Application partitionability in computational grids

Summary form only given. Computation grids provide large volume of computing resources and have become an attractive alternative for scientific computing. It is desired that the applications are developed to utilize the globally distributed computing resources. Partitioning is one important way to achieve this goal. However, whether partitioning an application for computational grids is profitable or not is a basic problem and it is not fully addressed by the existing work. We call it partitionability problem. In our work, we try to quantify this problem and define the concept of computation density and partitionability based on the criteria of response time. We theoretically analyze the relationship between partitionability and application attributes such as I/O and internal communication data size. We show that with given workloads, those applications with higher computation density result in higher partitionability. We also propose a global resource registration mechanism so that the up-to-date resource information is available in partitioning. Our experiments with the simulated map image matching application shows that the proposed concept and framework improve the response time of the application by almost 40%.