Proceedings of the 2018 ACM/SPEC International Conference

It is our great pleasure to welcome you to the 9th ACM/SPEC International Conference on Performance Engineering (ICPE 2018), being held in Berlin, Germany from April 9 to 13, 2018. The goal of the ACM/SPEC 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.

The call for contributions solicited submissions for several tracks, namely for research papers, industry/experience papers, work-in-progress/vision papers, artifacts (for accepted full papers), posters and demonstrations, tutorials, and workshops.

In the research track, 14 out of 59 papers were accepted as full papers. Hence, the full paper acceptance rate is 24 %. Two full papers received an ACM artifact badge after the subsequent review process in the newly introduced artifact evaluation track. Seven submissions were accepted as short research papers. In the industry/experience track, four out of 16 papers were accepted as full papers. Six submissions were accepted as short papers. The awards chairs selected three papers from the research track and two papers from the industry/experience track as candidates for the best paper award. The winner for both tracks will be announced during the banquet, after the candidates have presented their work during the conference. In the work-in-progress/vision track, ten out of 23 papers were accepted.

The technical program features the following three invited keynotes:

Peter Braam: Performance Engineering for the SKA Telescope
Michael R. Lyu: AI Techniques in Software Engineering Paradigm
Aad van Moorsel: Benchmarks and Models for Blockchain

In addition, the technical program includes three tutorials, the presentation of the SPEC Distinguished Dissertation Award, a poster and demonstration session, as well as six workshops on Performance Analysis of Big data Systems (PABS), Hot Topics in Cloud Computing Performance (HotCloudPerf), Challenges in Performance Methods for Software Development (WOSP-C), Load Testing and Benchmarking of Software Systems (LTB), Energy-aware Simulation and Modelling (ENERGY-SIM), and Quality-Aware DevOps (QUDOS).

The program covers traditional ICPE topics such as performance modeling, prediction, optimization, monitoring, profiling, load testing, benchmarking, and runtime adaptation for fields such as cloud and high performance computing, big data, energy, and enterprise applications.

Keynote and Invited Talks
Runtime Adaptation
High Performance Computing
Monitoring and Profiling
Cloud Computing
Enterprise Applications
Modeling, Prediction, and Optimization
Load Testing and Benchmarking

Keynote and Invited Talks

Performance Engineering for the SKA Telescope

Authors: Peter J. Braam
DOI: 10.1145/3184407.3184439
Pages: 1 – 1

AI Techniques in Software Engineering Paradigm

Authors: Michael R. Lyu
DOI: 10.1145/3184407.3184440
Pages: 2 – 2

Benchmarks and Models for Blockchain

Authors: Aad van Moorsel
DOI: 10.1145/3184407.3184441
Pages: 3 – 3

Runtime Adaptation

FOX: Cost-Awareness for Autonomic Resource Management in Public Clouds

Authors: Veronika Lesch; André Bauer; Nikolas Herbst; Samuel Kounev
DOI: 10.1145/3184407.3184415
Pages: 4 – 15

Adaptive Performance Optimization under Power Constraint in Multi-thread Applications with Diverse Scalability

Authors: Stefano Conoci; Pierangelo Di Sanzo; Bruno Ciciani; Francesco Quaglia
DOI: 10.1145/3184407.3184419
Pages: 16 – 27

Optimising Dynamic Binary Modification Across ARM Microarchitectures

Authors: Cosmin Gorgovan; Amanieu d’Antras; Mikel Luján
DOI: 10.1145/3184407.3184425
Pages: 28 – 39

TESS: Automated Performance Evaluation of Self-Healing and Self-Adaptive Distributed Software Systems

Authors: Jason Porter; Daniel A. Menascé; Hassan Gomaa; Emad Albassam
DOI: 10.1145/3184407.3184408
Pages: 40 – 47

To Adapt or Not to Adapt?: Technical Debt and Learning Driven Self-Adaptation for Managing Runtime Performance

Authors: Tao Chen; Rami Bahsoon; Shuo Wang; Xin Yao
DOI: 10.1145/3184407.3184413
Pages: 48 – 55

High Performance Computing

Involving CPUs into Multi-GPU Deep Learning

Authors: Tung D. Le; Taro Sekiyama; Yasushi Negishi; Haruki Imai; Kiyokuni Kawachiya
DOI: 10.1145/3184407.3184424
Pages: 56 – 67

Measuring Network Latency Variation Impacts to High Performance Computing Application Performance

