Dynamic Scheduling and Load Balancing for Monte Carlo based Radiotherapy Simulations
Abstract
The Monte Carlo dose transport computations are intractable for small cluster computing environments. We have simulated prostate cancer plans using 25X10^6 200-MeV protons. In the previous work using the medical grid for these computations, we reported significant loss in grid speed-up and grid efficiency. We believe that dynamic scheduling and load balancing strategies could improve simulation efficiencies and throughput in this type of data parallel applications. Our initial numerical experiment using cluster computing are promising. Additional calculations are in progress. Implementation of cluster-level dynamics scheduling and load balancing could offer overall improvements to the grid-scale speed-up and efficiency.
Intellectual Merit
N/A
Broader Impact
By this experiment we can say that, by doing the load balancing and dynamic scheduling one can reduce the estimated simulation run time. Thus can help in efficiently utilizing the resources a firm have.
Use of FutureGrid
Future Grid will help me in doing the experiment for my simulations.
Scale Of Use
I want to run a simulations on entire systems and for each I'll need about 10 days to do that.
I will then compare the result and after comparing
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