Agent skill · Databases

unified-memory

Expert skill for CUDA Unified Memory and memory prefetching optimization. Configure managed memory allocations, implement memory prefetch strategies, handle page fault analysis, configure memory hints and advise, profile unified memory migration, optimize for oversubscription scenarios, and compare managed vs explicit memory.

a5c-aigithub.com/a5c-aiGitHub ↗
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill unified-memory --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 15 KB
Bundled scripts: none
Version: 1.0.0
Declared author: babysitter-sdk
Allowed tools: Bash(*)ReadWriteEditGlobGrepWebFetch
Path: library/specializations/gpu-programming/skills/unified-memory/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# unified-memory You are **unified-memory** - a specialized skill for CUDA Unified Memory and memory prefetching optimization. This skill provides expert capabilities for simplifying GPU memory management while maintaining high performance. ## Overview This skill enables AI-powered Unified Memory operations including: - Configuring managed memory allocations - Implementing memory prefetch strategies - Handling page fault analysis - Configuring memory hints and advise - Profiling unified memory migration - Optimizing for oversubscription scenarios - Handling multi-GPU unified memory - Comparing managed vs explicit memory performance ## Prerequisites - NVIDIA CUDA Toolkit 8.0+ (Unified Memory) - CUDA 9.0+ for hardware page faulting on Pascal+ - CUDA 11.0+ for advanced prefetching - GPU with compute capability 6.0+ for full UM features - nvidia-smi for migration monitoring - Nsight Systems for migration profiling ## Capabilities ### 1. Basic Unified Memory Allocation Allocate memory accessible from both CPU and GPU: ```cuda #include <cuda_runtime.h> // Allocate managed memory float* data; size_t size = N * sizeof(float); cudaMallocManaged(&data, size); // Initialize on CPU for (int i

What's inside
Steps it walks through
  1. Overview
  2. Prerequisites
  3. Capabilities
  4. 1. Basic Unified Memory Allocation
  5. 2. Memory Prefetching
  6. 3. Memory Advise Hints
  7. 4. Memory Advise Types
  8. 5. Page Fault Analysis
  9. 6. Multi-GPU Unified Memory
  10. 7. Oversubscription Handling
  11. 8. Performance Comparison: Managed vs Explicit
  12. 9. Best Practices Pattern Library
  13. MCP Server Integration
  14. Best Practices
Ships with 1 file
  • README.md
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About this skill
What does the unified-memory skill do?

Expert skill for CUDA Unified Memory and memory prefetching optimization. Configure managed memory allocations, implement memory prefetch strategies, handle page fault analysis, configure memory hints and advise, profile unified memory migration, optimize for oversubscription scenarios, and compare managed vs explicit memory.

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill unified-memory --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going