dtk-rccl

Configure and troubleshoot RCCL-based distributed training across Hygon DCUs.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/dongg622/china-ai-chip-skill --skill dtk-rccl
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dtk-rccl
Source: https://github.com/dongg622/china-ai-chip-skill/tree/main/Hygon/dtk-rccl
Command: npx skills add https://github.com/dongg622/china-ai-chip-skill --skill dtk-rccl

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill facilitates the deployment and troubleshooting of RCCL-based distributed training setups on Huawei Hygon DCUs, ensuring reliable multi-node communication for AI workloads.

Core Features & Use Cases

  • Distributed Training Deployment: Assist in setting up multi-node RCCL environments for machine learning training across DCUs.
  • Troubleshooting & Optimization: Provide guidance for diagnosing communication issues, optimizing performance, and configuring network connections like XGMI.
  • Use Case: An engineer needs to deploy multi-node AI training on a Hygon DCU cluster; this Skill streamlines environment setup, persists configuration, and offers troubleshooting steps.

Quick Start

Load the environment, verify RCCL library availability, and follow the step-by-step commands to initialize and test multi-node communications with detailed diagnostics.

Frequently Asked Questions about dtk-rccl

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up multi-node distributed training on Hygon DCUs?

Multi-node distributed training on Hygon DCUs requires configuring RCCL environments across multiple nodes. This Skill provides step-by-step commands to initialize environments, verify RCCL library availability, and test multi-node communications for AI training workflows.

Why is RCCL communication failing across multiple DCUs during training?

RCCL communication failures across DCUs often stem from network configuration or XGMI connection issues. This Skill assists in diagnosing multi-node communication problems and provides troubleshooting steps to resolve network connections for reliable distributed training.

Can I optimize multi-node communication performance for Hygon DCU clusters?

Yes, you can optimize multi-node communication performance for Hygon DCU clusters. This Skill provides guidance for diagnosing communication issues, optimizing performance, and configuring network connections like XGMI to ensure efficient AI training.

What is RCCL used for in distributed AI training?

RCCL is used for efficient multi-node communication in distributed AI training. This Skill facilitates RCCL-based setup and troubleshooting across multiple Hygon DCUs, ensuring reliable communication and performance optimization for machine learning workloads.

Do I need specific network configurations for RCCL distributed training on DCUs?

RCCL distributed training on DCUs requires specific network configurations like XGMI. This Skill streamlines environment setup, persists configuration details, and offers troubleshooting steps to ensure proper network connections for multi-node training.

What's the best way to troubleshoot RCCL environment setup on Hygon DCU?

The best way to troubleshoot RCCL environment setup is to load the environment, verify library availability, and run detailed diagnostics. This Skill provides step-by-step commands to initialize and test multi-node communications effectively.