The goal of the International Conference on Performance Engineering (ICPE) is to integrate theory and practice in the field of performance engineering by providing a forum for sharing ideas and experiences between industry and academia. Nowadays, complex
systems of all types, like Web-based systems, data centers and cloud infrastructures, social networks, peer-to-peer, mobile and wireless systems, cyber-physical systems, the Internet of Things, real-time and embedded systems, have increasingly
distributed and dynamic system architectures that provide high flexibility, however, also increase the complexity of managing end-to-end application performance.
ICPE brings together researchers and industry practitioners to share and present their experiences, discuss challenges, and 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, and security.
ICPE'17 takes place from April 22 to 27, 2017.
The main conference runs from April 24 to 26, with a welcome reception on April 24 and a banquet on April 25.
Tutorials are held on April 22 and 23, while workshops take place on April 22, 23, and 27.
The following eight workshops will be held in conjunction with the main conference:
- Saturday, April 22:
-- ACPROSS: Autonomous Control for Performance and Reliability Trade-offs in Internet of Services
-- PABS: Third International Workshop on Performance Analysis of Big Data Systems
-- WOSP-C: Workshop on Challenges in Performance Methods for Software Development
- Sunday, April 23:
-- ENERGY-SIM: Third International Workshop on Energy-aware Simulation
-- LTB: Sixth International Workshop on Load Testing and Benchmarking of Software Systems
-- MoLS: First International Workshop on Monitoring in Large-Scale Software Systems
-- WEPPE: Workshop on Education and Practice of Performance Engineering
- Thursday, April 27:
-- QUDOS: Third International Workshop on Quality-aware DevOps
We are proud to announce our keynote speakers for ICPE'17:
Title: Autonomic storage management at scale
Cloud data centers use enormous amounts of storage, and it is critical to monitor, manage, and optimize the storage autonomically. Optimally configuring storage is difficult because storage workloads are very diverse and change over time. Data centers
measure running workloads, but this measurement data stream is itself quite large. We present some real world case studies in the use of big data techniques, sampling, and optimization to manage storage in data centers.
Arif Merchant is a Research Scientist at Google and leads the Storage Analytics group, which studies interactions between components of the storage stack. His interests include distributed storage systems, storage management, and stochastic modeling. He
holds the B.Tech. degree from IIT Bombay and the Ph.D. in Computer Science from Stanford University. He is an ACM Distinguished Scientist.
(University of Rome "La Sapienza")
Title: Performance is Also a Matter of Where You Live
Nowadays, a plethora of techniques and methods are available to optimize the runtime behavior of complex applications, ranging from modeling/prediction tools to the employment of recognized patterns and/or knowledge-bases on the expected performance
under specific workloads. However, in common scenarios, the ultimate applications' behavior may depend on features that are scarcely predictable or difficult to be taken into account when designing the applications and their own runtime optimizers. Among
them, we mention the actual structure of the underlying hardware and/or virtualized platforms, as well as specific runtime dynamics such as thread correlation on data and synchronization---not much the average behavior, rather punctual effects. We
believe that the environment where applications live, like operating systems and user-space runtime libraries, play a central role in coping with these features. We similarly believe that such environments must be re-staged so as to be actually effective
in pursuing the performance optimization goal. In this talk, we discuss specific guidelines to re-stage the environments, based on a real experience, and we point as well to challenges that are still untackled and deserve attention by the research
Francesco Quaglia received the Laurea degree (MS level) in Electronic Engineering in 1995 and the PhD degree in Computer Engineering in 1999 from the University of Rome ``La Sapienza''. From summer 1999 to summer 2000 he held an appointment as a
Researcher at the Italian National Research Council (CNR). Since January 2005 he works as an Associate Professor at the School of Engineering of the University of Rome ``La Sapienza", where he has previously worked as an Assistant Professor since
September 2000 to December 2004. His main research interests are in the areas of high performance computing, dependable computing, transactional systems, operating systems, automatic code parallelization, performance analysis and optimization. Currently,
he is the director of the HPDCS (High Performance and Dependable Computing Systems) Research Lab at the University of Rome ``La Sapienza''.
Title: Micro-Benchmarking Considered Harmful
Subtitle: When the Whole is Faster or Slower Than the Sum of its Parts
Measuring the time spent on small individual fractions of program code is a common technique for analysing performance behavior and detecting performance bottlenecks. The benefits of the approach include a detailed individual attribution of performance
and understandable feedback loops when experimenting with different code versions. There are however severe pitfalls when following this approach that can lead to vastly misleading results. Modern optimizing compilers use complex optimization techniques
that take a large part of the program into account. There can be therefore unexpected side-effects when combining different code snippets or even when running a presumably unrelated part of the code. This talk will present performance paradoxes with
examples from the domain of dynamic compilation of Java programs. Furthermore, it will discuss an alternative approach to modelling code performance characteristics that takes the challenges of complex optimising compilers into account.
system. Previously, he worked on the Crankshaft optimizing compiler of V8 at Google, and the Maxine research virtual machine at Sun Microsystems. He received a PhD degree from JKU Linz for his research about dynamic code evolution.
* Walter Binder, Università della Svizzera italiana (USI), Switzerland
* Vittorio Cortellessa, Università dell'Aquila, Italy
Research Program Chairs
* Anne Koziolek, Karlsruhe Institute of Technology, Germany
* Evgenia Smirni, College of William and Mary, USA
Industry Program Chairs
* Meikel Poess, Oracle, USA
* Valeria Cardellini, Università di Roma Torvergata, Italy
* Hanspeter Mössenböck, Johannes Kepler Universität Linz, Austria
* Catia Trubiani, Gran Sasso Science Institute, Italy
Posters and Demos Chair
* Lubomir Bulej, Charles University, Czech Republic
* Petr Tuma, Charles University, Czech Republic
* Murray Woodside, Carleton University, Canada
Local Organization Chair
* Antinisca Di Marco, Università dell'Aquila, Italy
* Andrea Rosà, Università della Svizzera italiana (USI), Switzerland
* Diego Perez, Politecnico di Milano, Italy
* André van Hoorn, University of Stuttgart
Publication and Registration Chair
* Davide Arcelli, Università dell'Aquila, Italy
Web Site Chair
* Daniele Di Pompeo, Università dell'Aquila, Italy