# \[ANN\] CUTEst.jl: Enhanced support for single, double, and quadruple precision

**URL:** https://discourse.julialang.org/t/ann-cutest-jl-enhanced-support-for-single-double-and-quadruple-precision/118788
**Category:** Package Announcements
**Created:** [August 30, 2024, 12:40am UTC](https://discourse.julialang.org/t/ann-cutest-jl-enhanced-support-for-single-double-and-quadruple-precision/118788 "2024-08-30T00:40:55Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![amontoison](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/amontoison/32/218741_2.png) [@amontoison](https://discourse.julialang.org/u/amontoison)
#### Post date: [August 30, 2024, 12:40am UTC](https://discourse.julialang.org/t/ann-cutest-jl-enhanced-support-for-single-double-and-quadruple-precision/118788/1 "2024-08-30T00:40:55Z")

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Dear Julia Community,

We are thrilled to announce the release 1.0.0 of **CUTEst.jl** , a powerful interface for testing and benchmarking optimization problems in Julia. This latest release introduces support for single, double, and quadruple precision — a first for CUTEst in any high-level language. This enhancement allows you to test your optimization models with unprecedented flexibility and precision.

### Key Features:

- **Multi-precision support** :  
Seamlessly switch between single, double, and quadruple precision.

- **Automatic download of SIF files** :  
Access a wide range of optimization problem sets with automatic SIF file downloads for LP, QP, and NLP collections.

- **Cross-platform compatibility** :  
Enjoy full support across different operating systems, including Windows, which is now officially supported.

- **Improved Documentation** :  
Comprehensive and clearer documentation to help users understand and utilize the full capabilities of **CUTEst.jl**.

- **Latest CUTEst features** :  
Integration with the most recent features of CUTEst.

Key improvements include the replacement of the previous Bash script with a standalone SIF decoder binary for smoother and more reliable performance. Additionally, Julia’s artifact system ensures that all necessary dependencies are automatically managed and installed, streamlining the setup process and providing a consistent experience across all platforms.

For more details and to start using **CUTEst.jl** , visit:

- **CUTEst.jl** [repository](https://github.com/JuliaSmoothOptimizers/CUTEst.jl) and [documentation](https://jso.dev/CUTEst.jl/stable/)

Alexis Montoison (@amontoison), on behalf of the GALAHAD team  
Nick Gould (@nimgould), Jari Fowkes (@jfowkes) & Dominique Orban (@dpo)