Dynamic Partitioning of GATE Monte-Carlo Simulations on EGEE

The EGEE Grid offers the necessary infrastructure and resources for reducing the running time of particle tracking Monte-Carlo applications like GATE. However, efforts are required to achieve reliable and efficient execution and to provide execution frameworks to end-users. This paper presents results obtained with porting the GATE software on the EGEE Grid, our ultimate goal being to provide reliable, user-friendly and fast execution of GATE to radiation therapy researchers. To address these requirements, we propose a new parallelization scheme based on a dynamic partitioning and its implementation in two different frameworks using pilot jobs and workflows. Results show that pilot jobs bring strong improvement w.r.t. regular gLite submission, that the proposed dynamic partitioning algorithm further reduces execution time by a factor of two and that the genericity and user-friendliness offered by the workflow implementation do not introduce significant overhead.

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