Authors: Robert Underwood; Jason Anderson; Amy Apon
DOI: 10.1145/3184407.3184427
Pages: 68 – 79

Pattern-based Modeling of Multiresilience Solutions for High-Performance Computing

Authors: Rizwan A. Ashraf; Saurabh Hukerikar; Christian Engelmann
DOI: 10.1145/3184407.3184421
Pages: 80 – 87

Energy and Performance Analysis of Parallel Particle Solvers from the ScaFaCoS Library

Authors: Michael Hofmann; Robert Kiesel; Gudula Rünger
DOI: 10.1145/3184407.3184409
Pages: 88 – 95

Characterizing the Microarchitectural Implications of a Convolutional Neural Network (CNN) Execution on GPUs

Authors: Shi Dong; Xiang Gong; Yifan Sun; Trinayan Baruah; David Kaeli
DOI: 10.1145/3184407.3184423
Pages: 96 – 106

Monitoring and Profiling

Round-Trip Time Anomaly Detection

Authors: Daniel Brahneborg; Wasif Afzal; Adnan Čaušević; Daniel Sundmark; Mats Björkman
DOI: 10.1145/3184407.3184436
Pages: 107 – 114

User-defined Classification and Multi-level Grouping of Objects in Memory Monitoring

Authors: Markus Weninger; Hanspeter Mössenböck
DOI: 10.1145/3184407.3184412
Pages: 115 – 126

Log4Perf: Suggesting Logging Locations for Web-based Systems’ Performance Monitoring

Authors: Kundi Yao; Guilherme B. de Pádua; Weiyi Shang; Steve Sporea; Andrei Toma; Sarah Sajedi
DOI: 10.1145/3184407.3184416
Pages: 127 – 138

ODP: An Infrastructure for On-Demand Service Profiling

Authors: John Nicol; Chen Li; Peinan Chen; Tao Feng; Haricharan Ramachandra
DOI: 10.1145/3184407.3184433
Pages: 139 – 144

Cloud Computing

Virtualization Techniques Compared: Performance, Resource, and Power Usage Overheads in Clouds

Authors: Selome Kostentinos Tesfatsion; Cristian Klein; Johan Tordsson
DOI: 10.1145/3184407.3184414
Pages: 145 – 156

Investigating Performance Metrics for Scaling Microservices in CloudIoT-Environments

Authors: Manuel Gotin; Felix Lösch; Robert Heinrich; Ralf Reussner
DOI: 10.1145/3184407.3184430
Pages: 157 – 167

Evaluating Scalability and Performance of a Security Management Solution in Large Virtualized Environments

Authors: Lishan Yang; Ludmila Cherkasova; Rajeev Badgujar; Jack Blancaflor; Rahul Konde; Jason Mills; Evgenia Smirni
DOI: 10.1145/3184407.3184435
Pages: 168 – 175

Runtime Performance Management for Cloud Applications with Adaptive Controllers

Authors: Cornel Barna; Marin Litoiu; Marios Fokaefs; Mark Shtern; Joe Wigglesworth
DOI: 10.1145/3184407.3184438
Pages: 176 – 183

Rapid Testing of IaaS Resource Management Algorithms via Cloud Middleware Simulation

Authors: Christian Stier; Jörg Domaschka; Anne Koziolek; Sebastian Krach; Jakub Krzywda; Ralf Reussner
DOI: 10.1145/3184407.3184428
Pages: 184 – 191

Performance Prediction of Cloud-Based Big Data Applications

Authors: Danilo Ardagna; Enrico Barbierato; Athanasia Evangelinou; Eugenio Gianniti; Marco Gribaudo; Túlio B. M. Pinto; Anna Guimarães; Ana Paula Couto da Silva; Jussara M. Almeida
DOI: 10.1145/3184407.3184420
Pages: 192 – 199

Enterprise Applications

Generating Workload for ERP Applications through End-User Organization Categorization using High Level Business Operation Data

Authors: Gururaj Maddodi; Slinger Jansen; Rolf de Jong
DOI: 10.1145/3184407.3184432
Pages: 200 – 210

One Size Does Not Fit All: In-Test Workload Adaptation for Performance Testing of Enterprise Applications

Authors: Vanessa Ayala-Rivera; Maciej Kaczmarski; John Murphy; Amarendra Darisa; A. Omar Portillo-Dominguez
DOI: 10.1145/3184407.3184418
Pages: 211 – 222