# Overview: Tuning Performance

This section describes several programming guidelines that can help you improve the performance of floating-point applications:

- Avoid exceeding representable ranges during computation; handling these cases can have a performance impact.
- Use a single-precision type (for example, float) unless the extra precision and/or range obtained through double or long double is required. Greater precision types increase memory size and bandwidth requirements. See Using Efficient Data Types section.
- Reduce the impact of denormal exceptions for all supported architectures.
- Avoid mixed data type arithmetic expressions.

Parent topic: Floating-Point Operations

- Handling Floating-point Array Operations in a Loop Body
- Reducing the Impact of Denormal Exceptions
- Avoiding Mixed Data Type Arithmetic Expressions
- Using Efficient Data Types

## See Also

Avoiding Mixed Data Type Arithmetic Expressions
Reducing the Impact of Denormal Exceptions
Using Efficient Data Types