mojo-simd-kernels

Provide Mojo SIMD kernels and an FFI bridge for Rust interop.

Updated Dec 30, 2025
One-click install
npx skills add https://github.com/Rigohl/MEMORY_P --skill mojo-simd-kernels
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mojo-simd-kernels
Source: https://github.com/Rigohl/MEMORY_P/tree/main/.github/skills/mojo-simd-kernels
Command: npx skills add https://github.com/Rigohl/MEMORY_P --skill mojo-simd-kernels

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides high-performance Mojo SIMD kernels and a stable FFI bridge to accelerate vectorized workloads inside MEMORY_P v2.0 and enable cross-language interoperability with Rust and other hosts.

Core Features & Use Cases

  • High-performance Mojo SIMD kernels: vectorized primitives optimized for Mojo.
  • FFI integration: smooth interop with Rust and other host languages.
  • Use Case: accelerate numerical kernels in memory-bound ML and graphics workloads.

Quick Start

Build the Mojo SIMD kernel module and run the example using the FFI bridge to validate end-to-end Mojo integration.

Frequently Asked Questions about mojo-simd-kernels

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I accelerate vector math operations using Mojo SIMD kernels?

Mojo SIMD kernels accelerate vector math by providing ready-to-use vectorized primitives optimized for numerical tasks, enabling fast execution in memory-bound ML and graphics workloads.

Can I use Mojo SIMD kernels for Rust FFI integration?

Yes, Mojo SIMD kernels provide a stable FFI bridge designed for smooth interop with Rust and other host languages, ensuring safe boundaries for cross-language deployments.

What is the best way to perform cross-language matrix operations with Mojo?

The best way to perform cross-language matrix operations is using Mojo SIMD kernels, which supply optimized numerical primitives and a stable FFI bridge for multi-language execution.

Does this FFI bridge support memory-bound ML workloads?

Yes, the FFI bridge and SIMD primitives specifically target memory-bound ML workloads, supplying fast execution and safe integration boundaries for vectorized numerical tasks.

How do I validate Mojo integration with an FFI bridge?

You validate Mojo integration by building the SIMD kernel module and running the provided example, which tests the FFI bridge end-to-end to confirm successful cross-language execution.