Companion Publication for ACM/SPEC on International Conference on Performance Engineering最新文献

{"title":"Tutorial on Challenges for Big Data Application Performance Tuning and Prediction","authors":"Rekha Singhal","doi":"10.1145/2859889.2883587","DOIUrl":"https://doi.org/10.1145/2859889.2883587","url":null,"abstract":"Digitization of user services and cheap access to the internet has led to two critical problems- quick response to end-user queries and faster analysis of large accumulated data to serve users better. This has also led to the advent of various big data processing technologies, each of them has architecture specific parameters to tune for optimal execution of the application. There are also challenges in optimal scheduling of analytic queries for faster analysis, which lead to the problem of estimating analytic queries execution time for large data sizes on the production system. A production system may be an enterprise database system or a cluster of machines with Hadoop etc, where each machine may be of different hardware configuration (known as heterogeneous environment). In the first part of this tutorial, we shall present need and challenges for tuning big data applications on various platforms. This is followed by discussion on various existing solutions for application tuning. The second part of the tutorial presents the challenges and state of the art for estimating application execution time.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116116321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Analysis of Load Test Results of Systems with Equilibrium or Transient Behavior: Invited Talk","authors":"A. Bondi","doi":"10.1145/2859889.2880447","DOIUrl":"https://doi.org/10.1145/2859889.2880447","url":null,"abstract":"Performance test data should be analyzed to determine if performance requirements are being met, to see if they reveal opportunities for performance improvement, and to see if they show signs of lurking performance issues or malfunctions. Automated analyses of the measurements can be useful when the number of resource usage measures and performance measures is large, when the number of nodes under test is large, or when the number of test cases is large. We shall examine this for cases in which the system under test is subjected to a constant load, as might be the case for an online transaction processing system, and for the case where the load is inherently bursty, as would be the case for an alarm or monitoring system that is receiving streams of notifications from many sensors at once. We expect a well behaved system under constant load to reach steady state shortly after the test load begins, and to ramp down to its previous state once the load is withdrawn. This corresponds to a system reaching equilibrium in stochastic terms. We also expect a well behaved system to return to steady state after a surge of traffic abates. Failure to achieve equilibrium under constant load is a sign of a problem that should be investigated. Automated analysis of voluminous test data facilitates the identification of intervals of steady operation and cases when steady operation has not occurred during performance tests. An embedded control or monitoring system, such as a building security system, might be subject to a sustained burst of message traffic in an emergency situation. Fire alarm systems might have to respond to at least one of these messages within seconds of the onset of the burst by triggering bells and sirens, closing doors, and automatically alerting emergency services. They might consist of only a few hosts. An automated tool could use statistical methods to identify phases of execution during an emergency by noting when each thread's processor consumption changes. This facilitates the identification of areas for performance improvement, especially if the system is implemented with so many processes or threads that visual identification of heavy consumers of processing power is difficult. We shall elaborate on these issues in this talk, and also discuss methods for performing automated analyses of load tests of systems whose loads are expected to be steady and of systems whose loads are expected to be intense for a transient period.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116556507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: WOSP'16","authors":"A. Koziolek","doi":"10.1145/3257769","DOIUrl":"https://doi.org/10.1145/3257769","url":null,"abstract":"It is a great pleasure to welcome you to the 2016 Workshop on Challenges in Performance Methods for Software Development -- WOSP-C'16. This second edition of our workshop continues to explore the challenges and to identify the most promising lines of attack on them. As such, this workshop repeats some aspects of WOSP98, the initial Workshop on Software and Performance, which successfully identified the issues of that time. The acronym WOSP-C reflects this. A third of the time will be devoted to discussion on identifying the key problems and the most fruitful lines of future research. WOSP-C continues to give researchers and practitioners a unique opportunity to share their perspectives on the future challenges of software performance engineering. We also encourage attendees to attend the invited talk by Murray Woodside. This talk, the paper presentations, and the discussions at the workshop will guide us to a better understanding of the future of software performance engineering.