Colloq: Speaker Institution:
University of Oregon
Lawrence Berkeley National Laboratory
Colloq: Date and Time:
Wed, 2013-08-21 11:00
Colloq: Host Email:
Many of today’s parallel visualization and analysis programs are designed for distributed-memory parallelism, but not for the shared-memory parallelism available on GPUs or multi-core CPUs. However, architectural trends on supercomputers increasingly contain more and more cores per node, whether through the presence of GPUs or through more cores per CPU node. To make the best use of such hardware, we must evaluate the benefits of hybrid parallelism — parallelism that blends distributed- and shared-memory approaches — for visualization and analysis's data-intensive workloads. With this talk, Hank explores the fundamental challenges and opportunities for hybrid parallelism with visualization and analysis, and discusses recent results that measure its benefit.
Colloq: Speaker Bio:
Hank Childs is an assistant professor at the University of Oregon and a computer systems engineer at Lawrence Berkeley National Laboratory. His research focuses on scientific visualization, high performance computing, and the intersection of the two. He received the Department of Energy Career award in 2012 to research explorative visualization use cases on exascale machines. Additionally, Hank is one of the founding members of the team that developed the VisIt visualization and analysis software. He received his Ph.D. from UC Davis in 2006.