Performance Evaluation of Data Management Layer by Data Sharing Patterns for Grid RPC Applications
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Experiments with SmartGridSolve: Achieving higher performance by improving the GridRPC model
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Enabling workflows in GridSolve: request sequencing and service trading
The Journal of Supercomputing
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In the framework of GridRPC, a new function that allows direct data transfer between RPC servers is implemented for efficient execution of a Task Sequencing job in a grid environment. In Task Sequencing, RPC requires dependency between input and output parameters, which means output of a previous RPC becomes the input of the next RPC. In this study, the direct transfer of data is implemented using the grid filesystem without destroying the GridRPC programming model and without changing very many parts of the existing Ninf-G implementation. Our Task Sequencing API library analyzes RPC arguments to detect intermediate data after task submissions, and reports the information to GridRPC servers so that the intermediate data is created on the grid filesystem. Through our performance evaluation on LAN and on the Japan-US grid environment, it was verified that the function achieved performance improvement in distributed Task Sequencing.