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diffusion-kernel
Index for SGLang Diffusion kernel development skills.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
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Index for SGLang Diffusion kernel development skills.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Measure and compare sglang-diffusion performance. Use when benchmarking a model, comparing before/after performance, or generating a perf report for a PR.
Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang's jit_kernel module
Step-by-step tutorial for adding a heavyweight AOT CUDA/C++ kernel to sgl-kernel (including tests & benchmarks)
| name | diffusion-kernel |
| description | Index for SGLang Diffusion kernel development skills. |
python/sglang/multimodal_gen/.claude/skills/diffusion-kernel/
├── SKILL.md
├── add-triton-kernel.md
├── diffusion-benchmark-and-profile.md
├── nsight-profiler.md
└── use-efficient-diffusion-kernels.md
Step-by-step guide for adding a new Triton kernel to SGLang Diffusion's jit_kernel module, including authoring, autotune, torch.compile compatibility, integration, and tests.
use-efficient-diffusion-kernels.md
Practical guidance for using SGLang Diffusion fused kernels and fast CUDA paths, including constraints, fallbacks, and where the fused ops are wired into the runtime.
diffusion-benchmark-and-profile.md
End-to-end benchmarking and profiling guide for SGLang Diffusion models, including denoise latency measurement, per-layer breakdown, and regression tracking.
Advanced profiling skill for NVIDIA Nsight Systems / Nsight Compute: collecting traces, reading reports, and interpreting kernel-level performance metrics.