triton-ascend-debugging

Diagnose Triton Ascend kernel issues across compile-time, runtime, and performance stages.

258|48|Updated Jun 22, 2020
One-click install
npx skills add https://github.com/mindspore-ai/akg --skill triton-ascend-debugging-mindspore-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: triton-ascend-debugging
Source: https://github.com/mindspore-ai/akg/tree/main/akg_agents/python/akg_agents/op/resources/skills/triton-ascend/fundamentals/triton-ascend-debugging
Command: npx skills add https://github.com/mindspore-ai/akg --skill triton-ascend-debugging-mindspore-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Triton Ascend debugging checklist and quick-reference for common errors, covering compile-time, runtime, precision, and performance diagnostics; suitable for kernel code generation, locating causes of errors, or verifying code correctness.

Core Features & Use Cases

  • Complete debugging checklist for Triton Ascend kernel development.
  • Memory access and masking consistency checks, boundary protections, and grid/config validations.
  • Control flow verification, slice/index correctness, and concurrency guidelines.
  • Performance and optimization guidance, common error quick-fixes, and regression checks.
  • Use Case: When optimizing a kernel for Atlas A2/A3 hardware, run the checklist to identify and fix issues before deployment.

Quick Start

Run the triton-ascend-debugging checklist against your kernel to identify and diagnose common compile and runtime issues

Frequently Asked Questions about triton-ascend-debugging

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

FAQPage Schema
How do I debug Triton kernel compilation errors on Ascend hardware?

To debug Triton kernel compilation errors on Ascend, apply a structured checklist verifying memory access patterns, control flow logic, and grid configuration to isolate code generation issues before assembly.

Why does my Triton Ascend kernel fail during runtime execution?

Runtime failures in Triton Ascend kernels often stem from boundary protection errors or incorrect slicing. Running diagnostics checks on index correctness and concurrency guidelines helps locate the exact cause.

What is the best way to optimize Triton kernel performance for Atlas A2 hardware?

Optimizing Triton kernel performance for Atlas A2 hardware involves executing regression checks and applying performance guidelines to identify bottlenecks in memory access and concurrency configurations.

Does the Triton Ascend debugging checklist cover precision diagnostics?

Yes, the Triton Ascend debugging checklist covers precision diagnostics by verifying masking consistency and performing control flow checks to ensure code correctness across compile and runtime stages.

Can I use this diagnostics checklist for kernel code generation on Ascend backends?

Yes, you can use this diagnostics checklist for kernel code generation on Ascend backends to validate grid configurations, apply boundary protections, and verify code correctness before deployment.