FastCuda Skill
FastCuda is a Cuda AI agent skill for Codex. FastCuda is a handwritten CUDA operator library featuring progressive GEMM and Reduce kernels, cuBLAS benchmarking, and C/C++/Python interfaces for learning, profiling, and performance optimization.
How to use FastCuda Skill
Compatible clients
What is FastCuda Skill?
FastCuda is a Cuda AI agent skill for Codex. FastCuda is a handwritten CUDA operator library featuring progressive GEMM and Reduce kernels, cuBLAS benchmarking, and C/C++/Python interfaces for learning, profiling, and performance optimization. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Reusable instructions support
- Includes SKILL.md support
- Shell commands support
- Document generation support
- .codex/skills/ncu-profiling/SKILL.md config support
- .codex/skills/benchmark-harness/SKILL.md config support
- .codex/skills/cuda-env-audit/SKILL.md config support
Technical details
- Built for Cuda
- Built for Python
- Works with Codex
- Network access
Requirements and access
Security and permissions
Review permissions before connecting any MCP server to an agent. Pay special attention to whether it can read local files, write data, call external services, or perform destructive actions.
When to use FastCuda Skill
- Use it for reusing agent instructions, scripts, and references.
- Use it for agent skills workflows.
- Use it for design workflows.
- Use it for documentation workflows.
- Use it for codex users.
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Frequently asked questions
What is FastCuda?
FastCuda is a Cuda AI agent skill for Codex. FastCuda is a handwritten CUDA operator library featuring progressive GEMM and Reduce kernels, cuBLAS benchmarking, and C/C++/Python interfaces for learning, profiling, and performance optimization.
Who is FastCuda best for?
FastCuda is best for reusing agent instructions, scripts, and references, agent skills workflows, design workflows, documentation workflows, codex users.
How do I install FastCuda?
Check the FastCuda GitHub repository for installation instructions.
Is FastCuda actively maintained?
FastCuda may need a closer maintenance check before production use.
Auto-fetched from GitHub.
