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ICPE 2022 : International Conference on Performance Engineering


Conference Series : International Conference on Performance Engineering
When Apr 9, 2022 - Apr 13, 2022
Where Beijing, China
Abstract Registration Due Sep 30, 2021
Submission Deadline Oct 7, 2021
Notification Due Dec 2, 2021
Categories    software engineering   computer science   performance engineering   benchmarking

Call For Papers

Call for Contributions
ICPE 2022
13th ACM/SPEC International Conference on Performance Engineering
Beijing, China
April 9 - 13, 2022
IMPORTANT DATES (All dates are in 23:59 AoE)

Double-Blind & in main conference proceedings:
Research abstracts: Sept 30, 2021
Research papers: Oct 07, 2021
Research paper notification: Dec 02, 2021
Industrial/experience abstracts: Sept 30, 2021
Industrial/experience papers: Oct 07, 2021
Industrial/experience paper notification: Dec 02, 2021

Single-Blind & in main conference proceedings
Artifact registration: Dec 10, 2021
Artifact submission: Dec 16, 2021
Artifact notification: Jan 31, 2022

Single-Blind & in conference companion as post-proceedings:
Workshop proposals submission: Oct 07, 2021
Workshop proposals notification: Oct 17, 2021

NEW: Data Challenge submission: Jan 15, 2022
Poster/demo submission: Jan 15, 2022
Tutorial proposals submission: Jan 15, 2022
Work-in-progress papers: Jan 15, 2022
Authors and attendees are guaranteed that they can attend and present at ICPE 2022
virtually without traveling to Beijing in cases where the ongoing Covid 19 pandemic
does imply travel restrictions or where attendees are concerned about their personal
health or CO2 emissions. However, we aim at and hope for most attendees and in particular
for paper authors to attend the conference physically in Beijing.

The International Conference on Performance Engineering (ICPE) is the leading
international forum for presenting and discussing novel ideas, innovations,
trends and experiences in the field of performance engineering. Modern systems,
such as big data and machine learning environments, data centers and cloud
infrastructures, social networks, peer-to-peer, mobile and wireless systems,
cyber-physical systems, the Internet of Things or more traditional ones such
as web-based or real- time systems, rely increasingly on distributed and
dynamic architectures and pose a challenge to their end-to-end performance management.

ICPE brings together researchers and practitioners to report state-of-the-art and
in-progress research on performance engineering of software and systems,
including performance measurement, modeling, benchmark design, and run-time
performance management. The focus is both on classical metrics such as response time,
throughput, resource utilization, and (energy) efficiency, as well as on
the relationship of such metrics to other system properties including
but not limited to scalability, elasticity, availability, reliability,
cost, sustainability, security and privacy. The systems of interest include
any type of computing or software system, such as (but not limited to)
desktop systems, cloud systems, web-based systems, embedded systems,
distributed systems and cyber-physical systems. The handling of
performance issues at all stages of software and system life cycles
is also of interest.

Topics of interest include, but are not limited to:

Performance modeling of software:
* Languages and ontologies
* Methods and tools
* Relationship/integration/tradeoffs with other QoS attributes
* Analytical, simulation and statistical modeling methodologies
* Machine learning and neural networks
* Model validation and calibration techniques
* Automatic model extraction
* Performance modeling and analysis tools
* Traceability of software and performance artifacts
* Control of software performance evolution

Performance and software development processes/paradigms:
* Software performance testing
* Software performance (anti-)patterns
* Software/performance tool interoperability (models and data interchange formats)
* Performance-oriented design, implementation and configuration management
* Software Performance Engineering and Model-Driven Development
* Gathering, interpreting and exploiting software performance annotations and data
* System sizing and capacity planning techniques
* (Model-driven) Performance requirements engineering
* Relationship between performance and architecture
* Performance and agile methods
* Performance in (micro)service-based and serverless systems
* Software and system scalability and its impact on performance

Performance measurement, monitoring and analysis:
* Application tracing and profiling
* Workload characterization techniques
* Experimental design
* Tools and techniques for performance testing, measurement, profiling and tuning,
* and analysis of the resulting data

* Performance metrics and benchmark suites
* Benchmarking methodologies
* Development of parameterizable, flexible benchmarks
* Benchmark workloads and scenarios
* Use of benchmarks in industry and academia

Run-time performance management and adaptation
* Machine learning and runtime performance decisions
* Context modeling and analysis
* Runtime model estimation
* Use of models at run-time
* Online performance prediction
* Autonomic resource management
* Utility-based optimization
* Capacity management

Power and performance, energy efficiency
* Power consumption models and management techniques
* Tradeoffs between performance and energy efficiency
* Performance-driven resource and power management

All other topics related to performance of software and systems.

Authors are invited to submit original, unpublished papers that are not being
considered in another forum. A variety of contribution styles for papers is
solicited including: basic and applied research papers for novel scientific insights,
industrial and experience papers reporting on applying performance engineering or
benchmarks in practice, and work-in-progress papers for ongoing innovative work.
Different acceptance criteria apply based on the expected content of the
individual contribution types.

=== Double Blind Review for Research and Industry/Experience submissions ===
From this year on, ICPE adopts a double-blind review process for the research &
industry/experience tracks (fall deadlines, papers that go into the main conference proceedings).
Double-blind reviewing is intended to increase fairness and reduce implicit bias during reviewing.
Authors are required to make a serious effort to anonymise their PDF submission and
declare known conflicts of interest with PC members during submission. We will provide an
extensive guideline with FAQ to help the authors with the anonymisation of their submission.
However, most important is that:
* Submitted PDFs do not contain an author list.
* Authors do not explicitly point at their own previous work in a way that would disclose
their identity (“In previous work [1], we have shown that …”).
* Submitted PDFs do not contain links to the author’s home institutions, personal websites,
or non-anonymous GitHub profiles, e.g., to point at data sets. Data can and should
be uploaded to third-party services blinded. Instructions how to upload blinded data
(which can be unblinded after acceptance) can be found here:
* There are no acknowledgements of named persons or projects in the submitted PDF
(evidently, acknowledgements can be added after acceptance).
Notably, double-blind reviewing does not preclude submitting work intended for ICPE
to preprint services such as Arxiv. However, we ask authors to use a clearly different
title for their preprint submission than for the PDF submitted to ICPE.
The PC chairs retain the right to desk-reject submissions that are not sufficiently anonymised.
=== Double Blind Review for Research and Industry/Experience submissions ===

Authors will be requested to self-classify their papers according to the provided topic
areas when submitting their papers. Submissions to all tracks need to be uploaded to
ICPE's submission system and conform to the ACM submission format.

At least one author of each accepted paper is required to register at the full rate,
attend the conference and present the paper. Presented papers will be published in the
ICPE 2022 conference proceedings that will be published by ACM and included in the ACM Digital Library.

Authors of accepted research papers are invited to submit an artifact to the ACM/SPEC ICPE 2022 Artifact Track.
Artifacts submissions are reviewed single-blind.

The highest quality papers, judged by multiple relevant factors, will be recognized with an award.

AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available
in the ACM Digital Library. This date may be up to two weeks prior to the first day of your conference.
The official publication date affects the deadline for any patent filings related to published work.
(For those rare conferences whose proceedings are published in the ACM Digital Library after the conference is over,
the official publication date remains the first day of the conference.)


Cristina L. Abad, ESPOL (WIP/Experience Chair)
Jose Nelson Amaral, University of Alberta
Amy Apon, Clemson University
Varsha Apte, Indian Institute of Technology - Bombay
Alberto Avritzer, EsulabSolutions, Inc.
Alexandre Bergel, University of Chile
Simona Bernardi, Universidad de Zaragoza
Walter Binder, University of Lugano
Robert Birke, ABB Research
Andre Bondi, Software Performance and Scalability Consulting LLC
Johann Bourcier, Universite de Rennes 1, IRISA, INRIA
Ivona Brandic, Vienna University of Technology
Lubomir Bulej, Charles University
Radu Calinescu, University of York
Mihai Capota, Intel
Valeria Cardellini, Universita di Tor Vergata
Tse-Hsun Peter Chen, Concordia University
Wenguang Chen, Tsinghua University
Lucy Cherkasova, ARM Research
Juergen Cito,TU Wien and Facebook
Vittorio Cortellessa, University of L'Aquila
Antinisca Di Marco, University of L'Aquila
Joerg Domaschka, Ulm University
Maryam Elahi, Mount Royal University
Vincenzo Ferme, USI Lugano
Antonio Filieri, Imperial College London
Tian Guo, Worcester Polytechnic Institute
Wilhelm Hasselbring, Kiel University
Nikolas Herbst, University of Wuerzburg (Co-Chair)
Andre van Hoorn, University of Stuttgart
Vojtech Horky, Charles University
Pooyan Jamshidi, University of South Carolina
Evangelia Kalyvianaki, University of Cambridge
Rita Kapur, IIT Ropar, Punjab
William Knottenbelt, Imperial College London
Samuel Kounev, University of Wuerzburg
Heiko Koziolek, ABB Corporate Research
Diwakar Krishnamurthy, University of Calgary
Christoph Laaber, University of Zurich
Patrick P. C. Lee, The Chinese University of Hong Kong
Philipp Leitner, Chalmers (Co-Chair)
Marin Litoiu, York University
Catalina M. Llado, Universitat Illes Balears
Wes Llyod, University of Washington, Tacoma
Andrea Marin, Universita Ca'Foscari Venezia
Daniel Menasce, George Mason University
Jose Merseguer, Universidad de Zaragoza
Ningfang Mi, Northeastern University
Raffaela Mirandola, Politecnico di Milano
Manoj Nambiar, Tata Consultancy Services
Vittoria de Nitto Persone, Universita di Tor Vergata
Dusan Okanovic, Novatec Consulting Gmbh
Panos Patros, University of Waikato
Dorina Petriu, Carleton University
Upsorn Praphamontripong, University of Virginia
Weiyi Shang, Concordia University
Norbert Siegmund, Leipzig University
Evgenia Smirni, College of William and Mary
Connie Smith, Performance Engineering Services
Mirco Tribastone, IMT School for Advanced Studies Lucca
Catia Trubiani, Gran Sasso Science Institute
Petr Tuma, Charles University
Katinka Wolter, Freie Universitaet zu Berlin
Murray Woodside, Carleton University


Monica Beckwith, Hewlett Packard Enterprise
Andreas Brunnert, RETIT GmbH
Mathew Colgrove, NVIDIA
Huimin Cui, Institute of Computing Technology, Chinese Academy of Sciences
Raphael Eidenbenz, Hitachi ABB Power Grids Research
Carsten Franke, Munich University of Applied Sciences
Yaoqing Gao, Huawei (Co-Chair)
Carolin Heinrich, Hewlett Packard Enterprise
Vojtěch Horký, Charles University
João Paulo Labegalini de Carvalho, University of Alberta
Klaus-Dieter Lange, Hewlett Packard Enterprise
Ali Omar Abdelazim Mohammed, University of Basel
Meikel Poess, Oracle Corporation
Norbert Schmitt, University of Wuerzburg (Co-Chair)
Mark Stoodley, IBM
Peng Wu, Facebook
Teng Yu, Tsinghua University
Zhibin Yu, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

The PC committees for some tracks are not fully formed yet so the ICPE website
will keep involving to reflect such info.

General Chairs
Dan Feng, Huazhong University of Science and Technology, Wuhan, China
Steffen Becker, University of Stuttgart, Germany

Local Chair
Arthur Kang, Inspur, Peking, China

Research Program Chairs
Nikolas Herbst, University of Wuerzburg, Germany
Philipp Leitner, Chalmers | University of Gothenburg, Sweden

Industry Track Chair
Yaoqing Gao, Huawei, Canada
Norbert Schmitt, University of Wuerzburg, Germany

Artifact Evaluation Chairs
Emma Soederberg, Lund University, Sweden
Simon Eismann, University of Wuerzburg, Germany

Wip/Vision Chair
Cristina L. Abad, ESPOL, Ecuador

Workshops Chairs
Joerg Domaschka, University of Ulm, Germany
Fang Wang, Huazhong University of Science and Technology, Wuhan, China

Tutorials Chairs
David Daly, MongoDB, US
Shuibing He, Zhejiang University, Hangzhou, China

Posters and Demos Chairs
Christoph Laaber, University of Zurich, Switzerland
Wen Xia, Harbin Institute of Technology, Shenzhen, China

Data Challenge Chairs
Cor-Paul Bezemer, University of Alberta, Canada
David Daly, MongoDB, US
Weiyi Shang, Concordia University, Canada

Awards Chairs
Klaus-Dieter Lange, Hewlett Packard Enterprise, Texas, US
Diwakar Krishnamurthy, University of Calgary, Canada

Publicity Chairs
Martin Straesser, University of Wuerzburg, Germany
Yuchong Hu, Huazhong University of Science and Technology, Wuhan, China
Dmitry Duplyakin, University of Utah, US

Social-Media Chair
Hamdy Michael Ayas, Chalmers, University of Gothenburg, Sweden

Finance Chair
Steven Deng, Inspur, China

Publications Chair
Alessandro Papadopoulos, Maelardalen University, Sweden

Web Chair
Thomas Prantl, University of Wuerzburg, Germany

Virtualisation/Hybridisation Chair
Juergen Cito, TU Vienna, Austria

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