AsHES Keynote

Summary form only given. Trends in execution concurrency on accelerated platforms make a compelling case for developing methods that can automatically and efficiently model and mitigate numerical irreproducibility beyond petascale and into exascale. High-performance accelerated computers at the extreme scale exhibit an enormous level of concurrency-a factor of 10,000 greater than on traditional platforms-that is moving computer simulations from bulk-synchronous executions to nondeterministic multithreading calculations and asynchronous I/O. As concurrency levels in simulations increase, the impact of rounding errors on numerical reproducibility is also exacerbated, ultimately affecting the ability of scientific simulations to reproduce program executions and numerical results. Under these circumstances, irreproducible results may not be trusted by a scientific community expecting reproducible behaviors; and any attempt to pursue reproducibility may come at a cost in performance that is too high.