{"title":"Vector Time Management Based on Topology Information for HLA/RTI","authors":"Chunpeng Chen, Hongjin Jia","doi":"10.1109/PADS.2012.47","DOIUrl":"https://doi.org/10.1109/PADS.2012.47","url":null,"abstract":"Aimed to reduce the overheads using the Time Management (TM) in HLA based distributed simulations, the TM based on publish-subscribe topology information is investigated. The condition under which the message may be received before its causal predecessor is firstly analyzed. And then, the TM algorithms using vector clock are put forward, in which the condition is judged before the clock is comparing. The algorithms will reduce overheads in many distributed simulation systems where topology information is static and reasonably sparse.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116170332","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":"Sensing-Based Modeling and Service for Conditional Connection of EDEVS Component","authors":"Yang Lu, Yiping Yao, Gang Liu, Longchen Qi","doi":"10.1109/PADS.2012.41","DOIUrl":"https://doi.org/10.1109/PADS.2012.41","url":null,"abstract":"based parallel and discrete event simulation (PDES) modeling is becoming an important trend to model large-scale complex system. In component-based modeling, \"Conditional Connection\" often exits among components, this means the connection varies with the system states. For example, the radar does not have a connection with the target outside its detecting range until the target enters the range. In current research, components are mostly composed by port-to-port connections. Therefore, extra \"adaptor\" should be introduced to discover whether the connection exists under certain system states, making the modeling less flexible and inefficient. To solve this problem, a sensing-based mechanism of sharing and accessing state variable is proposed in this paper. By using Interest Management of Data Distributed Management (DDM), the mechanism supports dynamic linking among components. First, we introduce the concept of the sensing environment and give the formal description of \"sensing\" to lay the foundation of the sensing-based mechanism. Then we put forward the sensing service process to support Conditional Connection.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116545192","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 Simulation of Large-Scale Artificial Society on CPU/GPU Mixed Architecture","authors":"Gang Guo, Bin Chen, X. Qiu, Zhen Li","doi":"10.1109/PADS.2012.31","DOIUrl":"https://doi.org/10.1109/PADS.2012.31","url":null,"abstract":"Parallel simulations focus on conservative or optimistic algorithms to guarantee state consistency and causal order of messages between logical processes (LPs). It is usually hard for application domain users to develop complicated models for parallel simulations. For simplicity in large-scale artificial society, a modified DEVS component model is advocated in time-stepped parallel simulation with two-phase synchronization. A two-tier parallel simulation engine is designed on CPU/GPU mixed architecture with support of MPI and OpenCL. One-sided communication is selected for reflection of remote components and message passing between LPs. For cooperation between CPU and GPU, a size of 512 work items in each group is recommended. The parallel simulation engine is implemented in a micro kernel manner. An artificial society based on agent, container, grid and relation models are used to test the performance on an ordinary computer and a cluster with varied scales. The maximum speedup reaches 46 and 114 on the computer and the cluster respectively with about half a million agents.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121270487","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":"Research on GPU-Based Computation Method for Line-of-Sight Queries","authors":"Bin Liu, Yiping Yao, Wenjie Tang, Yang Lu","doi":"10.1109/PADS.2012.37","DOIUrl":"https://doi.org/10.1109/PADS.2012.37","url":null,"abstract":"The line of sight (LOS) queries often consume a significant fraction of system resources in military simulation. The high time complexity of LOS computation not only limit the amount of entities in the simulation, but also hamper the CPU from doing more urgent and important tasks. To overcome this problem, we utilize graphic process units (GPU) to accelerate the LOS computation at two levels, single-query level and batch-query level. First, we decouple the dependency of data to parallelize the whole process of LOS computation, so that the potential of GPU can be exploited at single-query level. Second, a combine-and-partition algorithm is proposed to aggregate multiple single LOS queries into a GPU-based computation, so that the count of parallel threads can be maximized and the impact of communication latency can be minimized. It uses a combine function to assemble scattered single query into a batch query, and uses a partition function to get computational data or dispatch results. An early version of our prototype demonstrates at least 3x speedup at single-query level, and we expect to achieve a speedup eyond 200x at batch-query level based on the LOS culling methods in references 1 and 2.