# [Control floating-point accuracy modes in Arm Performance Libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/)

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/)
- [Floating-point representation](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/floating-point-rep/)
- [Units in the last place (ULP)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/ulp/)
- [ULP error and accuracy](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/ulp-error/)
- [Accuracy modes in Libamath](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/multi-accuracy/)
- [Arm Performance Libraries example](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/examples/)
- [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/_next-steps/)

## About this Learning Path

| Skill level:          | Introductory         |
|-----------------------|----------------------|
| Reading time:         | 20 min               |
| Last updated:         | 17 Jun 2026          |

| Author:              | Joana Cruz           |
|----------------------|----------------------|
| Arm IP:              | [Neoverse](https://support.arm.com/?tab=compute-ip&Product%20Type=Infrastructure%20Processors) |
| Tags:                | [Performance and Architecture](https://learn.arm.com/tag/performance-and-architecture), [Linux](https://learn.arm.com/tag/linux), [Arm Performance Libraries](https://learn.arm.com/tag/arm-performance-libraries), [GCC](https://learn.arm.com/tag/gcc), [Libamath](https://learn.arm.com/tag/libamath) |

### Who is this for?
This is an introductory topic for developers who want to use the different accuracy modes for vectorized math functions in Libamath, a component of Arm Performance Libraries.

### What will you learn?
Upon completion of this Learning Path, you will be able to:
- Describe how accuracy is defined and measured in Libamath
- Select an appropriate accuracy mode for your application
- Use Libamath with different vector accuracy modes in practice

### Prerequisites
Before starting, you will need the following:
- An Arm computer running Linux with [Arm Performance Libraries](https://learn.arm.com/install-guides/armpl/) version 25.04 or newer installed.