# HVM — Massively Parallel Runtime for Functional Programs

> HVM (Higher-order Virtual Machine) is a parallel runtime that executes functional programs across all available CPU and GPU cores automatically, using a novel interaction-net reduction model.

## Install

Save in your project root:

# HVM — Massively Parallel Runtime for Functional Programs

## Quick Use
```bash
# Install via Cargo
cargo install hvm

# Run a simple program
echo '
@main = (* 6 7)
' > hello.hvm
hvm run hello.hvm

# Or compile to parallel C code
hvm compile hello.hvm
gcc -O2 -o hello hello.c -lpthread
./hello
```

## Introduction
HVM (Higher-order Virtual Machine) is a runtime and compiler for functional programming that automatically parallelizes programs across CPU cores and GPUs. Built by HigherOrderCO, HVM uses interaction nets — a computation model from the theory of linear logic — that enables safe parallel reduction without locks, mutexes, or manual concurrency annotations. Programs written in the Bend language compile to HVM for execution.

## What HVM Does
- Executes functional programs in parallel across all available CPU cores automatically
- Compiles programs to C or CUDA code for native and GPU execution
- Reduces interaction nets using a lock-free, garbage-collection-free algorithm
- Supports higher-order functions, pattern matching, and algebraic data types
- Serves as the backend for the Bend programming language

## Architecture Overview
HVM is based on interaction combinators, a model of computation where programs are represented as graphs of interacting nodes. Reduction rules are local — each node pair can be reduced independently — which makes the model inherently parallel. The runtime dispatches interaction-net reductions across threads without synchronization. HVM compiles to C with pthreads for CPU parallelism and to CUDA for GPU execution. The absence of a garbage collector is fundamental to the design: interaction nets naturally deallocate memory as nodes are consumed during reduction.

## Self-Hosting & Configuration
- Install the HVM binary via Cargo (Rust toolchain required)
- Write programs directly in HVM's core syntax or use the Bend language as a frontend
- Compile to standalone C executables for deployment without the Rust toolchain
- Control thread count with the `-t` flag for CPU execution
- Use `hvm compile --cuda` to target GPU execution via CUDA

## Key Features
- Automatic parallelism with no manual thread management or async annotations
- Lock-free and garbage-collection-free design for predictable performance
- Compiles to standalone C or CUDA code for deployment
- Optimal beta-reduction via interaction nets based on Lamping's algorithm
- Supports the Bend language for a Python-like high-level programming experience

## Comparison with Similar Tools
- **GHC (Haskell)** — mature compiler with sophisticated optimizations but limited automatic parallelism; HVM parallelizes by default through its computation model
- **Erlang BEAM** — process-level concurrency with message passing; HVM provides instruction-level parallelism without explicit process management
- **Futhark** — functional GPU language for array computations; HVM targets general-purpose functional programs, not just numerical workloads
- **Chapel** — parallel programming language; HVM achieves parallelism through its computation model rather than language-level parallel constructs

## FAQ
**Q: Do I need to write parallel code to get parallelism from HVM?**
A: No. HVM automatically parallelizes any functional program. The interaction-net model is inherently parallel without annotations.

**Q: What is Bend and how does it relate to HVM?**
A: Bend is a high-level programming language with Python-like syntax that compiles to HVM. It is the recommended way to write programs for the HVM runtime.

**Q: Does HVM support GPU execution?**
A: Yes. HVM can compile programs to CUDA for execution on NVIDIA GPUs.

**Q: Is HVM production-ready?**
A: HVM is under active development and is suitable for experimentation and research. Production readiness depends on the specific workload.

## Sources
- https://github.com/HigherOrderCO/HVM
- https://github.com/HigherOrderCO/Bend

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Author: AI Open Source