Proceedings of the 5th ACM/SPEC international conference on Performance engineering最新文献_第2页

Real-time multi-cloud management needs application awareness 实时多云管理需要应用意识

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2576763

J. Chinneck, Marin Litoiu, C. Woodside

引用次数: 6

A power-measurement methodology for large-scale, high-performance computing 一种用于大规模高性能计算的功率测量方法

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2576795

T. Scogland, C. Steffen, T. Wilde, Florent Parent, S. Coghlan, Natalie J. Bates, Wu-chun Feng, E. Strohmaier

{"title":"A power-measurement methodology for large-scale, high-performance computing","authors":"T. Scogland, C. Steffen, T. Wilde, Florent Parent, S. Coghlan, Natalie J. Bates, Wu-chun Feng, E. Strohmaier","doi":"10.1145/2568088.2576795","DOIUrl":"https://doi.org/10.1145/2568088.2576795","url":null,"abstract":"Improvement in the energy efficiency of supercomputers can be accelerated by improving the quality and comparability of efficiency measurements. The ability to generate accurate measurements at extreme scale are just now emerging. The realization of system-level measurement capabilities can be accelerated with a commonly adopted and high quality measurement methodology for use while running a workload, typically a benchmark. This paper describes a methodology that has been developed collaboratively through the Energy Efficient HPC Working Group to support architectural analysis and comparative measurements for rankings, such as the Top500 and Green500. To support measurements with varying amounts of effort and equipment required we present three distinct levels of measurement, which provide increasing levels of accuracy. Level 1 is similar to the Green500 run rules today, a single average power measurement extrapolated from a subset of a machine. Level 2 is more comprehensive, but still widely achievable. Level 3 is the most rigorous of the three methodologies but is only possible at a few sites. However, the Level 3 methodology generates a high quality result that exposes details that the other methodologies may miss. In addition, we present case studies from the Leibniz Supercomputing Centre (LRZ), Argonne National Laboratory (ANL) and Calcul Québec Université Laval that explore the benefits and difficulties of gathering high quality, system-level measurements on large-scale machines.","PeriodicalId":243233,"journal":{"name":"Proceedings of the 5th ACM/SPEC international conference on Performance engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132383470","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}

引用次数: 32

A meta-controller method for improving run-time self-architecting in SOA systems 用于改进SOA系统中运行时自架构的元控制器方法

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2568098

J. M. Ewing, D. Menascé

{"title":"A meta-controller method for improving run-time self-architecting in SOA systems","authors":"J. M. Ewing, D. Menascé","doi":"10.1145/2568088.2568098","DOIUrl":"https://doi.org/10.1145/2568088.2568098","url":null,"abstract":"This paper builds on SASSY, a system for automatically generating SOA software architectures that optimize a given utility function of multiple QoS metrics. In SASSY, SOA software systems are automatically re-architected when services fail or degrade. Optimizing both architecture and service provider selection presents a pair of nested NP-hard problems. Here we adapt hill-climbing, beam search, simulated annealing, and evolutionary programming to both architecture optimization and service provider selection. Each of these techniques has several parameters that influence their efficiency. We introduce in this paper a meta-controller that automates the run-time selection of heuristic search techniques and their parameters. We examine two different meta-controller implementations that each use online learning. The first implementation identifies the best heuristic search combination from various prepared combinations. The second implementation analyzes the current self-architecting problem (e.g. changes in performance metrics, service degradations/failures) and looks for similar, previously encountered re-architecting problems to find an effective heuristic search combination for the current problem. A large set of experiments demonstrates the effectiveness of the first meta-controller implementation and indicates opportunities for improving the second meta-controller implementation.","PeriodicalId":243233,"journal":{"name":"Proceedings of the 5th ACM/SPEC international conference on Performance engineering","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122521006","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}

