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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开发者工具

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

关于

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.

主要功能

2 GitHub stars
Compiles Bend functional language to interaction nets for optimal reduction
Implements optimal sharing to eliminate redundant functional computations
Dispatches parallel computations to GPU threads via CUDA or Metal
Provides auto-parallelizing primitives for map and fold operations
Integrated GF(3) triadic classification for topological computation verification

使用场景

Accelerating recursive functional algorithms through massive GPU parallelism
Executing high-throughput data processing pipelines with optimal reduction
Researching and debugging interaction net-based graph reduction strategies

关于

主要功能

2 GitHub stars
Compiles Bend functional language to interaction nets for optimal reduction
Implements optimal sharing to eliminate redundant functional computations
Dispatches parallel computations to GPU threads via CUDA or Metal
Provides auto-parallelizing primitives for map and fold operations
Integrated GF(3) triadic classification for topological computation verification

使用场景

Accelerating recursive functional algorithms through massive GPU parallelism
Executing high-throughput data processing pipelines with optimal reduction
Researching and debugging interaction net-based graph reduction strategies