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kebab
kebab에는 LancerLab에서 수집한 skills 6개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Run operator benchmarks and single-run executables in Kebab for GEMM and elementwise add. Use when asked to execute performance baselines, compare implementations, or run quick correctness/perf checks through Make targets.
Build and bootstrap the Kebab project on Linux with CUDA, CMake, and Makefile workflows. Use when asked to set up dependencies, detect CUDA/GPU architecture, configure builds, or fix compilation environment issues.
Navigate and modify the Kebab CUDA codebase safely. Use when asked to locate GEMM, CuTe, CUDA baseline, benchmark, microbenchmark, profiling, or build logic in this repository, and when deciding where a change should be implemented.
Tune GEMM experiment settings in Kebab using config.yaml and optimization docs. Use when asked to adjust matrix sizes, precision, layout modes, tile sizes, kernel versions, or to design reproducible performance experiments.
Execute Kebab microbenchmarks and generate PTX/SASS dumps for kernel-level analysis. Use when asked to run mbench targets, inspect assembly output, compare copy or MMA kernels, or analyze low-level code generation.
Profile Kebab kernels with Nsight Compute and export readable reports. Use when asked to run tune/mtune targets, collect NCU reports, convert .ncu-rep to text summaries, or troubleshoot performance bottlenecks.