xe2-sdp-hd256
xe2-sdp-hd256 is an MLOps & model serving skill for AI agents, published by ModelTC in the LightX2V repository on GitHub. Skillspace rates xe2-sdp-hd256 C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill when writing, optimizing, benchmarking, or debugging Flash Attention SDP kernels with head dimension 256 (HD=256) targeting Intel Xe2 (Lunar Lake/LNL, Battlemage/BMG) GPU using SYCL ESIMD. Xe2 is the GPU architecture; LNL and BMG are product names. Covers the S^T (transposed scores) architecture, oneDNN-inspired v2 kernel design, GQA support, softmax optimization, lsc_slm_scatter S transpose elimination, ISA-level analysis, and the complete optimization journey from 64 to 88 TFLOPS. Use whenever the user mentions HD=256 SDP, head_dim=256 attention, rev256, onednn_v2 kernel, S transpose, s_scatter, s_gather, lsc_slm_scatter, lsc_slm_gather, or large head dimension flash attention on Intel GPU.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 2,499
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 98 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Intel Xe2 GPU and SYCL ESIMD kernel knowledge, platform-specific not repo-specific
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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