Does this skill support GPU execution?

Yes, the HVM Runtime skill supports compiling and running code on CUDA and Metal-enabled GPUs for maximum performance.

How does HVM achieve significant speedups?

HVM achieves speedups by compiling functional code into a graph-based representation that allows thousands of reductions to occur simultaneously on GPU cores.

What is the HVM Runtime?

HVM (Higher-order Virtual Machine) is a high-performance runtime that uses interaction nets to perform massively parallel reduction of functional code.

What is the Bend language?

Bend is the high-level functional language designed specifically for HVM, allowing users to write Python-like or Haskell-like code that auto-parallelizes.

What is 'optimal sharing' in this context?

Optimal sharing ensures that if a computation is needed multiple times, it is reduced once and the result is shared, preventing the exponential blowup often found in traditional functional execution.

HVM Runtime & Parallel Computation

Name: HVM Runtime & Parallel Computation
Author: plurigrid

byplurigrid

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Herramientas para Desarrolladores

Executes massively parallel functional code using interaction nets and GPU acceleration for optimal reduction speed.

The HVM Runtime skill integrates the Higher-order Virtual Machine into Claude, enabling the execution and optimization of high-performance functional programs via the Bend language. It leverages interaction net technology to achieve optimal sharing and parallel reduction, translating complex functional logic into GPU-accelerated graph reductions. This skill is ideal for developers building compute-intensive algorithms, parallel data processing pipelines, and researchers exploring the intersection of linear logic and massively parallel hardware architectures.

Características Principales

012 GitHub stars

02Compiles Bend functional language to interaction nets for optimal reduction

03Implements optimal sharing to eliminate redundant functional computations

04Dispatches parallel computations to GPU threads via CUDA or Metal

05Provides auto-parallelizing primitives for map and fold operations

06Integrated GF(3) triadic classification for topological computation verification

Casos de Uso

01Accelerating recursive functional algorithms through massive GPU parallelism

02Executing high-throughput data processing pipelines with optimal reduction

03Researching and debugging interaction net-based graph reduction strategies

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi hvm-runtime

For use in Claude.ai and ChatGPT

Download Skill