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Wednesday, May 11 • 10:50am - 11:40am
Using a Relative Index of Performance (RIP) to Determine Optimum Configuration Settings Compared to Random Forest Assessment Using Spark - Diane Feddema, Red Hat Inc, Canada

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Computer Systems can be set with a myriad of options, determining an optimal set-up for any particular application can be difficult. This pilot study demonstrates how numerous I/O performance tests with varied hardware and software configurations can be efficiently compared to determine an optimal set-up for an application. To simplify this process a statistic was developed to provide a quick relative performance comparison. This metric can be arithmetically manipulated to provide meaningful averaging of multiple performance tests into a single overall performance indicator. We will illustrate how RIP is used by comparing I/O performance test results on approximately 50-100 different hardware/software set-ups; RIP results will be compared to results from a random forest repeat sampling technique to determine the most influential performance factors.


Speakers
avatar for Diane Feddema

Diane Feddema

Principal Software Engineer, AI/ML Performance on RHEL and OpenShift Operator Development, Red Hat
Diane Feddema is a principal software engineer at Red Hat Inc, in the Performance and Scale team. Diane is currently focused on developing and applying machine learning techniques for performance analysis using hardware accelerators, automating these analyses and displaying data in... Read More →



Wednesday May 11, 2016 10:50am - 11:40am PDT
Georgia B