Proceedings of the 2023 ACM/SPEC International Conference

It is our great pleasure to welcome you to the 14th annual ACM/SPEC International Conference on Performance Engineering (ICPE 2023) and to the cultural city of Coimbra - located in the center of Portugal, known as A cidade dos estudantes (the city of the students), and hosting the oldest University in Portugal and of Portuguese language, the University of Coimbra.

The International Conference on Performance Engineering (ICPE) originated 14 years ago from the fusion of the ACM Workshop on Software Performance (WOSP Est. 1998) and the SPEC International Performance Engineering Workshop (SIPEW Est. 2008). Since then, ICPE has been the leading international forum for presenting and discussing novel ideas, innovations, trends and experiences in the field of performance engineering.

Performance, energy efficiency and reliability are becoming central to the acceptance and sustainability of modern computing systems. However, they are also becoming more and more challenging to achieve. The computing systems are constantly growing in complexity and becoming more tightly integrated in human interaction, which makes their behavior more complex and therefore more difficult to engineer and understand. We need to be able to manage this complexity so that our systems remain reliable, trustable and performant.

ICPE 2023 Welcome

General Chairs

Marco Vieira (University of Coimbra, Portugal)
Valeria Cardellini (University of Rome Tor Vergata, Italy)

Program Chairs

Antinisca Di Marco (University of L’Aquila, Italy)
Petr Tůma (Charles University, Czechia)

ICPE 2023 Conference Organization

Keynote Talks

Pushing the Limits of Video Game Performance: A Performance Engineering Perspective:

Authors: Mathieu Nayrolles
DOI: 10.1145/3578244.3583738
Pages: 1 -- 1

Automated Optimisation of Modern Software System Properties:

Authors: Federica Sarro
DOI: 10.1145/3578244.3583739
Pages: 3 -- 4

Application Knowledge Required: Performance Modeling for Fun and Profit:

Authors: Georg Hager
DOI: 10.1145/3578244.3585384
Pages: 5 -- 5

Cloud Computing

Is Sharing Caring? Analyzing the Incentives for Shared Cloud Clusters:

Authors: Talha Mehboob; Noman Bashir; Michael Zink; David Irwin
DOI: 10.1145/3578244.3583730
Pages: 7 -- 16

Lightweight Kubernetes Distributions: A Performance Comparison of MicroK8s, k3s, k0s, and Microshift:

Authors: Heiko Koziolek; Nafise Eskandani
DOI: 10.1145/3578244.3583737
Pages: 17 -- 29

Autoscaler Evaluation and Configuration: A Practitioner's Guideline:

Authors: Martin Straesser; Simon Eismann; Jóakim von Kistowski; André Bauer; Samuel Kounev
DOI: 10.1145/3578244.3583721
Pages: 31 -- 41

Measurement

DrGPU: A Top-Down Profiler for GPU Applications:

Authors: Yueming Hao; Nikhil Jain; Rob Van der Wijngaart; Nirmal Saxena; Yuanbo Fan; Xu Liu
DOI: 10.1145/3578244.3583736
Pages: 43 -- 53

Systematically Exploring High-Performance Representations of Vector Fields Through Compile-Time Composition:

Authors: Stephen Nicholas Swatman; Ana-Lucia Varbanescu; Andy Pimentel; Andreas Salzburger; Attila Krasznahorkay
DOI: 10.1145/3578244.3583723
Pages: 55 -- 66

Evaluating the Energy Measurements of the IBM POWER9 On-Chip Controller:

Authors: Hannes Tröpgen; Mario Bielert; Thomas Ilsche
DOI: 10.1145/3578244.3583729
Pages: 67 -- 76

Machine Learning

Predicting the Performance of ATL Model Transformations:

Authors: Raffaela Groner; Peter Bellmann; Stefan Höppner; Patrick Thiam; Friedhelm Schwenker; Matthias Tichy
DOI: 10.1145/3578244.3583727
Pages: 77 -- 89

Predicting the Performance of a Computing System with Deep Networks:

Authors: Mehmet Cengiz; Matthew Forshaw; Amir Atapour-Abarghouei; Andrew Stephen McGough
DOI: 10.1145/3578244.3583731
Pages: 91 -- 98

Predicting Inference Latency of Neural Architectures on Mobile Devices:

Authors: Zhuojin Li; Marco Paolieri; Leana Golubchik
DOI: 10.1145/3578244.3583735
Pages: 99 -- 112

A Method to Evaluate the Performance of Predictors in Cyber-Physical Systems:

Authors: Leonardo Passig Horstmann; Matheus Wagner; Antônio Augusto Fröhlich
DOI: 10.1145/3578244.3583732
Pages: 113 -- 123

Virtualization and Services

Analyzing the Performance of SD-WAN Enabled Service Function Chains Across the Globe with AWS:

Authors: Aris Leivadeas; Nikolai Pitaev; Matthias Falkner
DOI: 10.1145/3578244.3583722
Pages: 125 -- 135

HHVM Performance Optimization for Large Scale Web Services:

Authors: Yuhao Li; Abhishek Gupta; Alex Yang; Peinan Chen; Joey Pinto; Brian Karrer; Mayank Pundir; Maximilian Balandat; Arun Kejariwal; Benjamin Lee
DOI: 10.1145/3578244.3583720
Pages: 137 -- 148

A Methodology and Framework to Determine the Isolation Capabilities of Virtualisation Technologies:

Authors: Simon Volpert; Benjamin Erb; Georg Eisenhart; Daniel Seybold; Stefan Wesner; Jörg Domaschka
DOI: 10.1145/3578244.3583728
Pages: 149 -- 160

Benchmarking and Optimization

Implementation of Dataflow Software Pipelining for Codelet Model:

Authors: Siddhisanket Raskar; Jose M Monsalve Diaz; Thomas Applencourt; Kalyan Kumaran; Guang Gao
DOI: 10.1145/3578244.3583734
Pages: 161 -- 172

Meterstick: Benchmarking Performance Variability in Cloud and Self-hosted Minecraft-like Games:

Authors: Jerrit Eickhoff; Jesse Donkervliet; Alexandru Iosup
DOI: 10.1145/3578244.3583724
Pages: 173 -- 185

A Systematic Approach for Benchmarking of Container Orchestration Frameworks:

Authors: Martin Straesser; Jonas Mathiasch; André Bauer; Samuel Kounev
DOI: 10.1145/3578244.3583726
Pages: 187 -- 198

Hunter: Using Change Point Detection to Hunt for Performance Regressions:

Authors: Matt Fleming; Piotr Kolaczkowski; Ishita Kumar; Shaunak Das; Sean McCarthy; Pushkala Pattabhiraman; Henrik Ingo
DOI: 10.1145/3578244.3583719
Pages: 199 -- 206