A Novel Shard-Based Approach for Asynchronous Many-Task Models for In Situ Analysis
Workshop: ISAV 2017: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization
Authors: Philippe P. Pébaÿ (Sandia National Laboratories)
Abstract: We present the current status of our work towards a scalable, asynchronous many-task, in situ statistical analysis engine using the Legion runtime system, expanding upon earlier work, that was limited to a prototype implementation with a proxy mini-application as a surrogate for a full-scale scientific simulation code.
In contrast, we have more recently integrated our in situ analysis engines with S3D, a full-size scientific application, and conducted numerical tests on the largest computational platform currently available for DOE science applications.
The goal of this presentation is thus to describe the SPMD-Legion methodology that we have devised in this context, and to compare the data aggregation technique deployed herein to the approach taken within our previous work.