add-pallas-kernel
OfficialOptimize TPU/GPU kernels with Pallas.
Authormarin-community
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the need to implement, modify, benchmark, or autotune high-performance kernels on TPUs and GPUs using JAX's Pallas experimental features, ensuring numerical safety and performance.
Core Features & Use Cases
- Kernel Implementation: Develop both vanilla JAX and Pallas kernel implementations with consistent APIs.
- Correctness & Performance Validation: Includes harnesses for value/gradient parity, numerics, and steady-state timing.
- Autotuning: Automates the search for optimal block/tile sizes for specific hardware and shape regimes.
- Use Case: When developing a new neural network layer that requires custom, high-performance computation on accelerators, this Skill provides the framework to build, test, and optimize the underlying kernel.
Quick Start
Implement a Pallas kernel for matrix multiplication with autotuned block sizes for TPU v5e.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: add-pallas-kernel Download link: https://github.com/marin-community/marin/archive/main.zip#add-pallas-kernel Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 223,000+ vetted skills library on demand.