The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: Lewis Littman (University of Bristol), Tom Deakin (University of Bristol)
Supervisor:
Abstract: Traditional performance analysis tools, such as the roofline model, require visual interpretation to determine performance bounds. For CPUs which have complex cache hierarchies and front-end out-of-order capabilities—that is, the CPUs we use for high performance computing—accurately identifying the true performance bound is challenging. This work is the first step towards a data-driven approach to performance modeling, leveraging machine learning techniques. We build and evaluate a number of supervised and unsupervised models using a new curated data set of performance counters collected from well-understood (i.e., easily labeled) benchmark applications. We further analyze the data set and highlight potential "performance fingerprints" obtainable using this methodology.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF