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Supercomputers worldwide provide the necessary infrastructure forgroundbreaking research. However, most supercomputers are not designed equallydue to different desired figure of merit, which is derived from thecomputational bounds of the targeted scientific applications' portfolio. Inturn, the design of such computers becomes an optimization process that strivesto achieve the best performances possible in a multi-parameters search space.Therefore, verifying and evaluating whether a supercomputer can achieve itsdesired goal becomes a tedious and complex task. For this purpose, many full,mini, proxy, and benchmark applications have been introduced in the attempt torepresent scientific applications. Nevertheless, as these benchmarks are hardto expand, and most importantly, are over-simplified compared to scientificapplications that tend to couple multiple scientific domains, they fail torepresent the true scaling capabilities. We suggest a new physical scalablebenchmark framework, namely ScalSALE, based on the well-known SALE scheme.ScalSALE's main goal is to provide a simple, flexible, scalable infrastructurethat can be easily expanded to include multi-physical schemes while maintainingscalable and efficient execution times. By expanding ScalSALE, the gap betweenthe over-simplified benchmarks and scientific applications can be bridged. Toachieve this goal, ScalSALE is implemented in Modern Fortran with simple OOPdesign patterns and supported by transparent MPI-3 blocking and non-blockingcommunication that allows such a scalable framework. ScalSALE is compared toLULESH via simulating the Sedov-Taylor blast wave problem using strong and weakscaling tests. ScalSALE is executed and evaluated with both rezoning options -Lagrangian and Eulerian.

ScalSALE: Scalable SALE Benchmark Framework for Supercomputers