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The use of GPU clusters for scientific applications in areas such as physics, chemistry and bioinformatics is becoming more widespread. These clusters frequently have different types of processing devices, such as CPUs and GPUs, which can themselves be heterogeneous. To use these devices in an efficient manner, it is crucial to find the right amount of work for each processor that balances the computational...
Electric power consumed by servers has to be reduced in order to realize green societies. We consider computation ({\it{CP}}) and storage ({\it{ST}}) types of application processes performed on servers in this paper, where CPU and storage drives are mainly used, respectively. In the storage and computation based power consumption (SCBPC) model proposed by the authors, the power consumption rate of...
Agent-based crowd simulation, which aims to simulate large crowds of autonomous agents with realistic behavior, is a challenging but important problem. One key issue is scalability. Parallelism and distribution is an obvious approach to achieve scalability for agent-based crowd simulation. Parallel and distributed agent-based crowd simulation, however, introduces its own challenges, in particular,...
Clustered heterogeneous computing environment is used to execute parallel applications that require significant amount of computing resources either in the form of computational processing resources or data storage. A cluster, comprising of heterogeneous nodes, requires careful load balancing strategies in order to result in a good processing response time for parallel applications. The workload for...
Network model partitioning is a key component of distributed network simulations. Simulations slow down considerably due to inequitable load balancing and heavy inter-host communication leading to unbounded synchronization overhead. Also, regularly refreshing the node partition is necessary due to to the dynamic nature of simulation load and event generation. In this paper, we propose a distributed...
Decrease in hardware costs and advances in computer networking technologies have led to increased interest in the use of grid computing systems. One of the biggest issues in such systems is the development of effective techniques/algorithms for the distribution of the jobs/load of a grid application on multiple resources to achieve goals such as minimizing execution time, minimizing communication...
Load balancing techniques have been widely used in many existing distributed system and simulation frameworks. With the rapid development of virtual simulation technologies, many researchers have been investigating on how to apply virtual simulations to the distributed environment, especially when the virtual simulations need to be expanded to large-scale. In this paper, we propose an adaptive load-balancing...
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