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User Guide

Last updated: 03/24/2026

Overview

ray-ascend is a community-maintained hardware plugin that supports advanced Ray features on Ascend NPU accelerators.

This guide provides step-by-step instructions for installation, configuration, and usage of ray-ascend's key features:

  • HCCL Collective Communication: Distributed collective operations across Ray actors using Huawei Collective Communication Library
  • YuanRong Direct Transport: Efficient zero-copy transfer of CPU and NPU tensors between Ray actors

Prerequisites

  • Architecture: aarch64, x86
  • OS Kernel: Linux
  • Python: >= 3.10, \<= 3.11
  • Ray: Same version as ray-ascend

Optional dependencies for specific features:

  • CANN == 8.2.rc1: Required for NPU features (HCCL, NPU tensor transport)
  • torch == 2.7.1, torch-npu == 2.7.1.post1: Required for PyTorch NPU support

Quick Start

# Install with YuanRong support
pip install "ray-ascend[yr]"

Contents

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