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gpu-code-review

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Ensure optimal GPU kernel performance and correctness.

Software Engineering#performance#synchronization#memory management#gpu#cuda#kernel review#cuppy
Authorjarmak-personal
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps review GPU kernel code for performance bottlenecks, synchronization issues, and correctness errors before deployment.

Core Features & Use Cases

  • Performance Analysis: Detects anti-patterns, inefficient memory access, and suboptimal configurations for CUDA/NVRTC, CuPy, and CCCL code.
  • Risk Identification: Finds potential memory management, synchronization bugs, and precision problems across diverse GPU architectures.
  • Use Case: Use this to review CUDA source code or runtime pipelines handling large-scale spatial data, ensuring high throughput and correctness.

Quick Start

Use the gpu-code-review Skill to analyze your GPU kernel diffs for residency, synchronization, and performance risks.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: gpu-code-review
Download link: https://github.com/jarmak-personal/vibeSpatial/archive/main.zip#gpu-code-review

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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