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126468611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: PABS'16","authors":"Rekha Singhal, Dheeraj Chahal","doi":"10.1145/3257768","DOIUrl":"https://doi.org/10.1145/3257768","url":null,"abstract":"It is our great pleasure to welcome you to the 2016 ACM Workshop on Performance Analysis of Big Data Systems -- PABS'16 in conjunction with ICPE2016. The main objective of the workshop is to discuss the performance challenges imposed by big data systems and the different state-of-the-art solutions proposed to overcome these challenges. The workshop aims at providing a platform for scientific researchers, academicians and practitioners to discuss techniques, models, benchmarks, tools and experiences while dealing with performance issues in big data systems. The program committee reviewed 4 and accepted 2 full technical papers with acceptance rate as 50%. We welcome attendees to attend the keynote, invited talk, tutorial and paper presentations. These valuable and insightful talks can and will guide us to a better understanding of the future: Challenges in Truly Scaling Services, Manish Gupta (Director, Xerox Research Center, India) Performance Engineering for In-Memory Databases: Models, Experiments and Optimization, Giuliano Casale (Sr. Lecturer, Imperial College London.) Big Data Applications Performance Assurance, Boris Zibitsker ( CEO BEZNext, USA) Tutorial on Challenges for Big Data Application Performance Tuning and Prediction, Rekha Singhal (Sr. Scientist, TCS Innovation Labs).","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131683140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Engineering for In-Memory Databases: Models, Experiments and Optimization","authors":"G. Casale","doi":"10.1145/2859889.2883585","DOIUrl":"https://doi.org/10.1145/2859889.2883585","url":null,"abstract":"The recent growth of interest for in-memory databases poses the question on whether established performance engineering methods such as analytical models, response surfaces and queueing simulation are effective in describing these database systems. In this talk, I will discuss our recent work on analytical models for performance assessment and optimization of inmemory databases. These include novel response time approximations under online analytical processing workloads to model thread-level fork-join and per-class memory occupation. I will then discuss the relative merits of performance modelling compared to experimental design methods that generate response surfaces and our recent experience on optimal workload placement in such systems.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133341818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","authors":"Alberto Avritzer, A. Iosup, Xiaoyun Zhu, Steffen Becker","doi":"10.1145/2859889","DOIUrl":"https://doi.org/10.1145/2859889","url":null,"abstract":"The 7th ACM/SPEC International Conference on Performance Engineering (ICPE 2016) takes place in Delft in The Netherlands in March 2016. The conference grew out of the ACM Workshop on Software Performance (WOSP since 1998) and the SPEC International Performance Engineering Workshop (SIPEW since 2008), with the goal of integrating theory and practice in the field of performance engineering. It is a great pleasure for us to offer an outstanding technical program this year, which we believe will allow researchers and practitioners to present their visions and latest innovation, and to exchange ideas within the community. \u0000 \u0000Overall, we received 89 high quality submissions across all three tracks. The main Research Track attracted 57 submissions with 19 accepted (33% acceptance rate) for presentation at the conference. Among them were 16 full papers and three short papers. Each paper received at least three reviews from experienced program committee members. In the Work-In-Progress and Vision Track, six out of 15 contributions were selected. The Industry and Experience Track received 17 submissions, of which seven were selected for inclusion in the program. The accepted papers were organized into five research track sessions, two industry track sessions, and one WiP and vision track session. Three best paper candidates were also selected: two research papers and one industry paper. \u0000 \u0000We are proud to have three excellent keynote speakers as part of our technical program: \u0000Bianca Schroeder from University of Toronto, Canada, presenting \"Case studies from the real world: The importance of measurement and analysis in building better systems\" \u0000Wilhelm Hasselbring from Kiel University, Germany, discussing \"Microservices for Scalability\" \u0000Angelo Corsaro, Chief Technology Officer at PrismTech, talking about \"Cloudy, Foggy and Misty Internet of Things\" \u0000 \u0000 \u0000 \u0000In addition, the program includes four tutorials, a doctoral symposium, a poster and demo track, the SPEC Distinguished Dissertation Award, and three interesting workshops, including the International Workshop on Large-Scale Testing (LT), the 2nd International Workshop on Performance Analysis of Big data Systems (PABS), and the 2nd Workshop on Challenges in Performance Methods for Software Development (WOSPC). \u0000 \u0000The program covers traditional ICPE topics such as software and systems performance modeling and prediction, analysis and optimization, characterization and profiling, as well as application of performance engineering theory and techniques to several practical fields, including distributed systems, cloud computing, storage, energy, big data, virtualized systems and containers.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129497356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Testing in Software Development: Getting the Developers on Board","authors":"L. Bulej","doi":"10.1145/2859889.2880448","DOIUrl":"https://doi.org/10.1145/2859889.2880448","url":null,"abstract":"Society is increasingly dependent on software-intensive systems that are required to interact with a huge number of users and respond in timely manner. Failing that often results in users and consumers not being able to access the advertised services or products, or worse, citizens unable to access vital services provided by the state. In such systems, failures are more likely to be caused by performance issues than by faulty implementation of some features [3, 1]. Modern development processes for general-purpose software systems typically focus on managing complexity to deliver correctly functioning software on time, and best software development practices frown upon premature optimization. With other aspects of software design and construction put above performance concerns, performance becomes a secondary concern that only needs to be addressed if the system’s performance turns out to be