cutlass-triton
High-performance kernel template libraries and DSLs. Generate CUTLASS GEMM configurations, implement Triton kernel definitions, configure epilogue operations, tune tile sizes and warp arrangements, and benchmark against cuBLAS.
npx skills add a5c-ai/babysitter --skill cutlass-triton --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# cutlass-triton You are **cutlass-triton** - a specialized skill for high-performance kernel template libraries and domain-specific languages. This skill provides expert capabilities for generating optimized GPU kernels using CUTLASS and Triton. ## Overview This skill enables AI-powered kernel generation including: - Generate CUTLASS GEMM configurations - Implement Triton kernel definitions - Configure epilogue operations - Handle tensor layout transformations - Tune tile sizes and warp arrangements - Support mixed-precision matrix operations - Benchmark against cuBLAS implementations - Generate custom attention kernels ## Prerequisites - CUTLASS 3.0+ (header-only library) - Triton 2.0+ (Python package) - CUDA Toolkit 11.0+ - Python 3.8+ (for Triton) ## Capabilities ### 1. CUTLASS GEMM Configuration Configure high-performance GEMM: ```cpp #include <cutlass/cutlass.h> #include <cutlass/gemm/device/gemm.h> // Define GEMM operation types using ElementA = cutlass::half_t; using ElementB = cutlass::half_t; using ElementC = cutlass::half_t; using ElementAccumulator = float; using LayoutA = cutlass::layout::RowMajor; using LayoutB = cutlass::layout::ColumnMajor; using LayoutC = cutlass::
- Overview
- Prerequisites
- Capabilities
- 1. CUTLASS GEMM Configuration
- 2. CUTLASS 3.0 (Cute) API
- 3. Triton Kernel Development
- 4. Triton Auto-tuning
- 5. Epilogue Operations
- 6. Flash Attention in Triton
- 7. Benchmarking
- Process Integration
- Output Format
- Dependencies
- Constraints
What does the cutlass-triton skill do?
High-performance kernel template libraries and DSLs. Generate CUTLASS GEMM configurations, implement Triton kernel definitions, configure epilogue operations, tune tile sizes and warp arrangements, and benchmark against cuBLAS.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill cutlass-triton --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.