with one click
diffusion-kernel
Index for SGLang Diffusion kernel development skills.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Menu
Index for SGLang Diffusion kernel development skills.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
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.