Space is a very important aspect in the simulation of biochemical models;recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and large models of biochemic...
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We re-examine the problem of load balancing in conservatively synchronized parallel, discrete-event simulations executed on high-performance computing clusters, focusing on simulations where computational and messagin...
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ISBN:
(纸本)9781424472918
We re-examine the problem of load balancing in conservatively synchronized parallel, discrete-event simulations executed on high-performance computing clusters, focusing on simulations where computational and messaging load tend to be spatially clustered. Such domains are frequently characterized by the presence of geographic "hot-spots" - regions that generate significantly more simulation events than others. Examples of such domains include simulation of urban regions, transportation networks and networks where interaction between entities is often constrained by physical proximity. Noting that in conservatively synchronized parallelsimulations, the speed of execution of the simulation is determined by the slowest ( i.e most heavily loaded) simulation process, we study different partitioning strategies in achieving equitable processor-load distribution in domains with spatially clustered load. In particular, we study the effectiveness of partitioning via spatial scattering to achieve optimal load balance. In this partitioning technique, nearby entities are explicitly assigned to different processors, thereby scattering the load across the cluster. This is motivated by two observations, namely, (i) since load is spatially clustered, spatial scattering should, intuitively, spread the load across the compute cluster, and (ii) in parallelsimulations, equitable distribution of CPU load is a greater determinant of execution speed than message passing overhead. Through large-scale simulation experiments - both of abstracted and real simulation models - we observe that scatter partitioning, even with its greatly increased messaging overhead, significantly outperforms more conventional spatial partitioning techniques that seek to reduce messaging overhead. Further, even if hot-spots change over the course of the simulation, if the underlying feature of spatial clustering is retained, load continues to be balanced with spatial scattering leading us to the observation that
The parallel Random Access Machine is a very strong model of parallel computing that has resisted cost-efficient implementation attempts for decades. Recently, the development of VLSI technology has provided means for...
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ISBN:
(纸本)9781424416943
The parallel Random Access Machine is a very strong model of parallel computing that has resisted cost-efficient implementation attempts for decades. Recently, the development of VLSI technology has provided means for indirect on-chip implementation, but there are different variants of the PRAM model that provide different performance, area and power figures and it is not known how their implementations compare to each others. In this paper we measure the performance and estimate the cost of practical implementations of four PRAM models including EREW, Limited Arbitrary CRCW, Full Arbitrary CRCW, Full Arbitrary Multioperation CRCW on our Eclipse chip multiprocessor framework. Interestingly, the most powerful model shows the lowest simulation cost and highest performance/area and performance/power figures.
A large scale HLA-based simulation (federation) is composed of a large number of simulation components (federates), which may be developed by different participants and executed at different locations. These federates...
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Ethernet is the most widely implemented low-level networking technology used today, with Gigabit Ethernet seen as the emerging standard implementation. The backbones of many large scale networks (e.g., data centers, m...
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Usually researchers require many experiments to verify how biological systems respond to stimuli. However, the high cost of reagents and facilities as well as the time required to carry out experiments are sometimes t...
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The proceedings contain 6 papers. The topics discussed include: GPU-accelerated differential evolutionary Markov chain Monte Carlo method for multi-objective optimization over continuous space;a study of parallel and ...
ISBN:
(纸本)9781450300865
The proceedings contain 6 papers. The topics discussed include: GPU-accelerated differential evolutionary Markov chain Monte Carlo method for multi-objective optimization over continuous space;a study of parallel and distributed particle swarm optimization methods;ant system for service deployment in private and public clouds;an evolutionary game theoretic approach to adaptive and stable application deployment in clouds;GUMP: adapting client/server messaging protocols into peer-to-peer serverless environments;and simulation experiences with an ecological approach for pervasive service systems.
The current development towards multiple processor cores in personal computers is making distribution and parallelization of simulation software increasingly important. The possible speedups from parallelism are howev...
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The current development towards multiple processor cores in personal computers is making distribution and parallelization of simulation software increasingly important. The possible speedups from parallelism are however often limited with the current centralized solver algorithms, which are commonly used in today's simulation environments. An alternative method investigated in this work utilizes distributed solver algorithms using the transmission line modeling (TLM) method. Creation of models using TLM elements to separate model components makes them very suitable for computation in parallel because larger models can be partitioned into smaller independent submodels. The computation time can also be decreased by using small numerical solver step sizes only on those few submodels that need this for numerical stability. This is especially relevant for large and demanding models. In this paper we present work in how to combine TLM and solver inlining techniques in the Modelica equation-based language, giving the potential for efficient distributedsimulation of model components over several processors.
Real-time simulation of dynamic vehicle system models is essential to facilitate advances in operator and hardware in the loop simulation and virtual prototyping. Real-time virtual reality-based simulation enables use...
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ISBN:
(纸本)9780791849088
Real-time simulation of dynamic vehicle system models is essential to facilitate advances in operator and hardware in the loop simulation and virtual prototyping. Real-time virtual reality-based simulation enables users to visualize and perceive the effect of their actions during the simulation. As model complexity is increased to improve the model fidelity, the computational requirements will also increase, thus increasing the challenge to meet real-time constraints. A distributed simulator architecture was developed for off-road vehicle dynamic models and 3D graphics visualization to distribute the overall computational load across multiple computational platforms. This architecture consisted of three major components: a dynamic model simulator, a virtual reality simulator, and an interface to controller and input hardware devices. The dynamic model simulator component was developed using Matlab/Simulink Real Time workshop on a PC and also using Field Programmable Gate Arrays (FPGA), which offered a highly parallel hardware platform. The simulator architecture reduced the computational load to an individual platform and increased the real-time simulation capability with complex off-road vehicle system models and controllers. The architecture was used to develop, simulate and visualize a tractor and towed implement steering dynamics model. The model also included a steering valve subsystem which contained very high frequency hydraulic dynamics and required 10 mu s integration time step for numerical stability. The real-time simulation goal was not achievable for the model with this level of complexity when the PC-based simulator was used. However, the FPGA-based simulator achieved a real-time goal taking only 2 mu s to complete one integration time step.
In wireless sensor networks, collection of raw sensor data at a base station provides the flexibility to perform offline detailed analysis on the data which may not be possible with innetwork data aggregation. However...
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