geko-hipblaslt-tuning SKILL.md skillA
geko-hipblaslt-tuning from amd-agi/hyperloom is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add amd-agi/hyperloom/geko-hipblaslt-tuning@git:20261105.0d95dc2Pins git:20261105.0d95dc2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- amd-agi/hyperloom
- Path
src/hyperloom_arbor/.claude/skills/geko-hipblaslt-tuning/SKILL.md- Versions recorded
- 1
- Latest version
- git:20261105.0d95dc2, committed Nov 5, 2026
- Size
- 6,035 bytes
- Repository stars
- 262
- License
- a license file GitHub does not identify
Set up and run geko hipBLASLt GEMM tuning for DeepSeek-V4.1-Flash + vLLM/AgentX serving on AMD gfx950 (MI355X), then verify and interpret the result. Use when installing geko in a container, applying the hipBLASLt 1.5.0 msgpack + scale_type patches, building a merged device library, running geko --tune, confirming the tuned kernels actually fire in serving, or deciding whether hipBLASLt tuning is the right lever (vs aiter). Triggers: "install geko", "geko --tune", "hipBLASLt tuning…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# geko hipBLASLt tuning for DSV4.1-Flash serving (gfx950) Tune the critical decode hipBLASLt GEMMs for DeepSeek-V4.1-Flash on vLLM/AgentX, deploy them, and **prove the tuned kernels are actually used** — apple-to-apple against the stock library. ## When to use - Installing geko into a fresh ROCm vLLM container and running `geko --tune`. - Hitting `geko --tune` end-to-end errors (msgpack / scale_type — see the 3 patches below). - A tune produced big GEMM-level uplift but **no e2e change** → verify the kernels fire + check the budget. - Deciding whether hipBLASLt tuning is worth it for this workload (short answer below). ## Decision first: is hipBLASLt tuning even the lever? In the GPU-kernel-time budget for DSV4.1-Flash AgentX serving, **hipBLASLt `Cijk_*` is a small share**. Most of the cost is the **aiter** umbrella (MoE experts `mfma_moe*_afp8_wfp4`, dense `_mxfp8_linear`) plus TP all-reduce. So geko hipBLASLt tuning is **flat end-to-end at every concurrency even with tuned kernels verified firing (and faster at GEMM level)**. If the goal is e2e throughput, tune **aiter** (its native autotuner), …
Read the whole file at its exact version.
How to install
mdr add amd-agi/hyperloom/geko-hipblaslt-tuning@sha256:2eb24b86248b2281The line at the top of this page pins the label git:20261105.0d95dc2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_5friupf5saujezrv)
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Versions
The registry has recorded 1 version of this file, committed on Nov 5, 2026.
Audit of the latest version
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Source
amd-agi/hyperloom · 262 stars · license a license file GitHub does not identify · pushed 2026-11-06 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_5friupf5saujezrv GET https://markdownregistry.com/api/v1/resolve?ref=amd-agi/hyperloom/geko-hipblaslt-tuning GET https://markdownregistry.com/api/v1/blob/2eb24b86248b2281cbaf18a3880e62125a471bb82258721752ff381f7625259f
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.