gpu-kernels SKILL.md skillA
gpu-kernels from sparq-org/sparq is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add sparq-org/sparq/gpu-kernels@v0.1.0Pins v0.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- sparq-org/sparq
- Path
skills/gpu-kernels/SKILL.md- Versions recorded
- 4
- Latest version
- v0.1.0, committed Oct 9, 2026
- First version recorded
- Jun 16, 2026
- Size
- 7,345 bytes
- Repository stars
- 13
- License
- MIT
Experimental GPU (wgpu / WGSL) compute kernels for sparq's hot-path primitive shapes — FILTER + count, hash-join probe, and GROUP BY COUNT+SUM — over plain ValueId-shaped columns (&[u32] / &[f64]) in the opt-in sparq-gpu crate. Use when measuring whether a GPU beats the CPU for sparq's columnar primitives once the host->device transfer tax is charged, driving the Gpu handle and resident column/hash-table types, or reading the device-vs-CPU verdict. MEASUREMENT PROTOTYPE (roadmap T24d), PARKED…
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
# sparq-gpu — experimental GPU compute kernels (T24d, parked) `sparq-gpu` is an **opt-in measurement prototype**: opt-in [wgpu](https://wgpu.rs) / WGSL compute kernels for sparq's three hot-path primitive shapes — **FILTER + count**, **hash-join probe**, and **GROUP BY COUNT+SUM** — over plain `ValueId`-shaped columns (`&[u32]` / `&[f64]`). It was built to answer one question with measurements instead of aspiration: > Where (if anywhere) does a GPU beat the CPU for sparq's hot paths once the > host→device transfer tax is charged honestly? ## What this is — and is NOT (read first) - It is a **roadmap-T24d measurement prototype**, `publish = false`, and **parked**. **Nothing in the workspace depends on it**; it is **not wired into the query engine** — there is no scheduler integration, no residency cache, no SPARQL-level routing of work to the GPU. You drive the kernels directly. - It deliberately has **no `sparq-core` dependency** — the kernels take plain slices in exactly the shape of sparq-core's permutation-index object columns / dense numeric cache, so the engine carries zero GPU code and **wgpu never enters the wasm build** …
Read the whole file at its exact version.
How to install
mdr add sparq-org/sparq/gpu-kernels@sha256:0545957d1e49985aThe line at the top of this page pins the label v0.1.0, 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_3rzig742t6l5ayll)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Jun 16, 2026 and Oct 9, 2026, about one every 38 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v0.1.0 latest | 2026-10-09 | f0b870d | 7,345 B | A | view · diff |
| v0.1.0 | 2026-10-05 | bb7c604 | 7,328 B | A | view · diff |
| v0.1.0 | 2026-09-03 | 1a63aa7 | 6,275 B | A | view · diff |
| v0.1.0 | 2026-06-16 | 41ca27f | 6,271 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (7345 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
sparq-org/sparq · 13 stars · license MIT · pushed 2026-11-05 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_3rzig742t6l5ayll GET https://markdownregistry.com/api/v1/resolve?ref=sparq-org/sparq/gpu-kernels GET https://markdownregistry.com/api/v1/blob/0545957d1e49985ad11a09cea05b0e77986108514bd63e06106aa76405a5be06
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.