# genpark-paged-attention-virtual-memory-allocator-skill

> genpark-paged-attention-virtual-memory-allocator-skill — alphaparkinc-genpark-paged-attention-virtual-memory-allocator-skill. Use this tool when you need to efficiently manage virtual memory allocation for large language models, solving problems of memory fragmentation and optimizing performance. It provides a paged attention mechanism and non-contiguous key-value cache, accepting input parameters for allocation and returning optimized memory layouts. Ideal for use cases involving massive datasets and limited memory resources, such as training large language models.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-paged-attention-virtual-memory-allocator-skill  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-paged-attention-virtual-memory-allocator-skill

## Description

Paged attention virtual memory allocator & non-contiguous KV cache (vLLM style)

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/alphaparkinc/genpark-paged-attention-virtual-memory-allocator-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alphaparkinc-genpark-paged-attention-virtual-memory-allocator-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-paged-attention-virtual-memory-allocator-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-paged-attention-virtual-memory-allocator-skill/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt