Showing papers by "Roger Impey published in 2005"

Job completion prediction in grid using distributed case-based reasoning

Abstract: Grid allows several entities to share their computational resources. Selecting the best resource to run a job can become a complex and inadequate task for the user since grid is a distributed, dynamic, and heterogeneous network. The current frameworks for this problem still face some challenges. Users never know when the job will finish and what the service provider guarantees. Moreover, job scheduling for a future time is unavailable in most existing framework solutions since they lack performance prediction techniques. This paper presents an approach to job execution time prediction in grid using the case-based reasoning paradigm. The prediction module presented is part of a multi-agent system that selects the best resource to run a job in the grid environment. Case retrieval algorithms involving relevance and geometric matching are presented. We also elaborate adaptation algorithms that use prediction techniques for job workload forecasting.

Federating Grids : LCG meets Canadian HEPGrid

Abstract: A large number of Grids have been developed worldwide. Despite being mostly based on the same underlying middleware, the Globus Toolkit, they are generally not inter-operable for a variety of reasons. We present a method of federating those disparate grids which are based on the Globus Toolkit, together with a concrete example of interfacing the LHC Computing Grid (LCG) with HEPGrid. HEPGrid consists of shared resources, at several Canadian research institutes, which are exposed via Globus gatekeepers, and makes use of Condor-G for resource advertisement, matchmaking and job submission. An LCG Computing Element (CE) based at the TRIUMF Laboratory hosts a HEPGrid User Interface (UI) that is contained within a custom JobManager. This JobManager appears in the LCG information system as a normal CE publishing an aggregation of the HEPGrid resources. The interface interprets the incoming job in terms of HEPGrid UI usage, submits it onto HEPGrid, and implements the JobManager 'poll' and 'remove' methods, thus enabling monitoring and control across the grids. In this way non-LCG resources are integrated into LCG, without the need for LCG middleware on those resources. The same method can be used to create interfaces between other grids, with the details of the child-Grid being fully abstracted into the interface layer. The LCG-HEPGrid interface is operational, and has been used to federate 1300 CPU's at 4 sites into LCG for the ATLAS Data Challenge (DC2).