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The chemical task in internal combustion engine simulations concerns with the solution of a non-linear stiff system of Ordinary Differential Equations (ODEs) per each cell of a discretization grid representing engine geometry. The computational cost of the above task, when a detailed kinetic scheme is used, is dominating in engine simulations. Due to local physical-chemical conditions, each system...
The key of distributed computing is to fully utilize computing resources. However, the efficiency of distributed computing can always be affected by volatility of available nodes and uncertainty of network environment. In order to enhance resource allocation efficiency in distributed computing, this paper presents an inframarginal analysis based resource allocation method, which distributes computing...
The key of volunteer computing is to fully utilize computing resources. However, the efficiency of volunteer computing can always be affected by volatility of available nodes and uncertainty of network environment. In order to enhance resource allocation efficiency in volunteer computing, this paper presents an inframarginal analysis based resource allocation method, which distributes computing task...
Based on analyzing the problem of task scheduling and load balancing for parallel applications in P2P computing environment that can be broken down into independent subtasks, a tree-based task scheduling model for P2P computing is proposed. The hierarchical approach is introduced to the model so as to schedule a large number of parallel tasks and the mathematical analysis for this model shows a good...
In this paper, we present a dynamic load-balancing algorithm for optimistic gate level simulation making use of a machine learning approach. We first introduce two dynamic load-balancing algorithms oriented towards balancing the computational and communication load respectively in a Time Warp simulator. In addition, we utilize a multi-state Q-learning approach to create an algorithm which is a combination...
In hybrid heterogeneous and dynamically changing distributed grid environment, how to assign tasks to appropriate resources is one of the most challenging techniques. In this paper, we present a novel grid task assignment model and corresponding algorithm based on agents, small-world network model theory, and power-law. With the help of agents to assign tasks, the proposed model and algorithm can...
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...
This article is absorbed in the grid and a system framework for the simulation grid is introduced. The model of the modularization function is designed. The solution of pivotal technology and realization which correlated to function modules is discussed. Resource management and task schedule in simulation grid system is effectively realized which is shown to enhance the effect of simulation running.
Load balancing is crucial to computational grids. Based on the typeof information on which corresponding decisions are made, load balancing approaches can be generally categorized into two classes: average-based and instantaneous approaches. Both these two classeshave merits and demerits. It's therefore advantageous to combineboth of them to work in tandem to form a hybrid approach that makesthe best...
One of the challenges in grid computing is to find an efficient way to manage and allocate system resources. Through researching and analyzing present scheduling methods, a kind of two-level centralized scheduling model is proposed, and the algorithm is represented. The rate of load balancing is accelerated by the algorithm established two-level centralized scheduling pattern. Through the load balance...
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...
Grid resource management and scheduling are confronted with a great challenge. This paper presented a dynamic resource price-adjusting (RPA) strategy in computational Grid. Three new concepts and two new evaluation standards are defined. On the basis of these theories, a Grid resource scheduling algorithm based on marker-driven using dynamic RPA strategy is proposed. With the help of GridSim toolkit,...
In this paper, a novel dynamic task scheduling algorithm is proposed for parallel applications modeled in Kahn process networks (KPN) running in a distributed multi-processor cluster. Static job scheduling algorithms do not work for the purpose for that the complexity of a KPN model remains unpredictable at compile time. Dynamic load balancing strategies ignore the explicit data dependences among...
Dynamic load balancing is a key factor in achieving high performance for large scale distributed simulations on grid infrastructures. In a grid environment, the available resources and the simulationpsilas computation and communication behavior may experience run-time critical imbalances. Consequently, an initial static partitioning should be combined with a dynamic load balancing scheme to ensure...
Many parallel applications running on a distributed memory cluster generate data dynamically to process during their execution. In this case it is possible that some cluster nodes become overloaded. To improve performance we can integrate a dynamic data distribution algorithm.The integration of a dynamic load distribution policy into an application must consider the correct programming of several...
The ever changing demands on computational resources has information systems managers looking for solutions that are more flexible. Using a ldquobigger boxrdquo that has more and faster processors and permanent storage or more random access memory (RAM) is not a viable solution as the system usage patterns vary. In order for a system to handle the peak load adequately, it will go underutilized much...
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