ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)最新文献_第9页

PREFiguRE 预示

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-05-07 DOI: 10.1145/2872331

Feng Yan, X. Mountrouidou, Alma Riska, E. Smirni

引用次数: 3

Estimating the Transmission Probability in Wireless Networks with Configuration Models 用组态模型估计无线网络的传输概率

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-04-21 DOI: 10.1145/2858795

P. Bermolen, M. Jonckheere, Federico Larroca, P. Moyal

引用次数: 7

Dealing with Dead Ends 处理死胡同

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-02-22 DOI: 10.1145/2809779

Stefanie Roos, T. Strufe

{"title":"Dealing with Dead Ends","authors":"Stefanie Roos, T. Strufe","doi":"10.1145/2809779","DOIUrl":"https://doi.org/10.1145/2809779","url":null,"abstract":"Darknets, membership-concealing peer-to-peer networks, suffer from high message delivery delays due to insufficient routing strategies. They form topologies restricted to a subgraph of the social network of their users by limiting connections to peers with a mutual trust relationship in real life. Whereas centralized, highly successful social networking services entail a privacy loss of their users, Darknets at higher performance represent an optimal private and censorship-resistant communication substrate for social applications. Decentralized routing so far has been analyzed under the assumption that the network resembles a perfect lattice structure. Freenet, currently the only widely used Darknet, attempts to approximate this structure by embedding the social graph into a metric space. Considering the resulting distortion, the common greedy routing algorithm is adapted to account for local optima. Yet the impact of the adaptation has not been adequately analyzed. We thus suggest a model integrating inaccuracies in the embedding. In the context of this model, we show that the Freenet routing algorithm cannot achieve polylog performance. Consequently, we design NextBestOnce, a provable poylog algorithm based only on information about neighbors. Furthermore, we show that the routing length of NextBestOnce is further decreased by more than a constant factor if neighbor-of-neighbor information is included in the decision process.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120953467","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: 2

Sojourn Time Approximations for a Discriminatory Processor Sharing Queue 判别处理器共享队列的逗留时间逼近

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-02-22 DOI: 10.1145/2812807

A. Izagirre, U. Ayesta, M. Verloop

引用次数: 5

Validating the Simulation of Large-Scale Parallel Applications Using Statistical Characteristics 利用统计特性验证大规模并行应用的仿真

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-02-12 DOI: 10.1145/2809778

Deli Zhang, Jeremiah J. Wilke, G. Hendry, D. Dechev

{"title":"Validating the Simulation of Large-Scale Parallel Applications Using Statistical Characteristics","authors":"Deli Zhang, Jeremiah J. Wilke, G. Hendry, D. Dechev","doi":"10.1145/2809778","DOIUrl":"https://doi.org/10.1145/2809778","url":null,"abstract":"Simulation is a widely adopted method to analyze and predict the performance of large-scale parallel applications. Validating the hardware model is highly important for complex simulations with a large number of parameters. Common practice involves calculating the percent error between the projected and the real execution time of a benchmark program. However, in a high-dimensional parameter space, this coarse-grained approach often suffers from parameter insensitivity, which may not be known a priori. Moreover, the traditional approach cannot be applied to the validation of software models, such as application skeletons used in online simulations. In this work, we present a methodology and a toolset for validating both hardware and software models by quantitatively comparing fine-grained statistical characteristics obtained from execution traces. Although statistical information has been used in tasks like performance optimization, this is the first attempt to apply it to simulation validation. Our experimental results show that the proposed evaluation approach offers significant improvement in fidelity when compared to evaluation using total execution time, and the proposed metrics serve as reliable criteria that progress toward automating the simulation tuning process.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129273861","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: 1

Employing Software-Managed Caches in OpenACC 在OpenACC中使用软件管理缓存

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-02-12 DOI: 10.1145/2798724

Ahmad Lashgar, A. Baniasadi

引用次数: 9

Selecting the Top-Quality Item Through Crowd Scoring 通过人群评分选择最优质的项目

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2015-12-23 DOI: 10.1145/3157736

A. Nordio, A. Tarable, Emilio Leonardi, M. Marsan

引用次数: 1

Efficient Redundancy Techniques for Latency Reduction in Cloud Systems 云系统中减少延迟的有效冗余技术

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2015-08-14 DOI: 10.1145/3055281

Gauri Joshi, E. Soljanin, G. Wornell

{"title":"Efficient Redundancy Techniques for Latency Reduction in Cloud Systems","authors":"Gauri Joshi, E. Soljanin, G. Wornell","doi":"10.1145/3055281","DOIUrl":"https://doi.org/10.1145/3055281","url":null,"abstract":"In cloud computing systems, assigning a task to multiple servers and waiting for the earliest copy to finish is an effective method to combat the variability in response time of individual servers and reduce latency. But adding redundancy may result in higher cost of computing resources, as well as an increase in queueing delay due to higher traffic load. This work helps in understanding when and how redundancy gives a cost-efficient reduction in latency. For a general task service time distribution, we compare different redundancy strategies in terms of the number of redundant tasks and the time when they are issued and canceled. We get the insight that the log-concavity of the task service time creates a dichotomy of when adding redundancy helps. If the service time distribution is log-convex (i.e., log of the tail probability is convex), then adding maximum redundancy reduces both latency and cost. And if it is log-concave (i.e., log of the tail probability is concave), then less redundancy, and early cancellation of redundant tasks is more effective. Using these insights, we design a general redundancy strategy that achieves a good latency-cost trade-off for an arbitrary service time distribution. This work also generalizes and extends some results in the analysis of fork-join queues.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131173384","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: 117

Analysis of an Offloading Scheme for Data Centers in the Framework of Fog Computing 雾计算框架下数据中心卸载方案分析

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2015-07-21 DOI: 10.1145/2950047

C. Fricker, F. Guillemin, P. Robert, Guilherme Thompson

引用次数: 63

Efficient Straggler Replication in Large-Scale Parallel Computing 大规模并行计算中的高效离散子复制

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2015-03-11 DOI: 10.1145/3310336

Da Wang, Gauri Joshi, G. Wornell

{"title":"Efficient Straggler Replication in Large-Scale Parallel Computing","authors":"Da Wang, Gauri Joshi, G. Wornell","doi":"10.1145/3310336","DOIUrl":"https://doi.org/10.1145/3310336","url":null,"abstract":"In a cloud computing job with many parallel tasks, the tasks on the slowest machines (straggling tasks) become the bottleneck in the job completion. Computing frameworks such as MapReduce and Spark tackle this by replicating the straggling tasks and waiting for any one copy to finish. Despite being adopted in practice, there is little analysis of how replication affects the latency and the cost of additional computing resources. In this article, we provide a framework to analyze this latency-cost tradeoff and find the best replication strategy by answering design questions, such as (1) when to replicate straggling tasks, (2) how many replicas to launch, and (3) whether to kill the original copy or not. Our analysis reveals that for certain execution time distributions, a small amount of task replication can drastically reduce both latency and the cost of computing resources. We also propose an algorithm to estimate the latency and cost based on the empirical distribution of task execution time. Evaluations using samples in the Google Cluster Trace suggest further latency and cost reduction compared to the existing replication strategy used in MapReduce.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129128398","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: 36