Neural Fortran

A parallel neural net microframework for high-performance computing.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Neural Fortran?

Neural Fortran is a lightweight framework designed to enable the development of efficient and scalable neural networks using Fortran. It leverages modern Fortran features and parallel computing techniques to deliver high performance in scientific and engineering applications.

Key differentiator

Neural Fortran stands out as one of the few deep learning frameworks that fully leverages modern Fortran's capabilities to deliver high-performance neural networks, making it ideal for scientific and engineering applications requiring both speed and precision.

Capability profile

Strength Radar

Parallel computi…Lightweight desi…Modern Fortran f…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Parallel computing support for efficient neural network training and inference.

Lightweight design to minimize overhead in scientific applications.

Modern Fortran features for better performance and maintainability.

Fit analysis

Who is it for?

✓ Best for

Scientific researchers who need to integrate deep learning into their Fortran-based simulations.

Engineering teams working on performance-critical applications that require neural network capabilities.

✕ Not a fit for

Developers looking for a high-level, easy-to-use framework without the need for parallel computing expertise.

Projects where Python or other higher-level languages are preferred over Fortran.

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Next step

Get Started with Neural Fortran

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →