The GW IPCC center focuses on modern parallel programming for manycore chips and parallel architectures. Areas of specific interest include optimizations, productivity, locality exploitation and Partitioned Global Address Space (PGAS) programming models, applications in high performance computational science and engineering and HPC education.
The group works with domain scientists in many interesting areas including computational neuroscience, and computational science and engineering. Prior work included sponsored research projects in productive locality-aware parallel programming and run-time systems of accelerators including manycore chips and FPGAs and the group will continue some of those efforts under the GW IPCC. In addition, the group will be targeting a number of applications including accelerating brain simulations leveraging its expertise and collaborations in neuroscience and computational neuroscience, PGAS kernels, and VSIPL workloads to name a few.
The GW IPCC will also leverage its DC location and international collaborations for outreach including training and education in the area of productive multicore programming. The outreach will include local/international academia, government, industry and HBCU/MI. Both short training courses and formal class teaching modules will be featured.
Dr. Tarek El-Ghazawi
Professor and IEEE Fellow
Dr. El-Ghazawi is a Professor in the Department of Electrical and Computer Engineering at The George Washington University, where he leads the university-wide Strategic Academic Program in High-Performance Computing. He is the founding director of The GW Institute for Massively Parallel Applications and Computing Technologies (IMPACT). El-Ghazawi’s research interests include high-performance computing, computer architectures, reconfigurable, embedded computing and computer vision. He is one of the principal co-authors of the UPC parallel programming language and the first author of the UPC book from John Wiley and Sons. He has received his Ph.D. degree in Electrical and Computer Engineering from New Mexico State University in 1988. El-Ghazawi has published close to 250 refereed research publications in this area. Dr. El-Ghazawi’s research has been frequently supported by Federal agencies and industry including DARPA/DoD, NSF, DoE/LBNL, NASA, IBM, HP, Intel, AMD, SGI, Microsoft, and Mellanox. He serves or has served on many advisory boards including the Science Advisory Panel of the Arctic Region Supercomputing Center, DSP Logic and Mena Venture. El-Ghazawi received many national and international awards and recognitions. He is a Fellow of the IEEE, and was selected to a Research Faculty Fellow for the IBM Center for Advanced Studies, Toronto. He is a member of the Phi Kappa Phi national honor society and an elected member of the IFIP WG10.3. El-Ghazawi was also a U.S. Fulbright Scholar, a recipient of the 2012 Alexander Schwarzkopf Prize for Technological Innovations, a recipient of the Alexander von Humboldt international research award from Germany, and a recipient of the GWU SEAS Distinguished Researcher Award.
Dr. Vikram K. Narayana
Assistant Research Professor
Areas of Interest: High-Performance and Heterogeneous Computing, Computational Science and Engineering Applications, Photonic Network-on-Chip, New Computing Paradigms.
Dr. Ruben Tikidzhi-Khamburyan
Postdoctoral Research Scientist
Areas of Interest: Computational Neuroscience, Information Processing and Information Coding in Neural Networks, Massively Parallel Models of Neural Systems, Detailed Biophysical Models of Local Neural Networks.
Areas of Interest: High Performance Computing, Programming Models, Systems Optimizations
Areas of Interest: Parallel Computing, Big Data Applications, Photonic Network-on-Chip, Computational Chemistry Simulations
Areas of Interest: Big Data Analytics, High Performance Computing
Areas of Interest: High Performance Computing, Multicore Programming, Computational Neuroscience Simulations
Areas of Interest: Adaptive Mesh Refinement, Computational Engineering, Computational Fluid Dynamics, Mechanical Engineering