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Innovation

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CERT will develop exascale computer science algorithms and parallel performance models, exascale adaptive transport algorithms for both improved accuracy and numerical error estimation, multiscale physics models relating to transport in embedded voids and small cracks, and exascale multilevel preconditioning techniques. Our computer science research will include the development of methods for fault tolerance and the development of performance models that include the impact of iterative methods on parallel efficiency. The latter will enable us to choose an optimal solution technique based upon characteristics of the problem.

Below is a graph comparing the weak scaling performance of our latest transport solution algorithm with the predictions of the associated performance model.  It can be seen that our algorithm scales with roughly 60% efficiency from 1 to 384,000 cores of the Sequoia machine at LLNL, and that the performance model agrees very well with the actual performance. 

Parallel Efficiency Vs Core Count