引用次数: 14

Scalable hybrid stream and hadoop network analysis system 可扩展的混合流和hadoop网络分析系统

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2568103

V. Bumgardner, V. Marek

{"title":"Scalable hybrid stream and hadoop network analysis system","authors":"V. Bumgardner, V. Marek","doi":"10.1145/2568088.2568103","DOIUrl":"https://doi.org/10.1145/2568088.2568103","url":null,"abstract":"Collections of network traces have long been used in network traffic analysis. Flow analysis can be used in network anomaly discovery, intrusion detection and more generally, discovery of actionable events on the network. The data collected during processing may be also used for prediction and avoidance of traffic congestion, network capacity planning, and the development of software-defined networking rules. As network flow rates increase and new network technologies are introduced on existing hardware platforms, many organizations find themselves either technically or financially unable to generate, collect, and/or analyze network flow data. The continued rapid growth of network trace data, requires new methods of scalable data collection and analysis. We report on our deployment of a system designed and implemented at the University of Kentucky that supports analysis of network traffic across the enterprise. Our system addresses problems of scale in existing systems, by using distributed computing methodologies, and is based on a combination of stream and batch processing techniques. In addition to collection, stream processing using Storm is utilized to enrich the data stream with ephemeral environment data. Enriched stream-data is then used for event detection and near real-time flow analysis by an in-line complex event processor. Batch processing is performed by the Hadoop MapReduce framework, from data stored in HBase BigTable storage. In benchmarks on our 10 node cluster, using actual network data, we were able to stream process over 315k flows/sec. In batch analysis were we able to process over 2.6M flows/sec with a storage compression ratio of 6.7:1.","PeriodicalId":243233,"journal":{"name":"Proceedings of the 5th ACM/SPEC international conference on Performance engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115059259","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}

引用次数: 27

On the limits of modeling generational garbage collector performance 关于分代垃圾收集器性能建模的限制

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2568097

P. Libic, L. Bulej, Vojtech Horký, P. Tůma

引用次数: 19

Test-driving Intel Xeon Phi 测试英特尔Xeon Phi

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2576799

Jianbin Fang, H. Sips, Lilun Zhang, Chuanfu Xu, Yonggang Che, A. Varbanescu

{"title":"Test-driving Intel Xeon Phi","authors":"Jianbin Fang, H. Sips, Lilun Zhang, Chuanfu Xu, Yonggang Che, A. Varbanescu","doi":"10.1145/2568088.2576799","DOIUrl":"https://doi.org/10.1145/2568088.2576799","url":null,"abstract":"Based on Intel's Many Integrated Core (MIC) architecture, Intel Xeon Phi is one of the few truly many-core CPUs - featuring around 60 fairly powerful cores, two levels of caches, and graphic memory, all interconnected by a very fast ring. Given its promised ease-of-use and high performance, we took Xeon Phi out for a test drive. In this paper, we present this experience at two different levels: (1) the microbenchmark level, where we stress \"each nut and bolt\" of Phi in the lab, and (2) the application level, where we study Phi's performance response in a real-life environment. At the microbenchmarking level, we show the high performance of five components of the architecture, focusing on their maximum achieved performance and the prerequisites to achieve it. Next, we choose a medical imaging application (Leukocyte Tracking) as a case study. We observed that it is rather easy to get functional code and start benchmarking, but the first performance numbers can be far from satisfying. Our experience indicates that a simple data structure and massive parallelism are critical for Xeon Phi to perform well. When compiler-driven parallelization and/or vectorization fails, programming Xeon Phi for performance can become very challenging.","PeriodicalId":243233,"journal":{"name":"Proceedings of the 5th ACM/SPEC international conference on Performance engineering","volume":"315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123154302","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}

引用次数: 99

Server efficiency rating tool (SERT) 1.0.2: an overview 服务器效率评估工具(SERT) 1.0.2:概述

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2576094

Hansfried Block, J. Arnold, John Beckett, Sanjay Sharma, Michael G. Tricker, Kyle M. Rogers

引用次数: 2

Performance queries for architecture-level performance models 架构级性能模型的性能查询

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2568100

F. Gorsler, Fabian Brosig, Samuel Kounev

引用次数: 15

Extreme big data processing in large-scale graph analytics and billion-scale social simulation 大规模图形分析和十亿规模社会模拟中的极端大数据处理

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2576096

T. Suzumura

引用次数: 1

Efficient and accurate stack trace sampling in the Java hotspot virtual machine 在Java热点虚拟机中高效准确的堆栈跟踪采样

Proceedings of the 5th ACM/SPEC international conference on Performance engineering Pub Date : 2014-03-22 DOI: 10.1145/2568088.2576759

Peter Hofer, H. Mössenböck

引用次数: 5