Dhabaleswar K. Panda(editor)
Dr. Dhabaleswar K. (DK) Panda is a Professor and Distinguished Scholar of Computer Science at the Ohio State University. He obtained his Ph.D. in computer engineering from the University of Southern California. His research interests include high-performance computing, high-performance networking (InfiniBand), big data analytics (Spark and Hadoop), Deep Learning, cloud computing, Virtualization, GPUs and accelerators, file systems and storage, and exascale computing. Dr. Dhabaleswar K. (DK) Panda is a Professor and Distinguished Scholar of Computer Science at the Ohio State University. He obtained his Ph.D. in computer engineering from the University of Southern California. His research interests include high-performance computing, high-performance networking (InfiniBand), big data analytics (Spark and Hadoop), Deep Learning, cloud computing, Virtualization, GPUs and accelerators, file systems and storage, and exascale computing.
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About Dhabaleswar K. Panda(editor)
Dr. Dhabaleswar K. (DK) Panda is a Professor and Distinguished Scholar of Computer Science at the Ohio State University. He obtained his Ph.D. in computer engineering from the University of Southern California. His research interests include high-performance computing, high-performance networking (InfiniBand), big data analytics (Spark and Hadoop), Deep Learning, cloud computing, Virtualization, GPUs and accelerators, file systems and storage, and exascale computing.
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Supercomputing Frontiers: 6th Asian Conference, SCFA 2020, Singapore, February 24–27, 2020, Proceedings
This open access book constitutes the refereed proceedings of the 6th Asian Supercomputing Conference, SCFA 2020, which was planned to be held in February 2020, but unfortunately, the physical conference was cancelled due to the COVID-19 pandemic. The 8 full papers presented in this book were carefully reviewed and selected from 22 submissions. They cover a range of topics including file systems, memory hierarchy, HPC cloud platform, container image configuration workflow, large-scale applications, and scheduling.
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