Modeling Resource-Coupled Computations

Event Sponsor: 
Petascale Active Data Store (PADS) Fall Seminar Series
Start Date: 
Oct 29 2009 - 1:30pm to 2:30pm
Building/Room: 
Searle Lab, room 240
Location: 
University of Chicago
Speaker(s): 
Mark Hereld
Speaker(s) Title: 
Experimental Systems Engineer, Argonne National Laboratory
Host: 
Michael E. Papka

Increasingly massive datasets produced by tomorrow's simulations beg the question: How will we connect this data to the computational and display resources that support visualization and analysis? This question is driving research into new approaches to allocating computational, storage, and network resources. Some of these approaches rest on creating and exploiting ways to optimally couple these resources in real time.

Examples of what we mean by resource-coupled computations abound. For example, remote visualization is an activity which may couple data and large computation resources at the shared facility to client software and display hardware at the remote site. In situ analysis and visualization contemporaneously merges simulation and analysis onto the shared resource of the supercomputing platform. Co-analysis approaches will directly couple simulations running on a primary supercomputer to live analysis running on an optimized visualization and analysis platform over a high performance network.

Consequently, we are working on a systems approach to modeling the end-to-end activity of extracting understanding from computational models. In this paper we will present our models and results from experiments designed to test them.

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