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.
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 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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ISBN:
(纸本)9780769501550
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 introduces a novel algorithm, the Active Virtual Network Management Protocol, for predictive network management. It explains how the Active Virtual Network Management Protocol facilitates the management of ...
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ISBN:
(纸本)9780769501550
This paper introduces a novel algorithm, the Active Virtual Network Management Protocol, for predictive network management. It explains how the Active Virtual Network Management Protocol facilitates the management of an active network by allowing future predicted state information within an active network to be available to network management algorithms. This is accomplished by coupling ideas from optimistic discrete event simulation with active networking. The optimistic discrete event simulation method used is a form of self-adjusting Time Warp. It is self-adjusting because the system adjusts for predictions which are inaccurate beyond a given tolerance. The concept of a streptichron and autoanaplasis are introduced as mechanisms which take advantage of the enhanced flexibility and intelligence of active packets. Finally, it is demonstrated that the Active Virtual Network Management Protocol is a feasible concept.
This paper introduces the Critical Channel Traversing (CCT) algorithm, a new scheduling algorithm for both sequential and parallel discrete event simulation. CCT is a general conservative algorithm that is aimed at th...
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This paper introduces the Critical Channel Traversing (CCT) algorithm, a new scheduling algorithm for both sequential and parallel discrete event simulation. CCT is a general conservative algorithm that is aimed at the simulation of low-granularity network models on shared-memory multi-processor computers. An implementation of the CCT algorithm within a kernel called TasKit has demonstrated excellent performance for large ATM network simulations when compared to previous sequential, optimistic and conservative kernels. TasKit has achieved two to three times speedup on a single processor with respect to a splay tree central-event-list based sequential kernel. On a 16 processor (R8000) Silicon Graphics PowerChallenge, TasKit has achieved an event-rate of 1.2 million events per second and a speedup of 26 relative to the sequential kernel for a large ATM network model. Performance is achieved through a multi-level scheduling scheme that supports the scheduling of large grains of computation even with low-granularity events. Performance is also enhanced by supporting good cache behavior and automatic load balancing. The paper describes the algorithm and its motivation, proves its correctness and briefly presents performance results for TasKit.
A code for the simulation of X-ray diffraction pattern of a powder has been implemented on a massively parallel SIMD platform developed in the frame of the PQE2000 Project. The code allows the evaluation of the diffra...
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A code for the simulation of X-ray diffraction pattern of a powder has been implemented on a massively parallel SIMD platform developed in the frame of the PQE2000 Project. The code allows the evaluation of the diffraction pattern of atomic-scale models of both perfectly ordered and disordered structures. The code has been used to investigate the structures resulting from the non-equilibrium alloying process of an immiscible metallic couple (Ag-Cu).
We show that the latest version of massively parallel processing associative string processing architecture (System-V) is applicable for fast Monte Carlo simulation if an effective on-processor random number generator...
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We show that the latest version of massively parallel processing associative string processing architecture (System-V) is applicable for fast Monte Carlo simulation if an effective on-processor random number generator is implemented. Our lagged Fibonacci generator can produce 10/sup 8/ random numbers on a processor string of 12 K PE-s. The time dependent Monte Carlo algorithm of the one-dimensional non-equilibrium kinetic Ising model performs 80 faster than the corresponding serial algorithm on a 300 MHz UltraSparc.
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