Published November 6, 2025 | Version 1.2.0
Software Open

Fiats: Functional inference and training for surrogates

Authors/Creators

  • 1. ROR icon Lawrence Berkeley National Laboratory
  • 2. ROR icon NSF National Center for Atmospheric Research
  • 3. ROR icon Northern New Mexico College

Description

Fiats supports research on the training and deployment of neural-network surrogate models for computational science. Fiats also provides a platform for exploring and advancing the native parallel programming features of Fortran 2023 in the context of deep learning. The design of Fiats centers around functional programming patterns that facilitate concurrency, including loop-level parallelism via the do concurrent construct and Single-Program, Multiple Data (SMPD) parallelism via "multi-image" (i.e., multiprocess) execution.

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Additional details

Additional titles

Subtitle
Fiats release version 1.2.0

Identifiers

URL
https://go.lbl.gov/fiats
URL
https://github.com/berkeleylab/fiats

Related works

Is described by
Conference paper: 10.25344/S4QS3J (DOI)
Conference paper: 10.25344/S4VG6T (DOI)

Dates

Copyrighted
2025-11-06

Software

Repository URL
https://github.com/berkeleylab/fiats
Programming language
Fortran
Development Status
Active