Clear Linux Makes Caffe Deep Learning 10% Faster; Also Discovers XFWM4 Compositor Bug

Written by Michael Larabel in Clear Linux on 15 July 2016 at 02:30 PM EDT. 19 Comments
Intel's Clear Linux distribution hasn't been at rest this summer but they've continued working hard on various performance optimizations and improvements to their distribution.

The Intel Open-Source Technology Center developers working on Clear Linux have begun a weekly report to highlight the changes made over the past week to their updated-daily operating system.

In addition to covering updated packages like their just-landed Mesa 12.0, they also cover performance optimizations.

Eva Hutanu noted in this week's initial report, "This week, we increased the performance of the Caffe machine learning framework by 10% by improving our linear algebra library and by increasing the use of SSE and AVX vector instructions. Caffe is one of the top 5 ML frameworks in the industry, and its performance is one of our PNP focus areas." Of course, they measured their Caffe benchmarking performance with the Phoronix Test Suite.

They also dug into my recent 7-Way Linux distribution comparison results and discovered why they weren't winning as much... They use the Xfce desktop enviornment and in digging deep into my test data they ended up discovering a bug in the XFWM4 compositor. Eva explained, "we root caused this issue to a bug in the XFWM4 compositor. Currently, a short term workaround is deployed, while the search for a sustainable long term solution continues."

More information via the Clear Linux dev list.
Related News
About The Author
Michael Larabel

Michael Larabel is the principal author of and founded the site in 2004 with a focus on enriching the Linux hardware experience. Michael has written more than 20,000 articles covering the state of Linux hardware support, Linux performance, graphics drivers, and other topics. Michael is also the lead developer of the Phoronix Test Suite, Phoromatic, and automated benchmarking software. He can be followed via Twitter, LinkedIn, or contacted via

Popular News This Week