mojo-simd-optimize
CommunityBoost Mojo performance with SIMD.
Authormvillmow
Version1.0.0
Installs0
System Documentation
What problem does it solve? This Skill guides developers in applying SIMD (Single Instruction Multiple Data) optimizations to Mojo code, significantly boosting performance for parallel computations in tensor and array operations. It automates the identification of optimization patterns, saving manual tuning time.
Core Features & Use Cases:
- Vectorized Loops: Transforms scalar loops into highly efficient SIMD vector operations, maximizing CPU utilization.
- Remainder Handling: Provides patterns for processing data that doesn't fit perfectly into SIMD vectors, ensuring complete optimization.
- Use Case: Your Mojo tensor addition function is a performance bottleneck. Use this skill to learn how to vectorize the loop with SIMD instructions, achieving a significant speedup for large datasets and improving overall application performance.
Quick Start: Use the mojo-simd-optimize skill to apply SIMD optimization to the 'add' function in 'src/tensor.mojo'.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 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: mojo-simd-optimize Download link: https://github.com/mvillmow/ml-odyssey/archive/main.zip#mojo-simd-optimize Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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