Tolerant synchronization for distributed simulations of interconnected computer networks

Martini, Peter; Rümekasten, Markus; Tölle, Jens

doi:10.1145/268823.268912

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…For example, implicit look-ahead in First Come First Served stochastic queuing networks was introduced by Nicol [7], which was extended by Lazowska to round robin [8] and some other queuing networks. For example, Maritini et al [12] introduced the tolerant synchronization and accepted event errors during the synchronization. During the analysis of stochastic queuing networks, the service times of processes are pre-sampled into a 'future list'.…”

Section: Related Workmentioning

confidence: 99%

Improving the performance of distributed discrete event simulation by exchange of conditional look‐ahead

Becker

Szczerbicka

2016

Concurrency and Computation

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Distributed discrete event simulation is an important approach for enabling the modeling and analysis of the behavior of large systems. This approach presents a major problem, namely, the possible low performance due to the excessive overhead in synchronizing the distributed logical processes. To counter this, our approach to distributed discrete event simulation involves conservative synchronization and its acceleration using dynamic estimation of process-to-process look-ahead with a feedback mechanism. This mechanism allows for the estimation of a larger look-ahead, which may be invalidated and recalculated during the course of the simulation, if one of the processes obtains more detailed knowledge.In this work, we extend the dynamically estimated look-ahead, on the basis of the local state of the logical processes, by exchanging conditional look-aheads, in conjunction with the broadcast of invalidation announcements. A notable reduction in runtime in various cases is thus achieved, especially when the estimated look-ahead is stochastically too conservative. Figure 4. Pseudocode of the algorithm.shorter than LA 2 1 and LA 3 1 . Furthermore, LP 2 sends CLA to LP 1 with the condition that LP 1 will not modify the state of LP 2 and LP 3 with external events. If LP 1 sends an external event to LP 2 , an IA will be sent to itself as discussed previously.This alternative solution can be seen as a trade-off between the external LAs and internal LAs. On one side, any LA sent from LP i to any LP in the same group is limited by min¹LA i k jLP k belongs to the other groupº:Conditional look-ahead (CLA) can be applied to extend these LAs anyway, but the limit must be kept. On the other side, the LA / CLA sent from LP i to any LP in the other group could be extended by a condition. Whether this condition really helps to extend the LA depends strongly on the model and the partitioning. This is generally unpredictable due to the unknown state of LPs in the same group. But in some special situations, the interruption of some immediate communication loops is useful.

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Section: Related Workmentioning

confidence: 99%

Improving the performance of distributed discrete event simulation by exchange of conditional look‐ahead

Becker

Szczerbicka

2016

Concurrency and Computation

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“…Tolerant synchronization [Martini et al 1997] uses the lock-step method to process the simulation conservatively, but it allows the processor to execute the event optimistically if the timestamp is less than the tolerance point in the synchronization. The recovery procedure is not called, even if a causality error occurs, until the timestamp reaches the tolerance point.…”

Section: Trade-off Between Accuracy and Performancementioning

confidence: 99%

An analysis of queuing network simulation using GPU-based hardware acceleration

Park

Fishwick

2011

ACM Trans. Model. Comput. Simul.

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Queuing networks are used widely in computer simulation studies. Examples of queuing networks can be found in areas such as the supply chains, manufacturing work flow, and internet routing. If the networks are fairly small in size and complexity, it is possible to create discrete event simulations of the networks without incurring significant delays in analyzing the system. However, as the networks grow in size, such analysis can be time consuming, and thus require more expensive parallel processing computers or clusters. We have constructed a set of tools that allow the analyst to simulate queuing networks in parallel, using the fairly inexpensive and commonly available graphics processing units (GPUs) found in most recent computing platforms. We present an analysis of a GPU-based algorithm, describing benefits and issues with the GPU approach. The algorithm clusters events, achieving speedup at the expense of an approximation error which grows as the cluster size increases. We were able to achieve 10-x speedup using our approach with a small error in a specific implementation of a synthetic closed queuing network simulation. This error can be mitigated, based on error analysis trends, obtaining reasonably accurate output statistics. The experimental results of the mobile ad hoc network simulation show that errors occur only in the time-dependent output statistics.

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“…The main purpose of these LA estimation is to provide a longer LA to reduce the overhead of the algorithm. For example, Maritini et al [11] introduced the tolerant synchronization by accepting event errors during the synchronization. The interval where the event errors might occur is predicted and timewarp algorithm is applied to the time interval to resolve the occurred errors.…”

Section: Introductionmentioning

confidence: 99%

Accelerating Distributed Discrete Event Simulation through Exchange of Conditional Look-Ahead

Fu¹,

Becker²,

Szczerbicka³

2014

2014 IEEE/ACM 18th International Symposium on Distributed Simulation and Real Time Applications

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Distributed discrete event simulation is a very important method today to analyze the behavior of large models. We investigate the practical implementation of distributed discrete event simulation with conservative synchronization and its acceleration through dynamic estimation of process-to-process look-ahead. Since the dynamic look-ahead changes with time, we have to face the situation, that the look-ahead between some logical processes is decreased temporarily. The shortened lookahead has a very negative influence to the performance of the simulation and it is hard to avoid. However, this effect can be reduced by introducing some extra mechanisms in the simulation.In this paper, we present a mechanism to optimize the simulation for the situation that the look-ahead between some processes is very short. This mechanism is based on exchange of conditional look-ahead and broadcast of invalidation announcement. Our evaluation shows reduction of the execution time of a majority of distributed simulations, especially when the estimated look-ahead is stochastically too conservative.

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Tolerant synchronization for distributed simulations of interconnected computer networks

Cited by 9 publications

References 4 publications

Improving the performance of distributed discrete event simulation by exchange of conditional look‐ahead

Improving the performance of distributed discrete event simulation by exchange of conditional look‐ahead

An analysis of queuing network simulation using GPU-based hardware acceleration

Accelerating Distributed Discrete Event Simulation through Exchange of Conditional Look-Ahead

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