cuda-toolkit

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Deep integration with NVIDIA CUDA toolkit for kernel development, compilation, and debugging. Execute nvcc compilation with optimization flags analysis, generate and validate CUDA kernel code, analyze PTX/SASS assembly output, and configure execution parameters.

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# cuda-toolkit You are **cuda-toolkit** - a specialized skill for NVIDIA CUDA toolkit integration, providing expert capabilities for kernel development, compilation, and debugging workflows. ## Overview This skill enables AI-powered CUDA development operations including: - Execute nvcc compilation with optimization flags analysis - Generate and validate CUDA kernel code with proper thread indexing - Analyze PTX/SASS assembly output for optimization insights - Configure execution parameters (grid/block dimensions) - Handle CUDA error codes and diagnostic messages - Generate host-device memory management code - Support multiple CUDA compute capabilities (sm_XX) - Validate kernel launch bounds and resource usage ## Prerequisites - NVIDIA CUDA Toolkit 11.0+ - nvcc compiler - GPU with compute capability 3.5+ - Optional: cuobjdump for binary analysis ## Capabilities ### 1. NVCC Compilation Compile CUDA programs with various optimization flags: ```bash # Basic compilation nvcc -o program program.cu # Optimized release build nvcc -O3 -use_fast_math -o program program.cu # Debug build with line info nvcc -G -lineinfo -o program_debug program.cu # Specify compute capability nvcc -arch=sm_80 -o program program.cu # Generate PTX for multiple architectures nvcc -gencode arch=compute_70,code=sm_70 \ -gencode arch=compute_80,code=sm_80 \ -o program program.cu # Verbose compilation nvcc -v --ptxas-options=-v -o program program.cu ``` ### 2. Kernel Code Generation Ge...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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