Sessi MCP: Overcoming I/O limitations on exascale architectures

With larger systems and application scales, I/O is increasingly becoming a bottleneck. This is particularly true when global system states need to save regularly for checkpointing and analysis purposes, like in computational fluid dynamics applications. In this project we analyse the I/O performance of Nek5000 (a spectral element CFD code) and implement parallel I/O strategies to improve I/O performance and scaling. The method considered is the Discrete Legendre Transform (DLT) based on a priori error estimation allowing total control over the error considered permissible. Note that this is an improvement with respect to previous compression algorithms. We assess the impact of the compression in different situations such as turbulence statistics computation, flow visualization, vortex identification, spectra, as well as restarts from compressed data fields. It has been shown that compression ratios up to about 97% were acceptable.

Milestones
M1: Finalize analysis of truncation error on data analysis, and write paper (October 2017)
M2: Impact of compression on low-order models based on POD (December 2017)
M3: Implementation of compression in Nek5000, with bitwise encoding, optimized for Cray architectures (February 2018)
M4: Interface to visualisation software for on-the-fly decoding (March 2018)
M5: Optimisation of IO and memory access on KNL (May 2018)