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- Herbie detects inaccurate expressions and finds more accurate replacements. The red expression is inaccurate when x > 1; Herbie's replacement, in blue, is accurate for all x.
herbie.uwplse.org/
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Here, you can see that Herbie's most accurate alternative has an accuracy of 99.7%, much better than the initial program's 53.2%, and that in total Herbie found 5 alternatives. One of those alternatives is both more accurate than the original expression and also 1.9× faster.
- Overview
- Installing
- Running Herbie
- Helping Out
- Running Tests
Herbie automatically improves the error of floating point expressions. Visit our website for tutorials, documentation, and an online demo. Herbie has semi-regular releases once a year, maintains backwards compatibility, and uses standardized formats.
Installing from Source
Installing from source requires Racket 8.0 or later, Rust 1.60.0 or later, and supports Windows, macOS, and Linux for various architectures. Install Racket from here. We recommend the official Racket installer over Snap. If your configuration depends on Racket being installed via Snap, you will need to ensure that Herbie and all packages are located in your home directory or another allow-listed directory. Install Rust from here. In this directory, build Herbie with: This will install a herbie binary somewhere under ~/.racket (Linux) although this path is dependent on OS and Racket version (check installation messages for a possible location). Depending on your configuration, you may need to add the binary to your path manually. You can also run src/herbie.rkt directly.
Installing from the Racket package index
Use this method for installing Herbie if Rust is not on your system. Installing via the Racket package index requires Racket 8.0 or later and supports Windows, macOS, and Linux on x86-64 architectures. Install Racket from here. Install Herbie with: This will install a herbie binary somewhere under ~/.racket (Linux) although this path is dependent on OS and Racket version (check installation messages for a possible location). You can also run src/herbie.rkt directly. Please note that this method of installation will fail for Apple M1 systems and other ARM architectures. We hope to support this in the near future.
For full details on running Herbie, please see the tutorial.
Herbie's input format is the Scheme-like FPCore; for example (1 + x) - x is written
You can see more examples in bench/. To use Herbie, run herbie shell and enter an FPCore expression:
In this case Herbie's improved, more-accurate expression is the constant 1.
Herbie is developed as a joint project of the Universities of Washington and Utah. We use Github and Trello to organize development goals.
Herbie has unit tests for basic functionality, though coverage is far from complete. You can run the test suite by downloading the source code, changing to the source code directory, and running:
Herbie also contains a large benchmark suite drawn from open source projects, examples from users, and numerical analysis textbooks. This suite is found in bench/. The full test can be run with
You may see warnings; these are expected. The output is HTML files in report/. This full test can take a few hours to run. We often test Herbie on basic but representative examples with:
This takes approximately 10 minutes.
Improving Rust with Herbie : How our work on Herbie discovered an accuracy problem with Rust's asinh function—and how Herbie helped us fix it. A new era for Herbie : Celebrating the fact that pareto mode is now enabled by default in Herbie.
Jun 3, 2015 · We evaluated Herbie on examples from a classic numerical methods textbook, and found that Herbie was able to improve accuracy on each example, some by up to 60 bits, while imposing a median performance overhead of 40%.
- Pavel Panchekha, Alex Sanchez-Stern, James R. Wilcox, Zachary Tatlock
- 2015
The percentage accuracy of the initial program and what Herbie thinks is its most accurate alternative. Time The time it took Herbie to generate all of the alternatives.
demonstrate that Herbie can effectively discover transformations that substantially improve accuracy (recovering up to 60 bits lost to rounding error) while imposing a median overhead of 40%.
