stencil-convolution
Expert skill for optimized stencil and convolution pattern implementations on GPU. Design tiled stencil algorithms with halos, implement 2D/3D convolution kernels, optimize boundary condition handling, apply temporal blocking techniques, generate separable filter implementations, and profile stencil memory bandwidth.
npx skills add a5c-ai/babysitter --skill stencil-convolution --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.
# stencil-convolution You are **stencil-convolution** - a specialized skill for optimized stencil and convolution pattern implementations on GPU. This skill provides expert capabilities for scientific computing, image processing, and numerical simulations requiring neighborhood computations. ## Overview This skill enables AI-powered stencil and convolution operations including: - Designing tiled stencil algorithms with halos - Implementing 2D/3D convolution kernels - Optimizing boundary condition handling - Applying temporal blocking techniques - Generating separable filter implementations - Configuring shared memory tiling strategies - Profiling stencil memory bandwidth - Supporting multi-resolution stencils ## Prerequisites - NVIDIA CUDA Toolkit 11.0+ - GPU with compute capability 3.5+ - Understanding of memory coalescing patterns - Nsight Compute for memory analysis - Optional: cuDNN for optimized convolutions ## Capabilities ### 1. Basic 2D Stencil (5-Point Laplacian) ```cuda // Naive 5-point stencil (for comparison) __global__ void laplacian2D_naive( float* out, const float* in, int width, int height ) { int x = blockIdx.x * blockDim.x + threadIdx.x; int y = blockIdx.y * block
- Overview
- Prerequisites
- Capabilities
- 1. Basic 2D Stencil (5-Point Laplacian)
- 2. Tiled Stencil with Shared Memory and Halo
- 3. Generic N-Point Stencil with Configurable Radius
- 4. 2D Convolution with Arbitrary Kernel
- 5. Separable Convolution (2-Pass for Performance)
- 6. 3D Stencil (7-Point Laplacian)
- 7. Temporal Blocking (Multi-Timestep)
- 8. Boundary Condition Patterns
- Best Practices
- Memory Access Patterns
- Tile Size Selection
What does the stencil-convolution skill do?
Expert skill for optimized stencil and convolution pattern implementations on GPU. Design tiled stencil algorithms with halos, implement 2D/3D convolution kernels, optimize boundary condition handling, apply temporal blocking techniques, generate separable filter implementations, and profile stencil memory bandwidth.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill stencil-convolution --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.