An Automatic Synthesizer of Advising Tools for High Performance Computing

This article presents Egeria, the first automatic synthesizer of advising tools for High-Performance Computing (HPC). When one provides it with some HPC programming guides as inputs, Egeria automatically constructs a text retrieval tool that can advise on what to do to improve the performance of a given program. The advising tool provides a concise list of essential rules automatically extracted from the documents and can retrieve relevant optimization knowledge for optimization questions. Egeria is built based on a distinctive multi-layered design that leverages natural language processing (NLP) techniques and extends them with HPC-specific knowledge and considerations. This article presents the design, implementation, and both quantitative and qualitative evaluation results of Egeria.

Automated summary

Egeria is the first automatic synthesizer of advising tools for High-Performance Computing (HPC), which constructs a text retrieval tool based on HPC programming guides to improve program performance and provide optimization knowledge. It utilizes natural language processing techniques and HPC-specific knowledge in its multi-layered design.