gpu-ai-infrastructure-skills
🔌PluginAmey-Thakur/AI-SKILLS
|20 working methods for gpu ai infrastructure: ai-datacenter-networking, checkpointing-large-training, cuda-kernel-basics, distributed-training-scaling, and more
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Amey-Thakur/AI-SKILLS
Installation
/plugin marketplace add Amey-Thakur/AI-SKILLS/plugin install gpu-ai-infrastructure-skills@ai-skillsMore from this repository10
1 working methods for apis: api-design, and more
28 working methods for performance: algorithmic-optimization, async-io-patterns, batching-and-debouncing, benchmark-design, and more
41 working methods for testing: api-testing, approval-testing, assertion-libraries, bdd-scenarios, and more
5 working methods for llm engineering: agent-memory, mcp-server, prompt-engineering, rag-pipeline, and more
4 working methods for devops: ci-cd, containerization, dependency-management, incident-postmortem, and more
1 working methods for accessibility: accessibility-review, and more
43 working methods for security: api-security, audit-logging, authn-design, authz-design, and more
28 working methods for big tech processes: architecture-review-board, bar-raiser-interviewing, canary-analysis, chaos-gameday, and more
1 working methods for research thinking: research-synthesis, and more
2 working methods for frontend: design-systems, frontend-state, and more