Performance Tuning Research

Beginning in 2023, I joined a research study on randomized linear algebra algorithims.

I have been fortunate enough to join a professor at Santa Clara University in a field of research concerning randomized linear algorithim runtime on various hardware setups. While the research has just begun recently, I hope to be able to share more in the future about what we find, and the process along the way.

So far, I have been observing variations in simulation runtimes for CPU clusters concerning matrix multiplications, provided varying amounts of RAM and CPUs. In the future, we intend to utilize a library, RandBLAS, to simulate randomized linear algebra methods. We have been collecting data using an external library named PAPI, which permits us to analyze data of varying areas that a computer may output during a trial, such as CPU cycles or instruction count.

I will continue to update this page as I make further progress in my research!

If you'd like to view my research yourself, I have uploaded my scripts to a GitHub repository linked here.