Online Data Analysis and Reduction for Exascale Computing

Ian Foster, Argonne National Laboratory
Wed. 2:30 – 3:15pm

IanFoster_300A growing disparity between simulation speeds and I/O rates makes it increasingly infeasible for high-performance applications to save all results for offline analysis. By 2024, computers are expected to compute at exaflops but write to disk only at one terabyte/sec: a compute-to-output ratio 200 times worse than on the first petascale systems. In this new world, applications must increasingly perform online data analysis and reduction tasks that introduce algorithmic, implementation, and programming model challenges that are unfamiliar to many scientists and that have major implications for the design of various elements of exascale systems.

Ian Foster, Argonne National Laboratory