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124255259","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":"Clarifying Interoperability: The SISO CSPI PDG Standard for Commercial Off-The-Shelf Simulation Package Interoperability Reference Models","authors":"Simon J. E. Taylor, S. Turner, S. Strassburger","doi":"10.1109/WSC.2007.4419652","DOIUrl":"https://doi.org/10.1109/WSC.2007.4419652","url":null,"abstract":"For many years discrete-event simulation has been used to analyze production and logistics problems in manufacturing and defense. Commercial-off-the-shelf simulation packages (CSPs), visual interactive modelling environments such as Arena, Anylogic, Flexsim, Simul8, Witness, etc., support the development, experimentation and visualization of simulation models. There have been various attempts to create distributed simulations with these CSPs and their tools, some with the high level architecture (HLA). These are complex and it is quite difficult to assess how a set of models/CSP are actually interoperating. As the first in a series of standards aimed at standardizing how the HLA is used to support CSP distributed simulations, the Simulation Interoperability Standards Organization's (SISO) CSP Interoperability Product Development Group (CSPI PDG) has developed and standardized a set of interoperability reference models (IRM) that are intended to clearly identify the interoperability capabilities of CSP distributed simulations.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131758325","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":"Modeling and Simulating the Brain as a System","authors":"D. DeGroot","doi":"10.1109/PADS.2005.15","DOIUrl":"https://doi.org/10.1109/PADS.2005.15","url":null,"abstract":"We discuss some of the key research roles that played by simulation and modeling, performance engineering, distributed computing, architectures, visualization and other key technologies of interest to the PADS community. In particular, the discussion presents a concept for the development of isomorphic, hierarchical architectures and principles of operation of the brain at multiple levels, using interactive visualization and distributed simulation techniques.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114268264","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":"Efficient optimistic parallel simulations using reverse computation","authors":"C. Carothers, K. Perumalla, R. Fujimoto","doi":"10.1145/347823.347828","DOIUrl":"https://doi.org/10.1145/347823.347828","url":null,"abstract":"In optimistic parallel simulations, state-saving techniques have traditionally been used to realize rollback. In this article, we propose reverse computation as an alternative approach, and compare its execution performance against that of state-saving. Using compiler techniques, we describe an approach to automatically generate reversible computations, and to optimize them to reap the performance benefits of reverse computation transparently. For certain fine-grain models, such as queuing network models, we show that reverse computation can yield significant improvement in execution speed coupled with significant reduction in memory utilization, as compared to traditional state-saving. On sample models using reverse computation, we observe as much as a six-fold improvement in execution speed over traditional state-saving.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115993769","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}
J. Cleary, F. Gomes, B. Unger, Xiao Zhonge, Raimar Thudt
{"title":"Cost of state saving & rollback","authors":"J. Cleary, F. Gomes, B. Unger, Xiao Zhonge, Raimar Thudt","doi":"10.1145/182478.182545","DOIUrl":"https://doi.org/10.1145/182478.182545","url":null,"abstract":"Approaches to state saving and rollback for a shared memory, optimistically synchronized, simulation executive are presented. An analysis of copy state saving and incremental state saving is made and these two schemes are compared. Two benchmark programs are then described, one a simple, all overhead, model and one a performance model of a regional Canadian public telephone network. The latter is a large SS7 common channel signalling model that represents a very challenging, practical, test application for parallel simulation. Experimental results are presented which show the necessity and sufficiency of incremental state saving for this application.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123532868","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":"Maya: a simulation platform for distributed shared memories","authors":"D. Agrawal, M. Choy, H. Leong, Ambuj K. Singh","doi":"10.1145/182478.182583","DOIUrl":"https://doi.org/10.1145/182478.182583","url":null,"abstract":"Maya is a simulation platform for evaluating the performance of parallel programs on parallel architectures. It allows the rapid prototyping of memory protocols with varying degrees of coherence and facilitates the study of the impact of these protocols on application programs. The design of Maya and its simulation mechanism are discussed. Performance results on architectural simulation with different memory coherence protocols are presented. Parallel discrete event simulation techniques are adopted for the execution-driven simulation of parallel architectures.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127085958","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 distributed memory LAPSE: parallel simulation of message-passing programs","authors":"P. Dickens, P. Heidelberger, D. Nicol","doi":"10.1145/182478.182488","DOIUrl":"https://doi.org/10.1145/182478.182488","url":null,"abstract":"This paper describes a tool, LAPSE (Large Application Parallel Simulation Environment), that allows one to use a small number of parallel processors to simulate the behavior of a message-passing code running on a large number of processors, for the purposes of scalability studies and performance tuning. LAPSE is implemented on the Intel Paragon, and has achieved small slowdowns (relative to native code) and high speed-ups on large problems.","PeriodicalId":194781,"journal":{"name":"Workshop on Parallel and Distributed Simulation","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127455870","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}