Performance Evaluation and Analysis Consortium (PEAC) End Station

PI Leonid Oliker, Lawrence Berkeley National Laboratory
Project Description

Understanding how to efficiently use DOE leadership class systems is important due to the challenges of effectively managing extreme levels of concurrency as well as architectural heterogeneity. The team will have a PEAC End Station to complete this project. To facilitate further understanding of leadership class systems, Oliker’s team will develop new programming models and runtime systems. Consortium members will conduct research into the programming models, runtime systems, tools, system evaluations and application analysis that support computational science on leadership computing platforms. Ultimately, this will allow scientists to maximize the speed—and therefore the impact—of these large-scale platforms.