parallel discrete event simulation algorithms are usually based on time stamp ordering of events. distributed virtual environment (DVE) applications such as DIS typically use unordered event delivery. A partial order ...
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parallel discrete event simulation algorithms are usually based on time stamp ordering of events. distributed virtual environment (DVE) applications such as DIS typically use unordered event delivery. A partial order called approximate time (AT) is proposed to order events in both domains, facilitating reuse of simulations across DVE and analysis applications. A variation on AT-order called approximate time causal (ATC) order is also described. Synchronisation algorithms to realize these orderings are presented as well as performance measurements on a workstation cluster. A long-term goal of this work is to use AT and ATC order to exploit temporal uncertainty in the model to achieve efficient conservative parallelsimulation despite little or no lookahead, a long-standing problem in the field.
Ordering of simultaneous events in DES is an important issue as it has an impact on modelling expressiveness, model correctness as well as causal dependencies. In sequential DES this is a problem which has attracted m...
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Ordering of simultaneous events in DES is an important issue as it has an impact on modelling expressiveness, model correctness as well as causal dependencies. In sequential DES this is a problem which has attracted much attention over the years and most systems provide the user with tools to deal with such issues. This has also attracted some attention within the PDES community and we present an overview of these efforts. We have, however, not yet found a scheme which provides us with the desired functionality. Thus, we present and evaluate some simple schemes to achieve a well defined ordering of events and means to identify both causally dependent and independent events with identical timestamps in the context of optimistic simulations. These schemes should be applicable also to conservative PDES.
Most successful examples of parallelsimulation models were developed for parallel execution, from the beginning. A number of simulation models are designed only for sequential simulation, even in languages like PARSE...
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Most successful examples of parallelsimulation models were developed for parallel execution, from the beginning. A number of simulation models are designed only for sequential simulation, even in languages like PARSEC, that support both sequential and parallelsimulation algorithms. Converting such simulation models to a form that yields good performance with a parallel implementation can be non-trivial. We describe a case study showing this conversion process for a simulation model of replicated file systems. The details of the major steps taken in converting the simulation into a parallelsimulation are presented: correctness changes; performance changes such as communication topology simplification and lookahead specification; and modeling changes to eliminate performance bottlenecks. The details and performance improvements of each step are presented.
The simulation of incompressible fluids is one of the important problem classes in computational fluid dynamics. We consider a simulation algorithm for the convection in binary fluid mixtures, a problem where a quite ...
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The simulation of incompressible fluids is one of the important problem classes in computational fluid dynamics. We consider a simulation algorithm for the convection in binary fluid mixtures, a problem where a quite simple model describes a very complex behavior. In a parallel implementation on an IBM SP2, we investigate several implementation strategies involving different data layouts and communication organizations.
We have developed a set of performance prediction tools which help to estimate the achievable speedups from parallelizing a sequential simulation. The tools focus on two important factors in the actual speedup of a pa...
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We have developed a set of performance prediction tools which help to estimate the achievable speedups from parallelizing a sequential simulation. The tools focus on two important factors in the actual speedup of a parallelsimulation program: (a) the simulation protocol used, and (b) the inherent parallelism in the simulation model. The first two tools are a performance/parallelism analyzer for a conservative, asynchronous simulation protocol, and a similar analyzer for a conservative, synchronous ('super-step') protocol. Each analyzer allows us to study how the speedup of a model changes with increasing number of processors, when a specific protocol is used. The third tool - a critical path analyzer - gives an ideal upper bound to the model's speedup. This paper gives an overview of the prediction tools, and reports the predictions from applying the tools to a discrete-event wafer fabrication simulation model. The predictions are close to speedups from actual parallel implementations. These tools help us to set realistic expectations of the speedup from a parallelsimulation program, and to focus our work on issues which are more likely to yield performance improvement.
This paper presents a checkpointing scheme for optimistic simulation which is a mixed approach between periodic and probabilistic checkpointing. The latter, basing on statistical data collected during the simulation, ...
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This paper presents a checkpointing scheme for optimistic simulation which is a mixed approach between periodic and probabilistic checkpointing. The latter, basing on statistical data collected during the simulation, aims at recording as checkpoints states of a logical process that have high probability to be restored due to rollback (this is done in order to make those states immediately available). The periodic part prevents performance degradation due to state reconstruction (coasting forward) cost whenever the collected statistics do not allow to identify states highly likely to be restored. Hence, this scheme can be seen as a highly general solution to tackle the checkpoint problem in optimistic simulation. A performance comparison with previous solutions is carried out through a simulation study of a store-and-forward communication network in a two-dimensional torus topology.
In optimistic parallelsimulations, state-saving techniques have been traditionally used to realize rollback. In this article, we propose reverse computation as an alternative approach, and compare its execution perfo...
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In optimistic parallelsimulations, state-saving techniques have been traditionally 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 transparently reap the performance benefits of reverse computation. 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 three-fold improvement in execution speed over traditional state-saving.
We present a parallel simulator (SWiMNet) for PCS networks using a combination of optimistic and conservative paradigms. The proposed methodology exploits event precomputation permitted by model independence within th...
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We present a parallel simulator (SWiMNet) for PCS networks using a combination of optimistic and conservative paradigms. The proposed methodology exploits event precomputation permitted by model independence within the PCS components. The low percentage of blocked calls is exploited in the channel allocation simulation of precomputed events by means of an optimistic approach. Experiments were conducted with various call arrival rates and mobile host densities on a cluster of Pentium workstations. Performance results indicate that the SWiMNet achieves a speedup of 6 employing 8 workstations, and a speedup of 12 with 16 workstations.
Traditionally, parallel discrete-event simulators based on the Time Warp synchronization protocol have been implemented using either the shared memory programming model or the distributed memory, message passing progr...
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Traditionally, parallel discrete-event simulators based on the Time Warp synchronization protocol have been implemented using either the shared memory programming model or the distributed memory, message passing programming model. This was because the preferred hardware platform was either a shared memory multiprocessor workstation or a network of uniprocessor workstations. However, with the advent of clumps (cluster of shared memory multiprocessors), a change in this dichotomous view becomes necessary. We explore the design and implementation issues involved in exploiting this new platform for Time Warp simulations. Specifically, we present two generic strategies for implementing Time Warp simulators on clumps. In addition, we present our experiences in implementing these strategies on an extant distributed memory, message passing Time Warp simulator (WARPED). Preliminary performance results comparing the modified clump-specific simulation kernel to the unmodified distributed memory, message passing simulation kernel are also presented.
There are at least three major obstacles thwarting widespread adoption of parallel discrete-event simulation: lack of need; lack of tools; and lack of predictability in behavior and performance. The plain truth is tha...
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There are at least three major obstacles thwarting widespread adoption of parallel discrete-event simulation: lack of need; lack of tools; and lack of predictability in behavior and performance. The plain truth is that most simulation studies can be adequately done on ordinary serial computers. parallelsimulation tools are products of research efforts, and simply do not stand up to the demands of modern software engineering. The results of 20 years of research in parallelsimulation reveal it to be a highly complex endeavour, with performance results very much dependent on implementation details and model characteristics. The Scalable simulation Framework (SSF) is an effort to address some these concerns. It addresses lack of need in two ways; it provides a modeling API that is attractive both for serial and parallelsimulation, with parallel execution requiring no change to the model, and it targets large-scale telecommunication system modeling, an application area that requires the computational capabilities of parallelism. We address the concern over unpredictable behavior. We show how we measured the internal overheads of the Dartmouth implementation of the SSF API (DaSSF), and how those measurements can be used to predict the performance of a given model, using given features of the simulator, without having to run, or even build, the model.
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