0 KiB | 11.08 | 11.83 | PASS | 17.54 | 7.47 | PASS | 1.58 |
| 256.0 KiB | 11.15 | 23.50 | PASS | 17.71 | 14.80 | PASS | 1.59 |
| 512.0 KiB | 11.56 | 45.34 | PASS | 18.21 | 28.79 | PASS | 1.57 |
| 1.0 MiB | 13.64 | 76.90 | PASS | 19.87 | 52.77 | PASS | 1.46 |
| 2.0 MiB | 17.24 | 121.67 | PASS | 31.63 | 66.30 | PASS | 1.84 |
| 4.0 MiB | 25.19 | 166.47 | PASS | 38.63 | 108.57 | PASS | 1.53 |
| 8.0 MiB | 40.38 | 207.72 | PASS | 62.65 | 133.89 | PASS | 1.55 |
| 16.0 MiB | 70.72 | 237.23 | PASS | 114.57 | 146.44 | PASS | 1.62 |
| 32.0 MiB | 131.49 | 255.18 | PASS | 200.79 | 167.11 | PASS | 1.53 |
| 64.0 MiB | 253.98 | 264.23 | PASS | 342.58 | 195.89 | PASS | 1.35 |
| 128.0 MiB | 496.96 | 270.08 | PASS | 670.64 | 200.13 | PASS | 1.35 |
| 256.0 MiB | 982.83 | 273.12 | PASS | 1318.90 | 203.53 | PASS | 1.34 |
| 512.0 MiB | 1954.07 | 274.75 | PASS | 2609.04 | 205.77 | PASS | 1.34 |
+-------------+-----------+--------------+-------------+----------------+-------------------+------------------+----------+
2024-08-16 11:11:54 +08:00
Binyang Li
5971508eed
Remove cuda-python from project ( #245 )
...
Remove cuda-python and use CuPy APIs instead
---------
Co-authored-by: Changho Hwang <changhohwang@microsoft.com >
2024-02-13 21:44:11 +08:00
Saeed Maleki
91d592dcc0
NVLS support. ( #250 )
...
Co-authored-by: Saeed Maleki <saemal@microsoft.com >
Co-authored-by: Binyang Li <binyli@microsoft.com >
Co-authored-by: Changho Hwang <changhohwang@microsoft.com >
2024-02-04 20:46:10 -08:00
Changho Hwang
7bd66a938c
Robust correctness test ( #221 )
...
Co-authored-by: Aashaka Shah <aashaka96@gmail.com >
2023-11-22 12:06:50 +08:00
