dreamlab-ai CUDA Specialist Skill
AI-powered CUDA development assistant integrating 4 specialist agents with comprehensive GPU development tools.
When Not To Use
- For high-level PyTorch model training that does not need custom kernels -- use the pytorch-ml skill instead
- For distributed neural network training in cloud sandboxes -- use the flow-nexus-neural skill instead
- For general Rust or C++ systems programming without GPU involvement -- use the rust-development skill instead
- For WebAssembly-based compute without GPU -- use the wasm-js skill instead
- For CPU-only performance profiling of swarm operations -- use the performance-analysis skill instead
Overview
The CUDA skill brings professional CUDA development capabilities to Claude Code through:
- 4 AI Specialist Agents: General, Optimizer, Debugger, Analyzer
- CUDA Compilation: nvcc integration with auto-architecture detection
- Kernel Analysis: Pattern detection and optimisation opportunities
- GPU Profiling: Performance measurement and bottleneck identification
- Code Generation: Create optimised kernels from specifications
Reference Files
Load the reference that matches the task:
- references/agents.md — the 4 specialist agents (General, Optimizer, Debugger, Analyzer): when to use each and invocation examples.
- references/mcp-tools.md — full MCP tool catalogue (kernel dev, GPU management, agent routing, file ops) plus JSON call examples.
- references/environment.md — CUDA toolkit checks, container GPUs, and PyTorch CUDA verification.
- references/examples.md — quick-start prompts and integration patterns with PyTorch and Rust skills.
- references/optimisation.md — performance checklist, advanced compilation flags, nsys/ncu profiling, benchmarking, and best practices.
- references/troubleshooting.md — fixes for CUDA-not-found, GPU-not-accessible, and compilation errors.
Related Skills
- pytorch-ml - Deep learning with PyTorch + CUDA
- rust-development - Safe CUDA bindings in Rust
- docker-orchestrator - Deploy GPU containers
- infrastructure-manager - Provision GPU cloud instances
References
Skill Status: Production Ready CUDA Support: 11.0 - 13.0 GPU Architectures: Pascal, Volta, Turing, Ampere, Ada Lovelace, Hopper Container GPUs: 3x (RTX A6000 + 2x RTX 6000 Ada Generation) — sm_86 (A6000) + sm_89 (Ada Generation)