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Dr. Christian Engelmann
Oak Ridge National Laboratory
One Bethel Valley Road, Oak Ridge, TN 37831-6173, USA
+1 (865) 574-3132
+1 (865) 576-5491
engelmannc@ornl.gov

Abstract

Dr. Christian Engelmann is a Research and Development Associate in the System Research Team of the Computer Science Research Group in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL). He holds a PhD and a MSc in Computer Science from the University of Reading, UK, and a German Certified Engineer diploma (MSc equivalent) in Computer Systems Engineering from the Technical College for Engineering and Economics (FHTW) Berlin.

Dr. Engelmann's work deals with software research and development for next-generation extreme-scale high-performance computing (HPC) systems. As part of the System Research Team at ORNL and in collaboration with other laboratories and universities, Dr. Engelmann's research aims at providing high-level reliability, availability, and serviceability (RAS) for next-generation supercomputers to improve their resiliency (and ultimately efficiency) by performing research and development in novel high availability and fault tolerance system software solutions. Another area Dr. Engelmann is focusing on is research and development in core system software technologies to enable "plug-and-play" supercomputing, which offers transparent portability of software to eliminate most of the software modifications caused by divers supercomputing platforms and supercomputing system upgrades.

Other, past research by Dr. Engelmann included work on a pluggable lightweight heterogeneous Distributed Virtual Machine (DVM) environment, where clusters of personal computers, workstations, and supercomputers can be aggregated to form one giant DVM (in the spirit of its widely-used predecessor, Parallel Virtual Machine (PVM)). Further past work was part of a Cooperative Research and Development Agreement (CRADA) with IBM that focused on a new generation of scientific algorithms (super-scalable algorithms) to address the challenges in scalability and fault tolerance for extreme-scale supercomputers, such as the IBM Blue Gene/L system.

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