unsatisfactory. This contrasts with real-time systems, where meeting realtime performance requirements is essential, and performance is a primary design concern that permeates the development process and the resulting system as a whole. Consequently, the overall performance of the system is a concern that cannot be addressed locally—it must be designed into the system, and strictly controlled throughout its construction. Simply adopting the process of real-time system development for the development of general-purpose systems is not possible. The size, complexity, and the depth of the software stack used to build general-purpose software-intensive systems typically dwarfs that of the special-purpose missionor safety-critical real-time systems. The level of control that can be exerted over individual elements of real-time systems either does not scale, or is not possible at all, in addition to performance requirements being usually much less precise, and not easily expressed in terms of latencies or deadlines. The productivity of developers during development is also an important aspect. Where real-time systems limit development flexibility to maintain control over performance (by avoiding many features of modern runtime platforms unless their performance impact can be sufficiently controlled),","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123145522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: LT'16","authors":"Christian Vögele, Z. Jiang","doi":"10.1145/3257767","DOIUrl":"https://doi.org/10.1145/3257767","url":null,"abstract":"It is our great pleasure to welcome you to the Fifth International Workshop on Large-Scale Testing (LT 2016), held in Delft, the Netherlands, on March 12th, 2016. Large-scale software systems must service thousands (e.g., enterprise applications) or even millions (e.g., e-commerce websites like Amazon) of concurrent users every day. Many field problems of these systems are due to their inability to scale to field workloads, rather than featurebugs. In addition to conventional functional testing (e.g., unit and integration testing), these systems must be tested with large volumes of concurrent requests (called the load) to ensure the quality of these systems. Large-scale testing includes all different objectives and strategies of testing large-scale software systems using load. Examples of large-scale testing include live upgrade testing, load testing, high availability testing, operational profile testing, performance testing, reliability testing, stability testing and stress testing. LT 2016 is a one-day workshop. The workshop participants consist of a mixture of academic and industrial researchers. A big emphasis of this workshop is to make the workshop interactive with many discussion slots assigned throughout the schedule. The workshop has two keynote talks: \"Automated Analysis of Load Test Results of Systems with Equilibrium or Transient Behaviour\" by Dr. André Bondi and \"Performance Testing in Software Development: Getting the Developers on Board\" by Professor Lubomír Bulej from Charles University. In addition, the workshop also includes presentations from technical papers and industrial talks. Finally, there is a discussion panel, which brings together industrial practitioners and academic researchers to discuss the opportunities and challenges associated with large-scale testing. We hope you enjoy the technical and social program. If you are not able to attend our workshop, we hope you will find the papers and talks in this workshop stimulating. This workshop would not happen without the efforts of the program committee members who helped with timely and constructive reviews. In addition, we want to extend our gratitude to each author and presenter who submitted their work to the LT 2016 workshop.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122321124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Constraint Programming Based Energy Aware Resource Management Middleware for Clouds Processing MapReduce Jobs with Deadlines","authors":"A. Gregory, S. Majumdar","doi":"10.1145/2859889.2859892","DOIUrl":"https://doi.org/10.1145/2859889.2859892","url":null,"abstract":"This paper concerns guarantees on system performance through Service Level Agreement (SLA) compliance and focuses on devising energy aware resource management techniques based on Dynamic Voltage and Frequency Scaling (DVFS) used by resource management middleware in clouds that handle MapReduce jobs. This research formulates the resource management problem as an optimization problem using Constraint Programming (CP). Experimental results presented in the paper demonstrate the effectiveness of the technique.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115030935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of Techniques to Improve the Utilization of Cloud Elasticity in Workload-aware Adaptive Software","authors":"Diego Perez-Palacin, R. Mirandola, Marco Scoppetta","doi":"10.1145/2859889.2859897","DOIUrl":"https://doi.org/10.1145/2859889.2859897","url":null,"abstract":"More and more software owners consider moving their IT infrastructure to the cloud. At present, cloud providers offer easy manners to deploy software artifacts. Therefore, the profile of cloud clients is no longer limited to computing experts. However, an appropriate configuration of the elasticity offered by cloud computing is still complicated. To help these clients, this work presents a simulator of the behavior of software services that run on the cloud and use the cloud elasticity for adapting their infrastructure in order to accommodate their workload in each moment. This work identifies techniques that are used to help mitigating at runtime the lack of predictability of workload changes. The presented simulator implements the identified techniques and allows users to execute scenarios where a combination of these techniques is enabled.","PeriodicalId":265808,"journal":{"name":"Companion Publication for ACM/SPEC on International Conference on Performance Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127700201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}