Computing over Networks: An Illustrated Example

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Abstract
Monitor both the application and the environment is critical. For this reason we developed monitoring tools With the advances in high-speed networking, partitioning based on BEE (4), a monitoring kernel for distributed applications over a group of computer systems is environments that allows users to trace important events becoming an attractive way of exploiting parallelism. in their application efficiently. Programming general multicomputers is however very challenging: nodes are typically heterogeneous and shared In Section 2 we first give an overview of the with other users, making the availability of computing application that is used to illustrate the problems of cycles on the nodes and communication bandwidth on the network computing. In Sections 3 and 4 we describe a network unpredictable. This environment often requires static and dynamic partitioning of the problem on Nectar. users to use a programming model based on dynamic load We finally illustrate how the two implementations behave balancing. In this paper, we use an flow field generation under different conditions using BEE. application to look at the problems that come up in a network environment. We use BEE, a monitoring system that allows programmers to interactively monitor their 2. Simulating the Air Pollution in Los Angeles application, to show the behavior of the program under Flow field problems, such as weather forecasting and different conditions. tracking of spills, are computationally intensive and can benefit from parallel processing. We have ported a

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