LANS Informal Seminar: Tom Peterka

Seminar Title: Scalable Data Analysis
Speaker: Tom Peterka, MCS

Date/Time: 2010-06-09 15:00
Location: Bldg 240 Conference Center 1404-1405

Description:
While data analysis and visualization have contributed to scientific discoveries since the 1600s, what we think of today as modern scientific visualization dates back to the late 1980s. Over the past 20 years or so, computer scientists have developed fundamental algorithms that produce meaningful analysis of computed datasets, but as computations grow in size and complexity, the resulting datasets are beginning to overwhelm the way that we are accustomed to processing them. Finding scalable solutions to data analysis is a challenging problem now, one that will only grow as we advance toward exascale computing. In particular, the high cost of moving and accessing data motivates performing analysis in some unconventional places in HPC systems. These include computational nodes, I/O nodes, and the storage system, alongside the conventional data analysis cluster nodes. This talk will examine the feasibility of performing parallel analysis directly on the same compute nodes used to generate the simulation, and will draw upon examples in parallel volume rendering, parallel image compositing, and parallel particle tracing to analyze the scalability of these approaches.