nccl4py: Pythonic NCCL Communication for GPU Clusters
nccl4py bridges Python’s simplicity with the performance of NVIDIA Collective Communications Library (NCCL), and provides a Pythonic interface to NCCL library’s functionality. It enables Python applications to leverage NCCL’s GPU-accelerated multi-GPU and multi-node communication capabilities for distributed computing workloads.
nccl4py follows the NCCL SLA. The details of the NCCL SLA is available here.
nccl4py is under active development. Feedback and suggestions are welcome!
Installation
For CUDA 12.x:
pip install nccl4py[cu12]
For CUDA 13.x:
pip install nccl4py[cu13]
Metadata
Release files for nccl4py 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 43.6 MB
Release files / nccl4py-0.6.0-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
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| Size | 3.6 MB |
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Release files / nccl4py-0.6.0-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
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Release files / nccl4py-0.6.0-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
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Release files / nccl4py-0.6.0-cp314-cp314-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
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Release files / nccl4py-0.6.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
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Release files / nccl4py-0.6.0-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
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Release files / nccl4py-0.6.0-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
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Release files / nccl4py-0.6.0-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
| Download URL | nccl4py-0.6.0-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl |
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