2021 journal article

An Automatic Synthesizer of Advising Tools for High Performance Computing

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 32(2), 330–341.

By: H. Guan*, X. Shen n & H. Krim n

author keywords: Tools; Optimization; Programming; Syntactics; Semantics; Guidelines; Natural language processing; Performance tools; natural language processing; code optimization
TL;DR: 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 and can retrieve relevant optimization knowledge for optimization questions. (via Semantic Scholar)
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Source: Web Of Science
Added: September 28, 2020

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.