Improving the BAC and HemeLB: ComPat Collaboration Sample Clauses

Improving the BAC and HemeLB: ComPat Collaboration. This Section outlines the performance studies performed by CompBioMed partners under the ComPat programme. The full ComPat report can be found in the Appendix. The CompBioMed Core Partner UCL considered both HemeLB and the BAC with a view to scaling associated simulations on exascale platforms. Various performance metrics were considered, as may be most appropriate for the given application e.g. wall clock time, file sizes, scalability (strong and weak), and energy consumption (where available). In one weak-scaling application we also consider scalability of the middleware itself. To further explore and assess the potential impact of extreme parallelism, we also carried out performance studies on two applications using even larger supercomputers. To simplify the assessment, we note that the multiscale applications can be abstracted as sections of replica computing steps, and large monolithic applications. For this reason, our predictions as pertain to exascale resource usage largely come from detailed studies of application performance for a Replica-based exemplar (the Binding Affinity Calculator, or BAC) and for an exemplar containing a large monolithic application (HemeLB). Furthermore, a detailed mathematical model was developed to predict the time and length scales attainable by a lattice-Boltzmann solver (such as Palabos or HemeLB) in a fixed time on computers with e.g. 1 billion cores (exascale). With respect to the exascale, a major conclusion of this work was that, even for those applications exhibiting excellent strong scaling characteristics, the trade-off between resolving time or physical length scales in the system will frequently render such simulations inefficient on enormous core counts when compared to the weak scaling (replica) case. We therefore expect that the actual impact of exascale resources on future science applications will be to encourage the use of uncertainty quantification (techniques that often require multiple runs) in a field where researchers too often only run large simulations once. The full report can be found in Appendix B.
Sample 1
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Related to Improving the BAC and HemeLB: ComPat Collaboration

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