AI for Performance Engineering and Performance Engineering for AI

Artificial Intelligence (AI) and Machine Learning (ML) techniques are revolutionizing various domains, including performance engineering. Performance engineering, which involves the evaluation, modeling, and optimization of system performance, has traditionally relied on established methodologies that have proven effective over the years. However, the growing complexity and heterogeneity of modern computing systems, particularly with the emergence of AI accelerators, has resulted in a shift in approach. AI and ML techniques are now being leveraged to achieve unprecedented levels of efficiency and scalability in performance engineering. Similarly, performance engineering is modifying metrics and methodologies for ML benchmarking. This talk will describe some opportunities and challenges when AI meets Performance Engineering.

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Publication Details

Published
2025-05-03
DOI
https://doi.org/10.1145/3676151.3720528
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

AI for Performance Engineering and Performance Engineering for AI

Lizy K. John
Parallel Computing and Optimization Techniques
article

AI for Performance Engineering and Performance Engineering for AI

Lizy K. John
article en

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) techniques are revolutionizing various domains, including performance engineering. Performance engineering, which involves the evaluation, modeling, and optimization of system performance, has traditionally relied on established methodologies that have proven effective over the years. However, the growing complexity and heterogeneity of modern computing systems, particularly with the emergence of AI accelerators, has resulted in a shift in approach. AI and ML techniques are now being leveraged to achieve unprecedented levels of efficiency and scalability in performance engineering. Similarly, performance engineering is modifying metrics and methodologies for ML benchmarking. This talk will describe some opportunities and challenges when AI meets Performance Engineering.

The University of Texas at Austin (US)
Openalex Percentile: Top 92%
Parallel Computing and Optimization Techniques
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AI for Performance Engineering and Performance Engineering for AI — Lizy K. John · (2025) | TGRS Research Map | TGRS