Answers are grounded in this paper and cite their sources.
We describe the design and implementation of an application-level parallel I/O (PIO) library for the reading and writing of distributed arrays to several common scientific data formats. PIO provides the flexibility to control the number of I/O tasks through data rearrangement to an I/O friendly decomposition. This flexibility enables reductions in per task memory usage and improvements in disk I/O performance versus a serial I/O approach. We illustrate the impact various features within PIO have on memory usage and disk I/O bandwidth on a Cray XT5 system.
No takes yet. Share an insight, caveat, or question.
Dennis et al. (2011) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: