Data Analysis and Simulations in Exascale Computing: Quō vādis?

We are less than three years apart from the first, double precision Exa-Flop/s supercomputers. Already today, our scientific software stacks are facing the challenge to run efficiently on a potpourri of architectures. But the real troubles might await us at the choke points of extreme data rates, where traditional workflows of data acquisition, filtering, processing and subsequent long-term storage might not be able to be sustained anymore. How would you like to express your scientific algorithms in a world where Flop/s are increasingly cheap, yet hard to achieve, but data movement and especially data at rest is increasingly in-proportionally expensive? Would you be OK to throw data away and measure twice? Can we in situ compute results with a different prepared question instead of waiting for an always-full and quickly-purged filesystem? How do we ensure reproducibility? How large a mix of programming languages and double-implementations of algorithms can we burden before we are running out of developers (due to lack of maintainability)? This talk will present our vision for the next years of data-driven scientific computing. Based on our experience with single-source, performance-portable C++ HPC libraries, we will present zero-overhead C++ abstractions that spare code-duplication. Together with light-weight code coupling, possible directions for analyzing resulting data rates are discussed on examples from laser-driven particle accelerator research. With such meta-programming approaches, an underestimated risk lies in cutbacks for both development workflows and user interactivity at runtime, which we want to openly change with interactive Cling-assisted execution in modern environments such as Jupyter, for which we recently enabled CUDA C++ capabilities.This research used resources of the Oak Ridge Leadership Computing Facility located in the Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy under Contract DE-AC05-00OR22725