Desheng Fu, Matthias Becker, Marcus O'Connor, H. Szczerbicka
{"title":"Estimating performance of large scale distributed simulation built on homogeneous hardware","authors":"Desheng Fu, Matthias Becker, Marcus O'Connor, H. Szczerbicka","doi":"10.1109/DISTRA.2017.8167678","DOIUrl":"https://doi.org/10.1109/DISTRA.2017.8167678","url":null,"abstract":"Large scale distributed simulation should be well planned before the execution, since applying unnecessary hardware only wastes our time and money. On the other side, we need enough hardware to achieve an acceptable performance. Thus, it is considerable to estimate the performance of a large scale distributed simulation before the execution. Such an estimation also improves the efficiency of the applied hardware in many cases due to the optimization on the simulation algorithm and on the partition of the model. In this paper, we show our approaches to estimate the performance, especially the duration of execution, of a large scale distributed simulation system built on a large set of homogeneous hardware, using a small set of hardware of the same type. Our basic idea is to simulate a distributed simulation in a sequential way for a short time considering all the costs and benefits of the distribution. The results of our case study show that our approaches are able to provide meaningful estimations.","PeriodicalId":109971,"journal":{"name":"2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133287811","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":"Parallel sort-based matching for data distribution management on shared-memory multiprocessors","authors":"M. Marzolla, Gabriele D’angelo","doi":"10.1109/DISTRA.2017.8167660","DOIUrl":"https://doi.org/10.1109/DISTRA.2017.8167660","url":null,"abstract":"In this paper we consider the problem of identifying intersections between two sets of d-dimensional axis-parallel rectangles. This is a common operation that arises in many agent-based simulation studies, and is of central importance in the context of High Level Architecture (HLA), where it is at the core of the Data Distribution Management (DDM) service. Several realizations of the DDM service have been proposed; however, many of them are either inefficient or inherently sequential. We propose a parallel version of the Sort-Based Matching algorithm for shared-memory multiprocessors. SortBased Matching is one of the most efficient serial algorithms for the DDM problem, but is quite difficult to parallelize because of data dependencies. We describe the algorithm and compute its asymptotic running time; we complete the analysis by assessing its performance and scalability through extensive experiments on two commodity multicore systems based on a dual socket Intel Xeon processor, and a single socket Intel Core i7 processor.","PeriodicalId":109971,"journal":{"name":"2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115204540","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}