Karl Schulz, Intel
In this video from the 4th Annual MVAPICH User Group, Karl Schulz from Intel presents: OpenHPC – Community Building Blocks for HPC Systems.
“Today, many supercomputing sites spend considerable effort aggregating a large suite of open-source projects on top of their chosen base Linux distribution in order to provide a capable HPC environment for their users. They also frequently leverage a mix of external and in-house tools to perform software builds, provisioning, config management, software upgrades, and system diagnostics. Although the functionality is similar, the implementations across sites is often different which can lead to duplication of effort. This presentation will use the above challenges as motivation for introducing a new, open-source HPC community (OpenHPC) that is focused on providing HPC-centric package builds for a variety of common building-blocks in an effort to minimize duplication, implement integration testing to gain validation confidence, incorporate ongoing novel R&D efforts, and provide a platform to share configuration recipes from a variety of sites.”
Karl W. Schulz received his Ph.D. in Aerospace Engineering from the University of Texas in 1999. After completing a one-year post-doc, he transitioned to the commercial software industry working for the CD-Adapco group as a Senior Project Engineer to develop and support engineering software in the field of computational fluid dynamics. After several years in industry, Karl returned to the University of Texas in 2003, joining the research staff at the Texas Advanced Computing Center (TACC). During his time at TACC, Karl engaged in HPC research, scientific curriculum development, technology evaluation, and strategic initiatives serving on the Center’s leadership team as an Associate Director and leading TACC’s HPC group and Scientific Applications group during his tenure. Karl joined the Technical Computing Group at Intel in January 2014 and leads a team of Cluster Makers focused on improving runtime environments, administration, and scaling properties for future HPC systems.
