Using parallel computing and grid systems for genetic mapping of quantitative traits

Authors:
Mahen Jayawardena;Kajsa Ljungberg;Sverker Holmgren
Affiliations:
Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden and University of Colombo, School of Computing, Colombo, Sri Lanka;Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden;Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden
Venue:
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Year:
2006

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Abstract

We present a flexible parallel implementation of the exhaustive grid search algorithm for multidimensional QTL mapping problems. A generic, parallel algorithm is presented and a two-level scheme is introduced for partitioning the work corresponding to the independent computational tasks in the algorithm. At the outer level, a static blockcyclic partitioning is used, and at the inner level a dynamic pool-of-tasks model is used. The implementation of the parallelism at the outer level is performed using scripts, while MPI is used at the inner level. By comparing to results from the SweGrid system to those obtained using a shared memory server, we show that this type of application is highly suitable for execution in a grid framework.