parallel-patterns
GPU parallel algorithm design patterns and implementations. Implement parallel reduction, scan/prefix sum, histogram, parallel sort algorithms, stream compaction, and work-efficient patterns optimized for specific GPU architectures.
npx skills add a5c-ai/babysitter --skill parallel-patterns --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# parallel-patterns You are **parallel-patterns** - a specialized skill for GPU parallel algorithm design patterns and implementations. This skill provides expert capabilities for implementing efficient parallel algorithms on GPUs. ## Overview This skill enables AI-powered parallel algorithm development including: - Implement parallel reduction algorithms (tree-based, warp) - Generate scan (prefix sum) implementations - Design histogram and binning algorithms - Implement parallel sort algorithms (radix, merge) - Generate stream compaction code - Design work-efficient parallel patterns - Handle multi-pass large-data algorithms - Optimize for specific GPU architectures ## Prerequisites - CUDA Toolkit 11.0+ - CUB library (included with CUDA) - Thrust library (included with CUDA) ## Capabilities ### 1. Parallel Reduction Implement efficient reductions: ```cuda // Warp-level reduction (no shared memory needed for single warp) __device__ float warpReduce(float val) { for (int offset = warpSize / 2; offset > 0; offset >>= 1) { val += __shfl_down_sync(0xffffffff, val, offset); } return val; } // Block-level reduction with shared memory template<int BLOCK_SIZE> __device__ float blockReduce(
- Overview
- Prerequisites
- Capabilities
- 1. Parallel Reduction
- 2. Prefix Sum (Scan)
- 3. Histogram
- 4. Radix Sort
- 5. Stream Compaction
- 6. Parallel Merge
- 7. Work Distribution Patterns
- Process Integration
- Output Format
- Dependencies
- Constraints
What does the parallel-patterns skill do?
GPU parallel algorithm design patterns and implementations. Implement parallel reduction, scan/prefix sum, histogram, parallel sort algorithms, stream compaction, and work-efficient patterns optimized for specific GPU architectures.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill parallel-patterns --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.