Linux

Using Tracealyzer to Evaluate Python Algorithms in Linux

Using Tracealyzer to Evaluate Python Algorithms in Linux

In this blog post, we will see how Tracealyzer can be used to quickly and efficiently evaluate multiple implementations of an algorithm in Python, a language that is becoming more common in embedded application development as most machine learning frameworks are implemented in Python.

read more
Understanding the impact of compiler options on performance

Understanding the impact of compiler options on performance

In this post, we’re going to understand how the combination of LTTng and Tracealyzer can shine light on how compiler options impact performance. The method discussed can come in handy whenever we are evaluating the performance of multiple candidate implementations of a particular feature.

read more
Using Tracealyzer With a Yocto-based Linux Distribution

Using Tracealyzer With a Yocto-based Linux Distribution

While there are mechanisms native to the Linux kernel to ensure that the functionality of a custom-written driver is correct, evaluating performance is not straightforward. Here’s how you can use Tracealyzer for Linux to assess the performance and identify any deficiencies.

read more