Dr. Dhabaleswar K. (DK) Panda is a Professor and University 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 parallel computer architecture, high performance computing, communication protocols, files systems, network-based computing, and Quality of Service. He has published over 400 papers in major journals and international conferences related to these research areas. Dr. Panda and his research group members have been doing extensive research on modern networking technologies including InfiniBand, HSE and RDMA over Converged Enhanced Ethernet (RoCE). His research group is currently collaborating with National Laboratories and leading InfiniBand and 10GigE/iWARP companies on designing various subsystems of next generation high-end systems. The MVAPICH2 (High Performance MPI over InfiniBand, iWARP and RoCE) open-source software package, developed by his research group, are currently being used by more than 2,950 organizations worldwide (in 86 countries). This software has enabled several InfiniBand clusters (including the 1st one) to get into the latest TOP500 ranking. More than 507,000 downloads of these libraries have taken place from the project’s site. These software packages are also available with the stacks for network vendors (InfiniBand and iWARP), server vendors and Linux distributors. The RDMA-enabled Apache Hadoop, Spark and Memcached packages, consisting of acceleration for HDFS, MapReduce, RPC, Spark and Memcached, are publicly available from High-Performance Big Data (HiBD) project site: http://hibd.cse.ohio-state.edu. These packages are currently being used by more than 295 organizations in 35 countries. More than 28,450 downloads have taken place from the project’s site. The group has also been focusing on co-designing Deep Learning Frameworks and MPI Libraries. High-performance and scalable versions of the Caffe and TensorFlow frameworks are available from High-Performance Deep Learning (HiDL) Project site: site: http://hidl.cse.ohio-state.edu. Dr. Panda’s research is supported by funding from US National Science Foundation, US Department of Energy, and several industries including Intel, Cisco, SUN, Mellanox, Microsoft, QLogic, NVIDIA and NetApp. He is an IEEE Fellow and a member of ACM. More details about Dr. Panda, including a comprehensive CV and publications are available at http://web.cse.ohio-state.edu/~panda.2/.

Ammar Ahmad Awan received his B.S. and M.S. degrees in Computer Science and Engineering from National University of Science and Technology (NUST), Pakistan and Kyung Hee University (KHU), South Korea, respectively. Currently, Ammar is working towards his Ph.D. degree in Computer Science and Engineering at The Ohio State University. His current research focus lies at the intersection of High Performance Computing (HPC) libraries and Deep Learning (DL) frameworks. He previously worked on a Java-based Message Passing Interface (MPI) and nested parallelism with OpenMP and MPI for scientific applications. He has published 14 papers in conferences and journals related to these research areas. He actively contributes to various projects like MVAPICH2-GDR (High Performance MPI for GPU clusters, OMB (OSU Micro Benchmarks), and HiDL (High Performance Deep Learning). He is the lead author of the OSU-Caffe framework (part of HiDL project) that allows efficient distributed training of Deep Neural Networks.

Dr. Hari Subramoni is a research scientist in the Department of Computer Science and Engineering at the Ohio State University, USA, since September 2015. His current research interests include high performance interconnects and protocols, parallel computer architecture, network-based computing, exascale computing, network topology aware computing, QoS, power-aware LAN-WAN communication, fault tolerance, virtualization, big data and cloud computing. He has published over 70 papers in international journals and conferences related to these research areas. He has been actively involved in various professional activities in academic journals and conferences. Dr. Subramoni is doing research on the design and development of MVAPICH2 (High Performance MPI over InfiniBand, iWARP and RoCE) and MVAPICH2-X (Hybrid MPI and PGAS (OpenSHMEM, UPC and CAF)) software packages. He is a member of IEEE. More details about Dr. Subramoni are available at http://web.cse.ohio-state.edu/~subramoni.1/.

Julio Suarez is an engineer in the Infrastructure Line of Business at Arm. His top priority is to work with partners to enable and improve the Arm ecosystem. This includes writing blogs, giving presentations, developing proof of concepts, and developing and running server & networking performance workloads. You will often find Julio at trade shows demoing proof of concepts of container and networking technologies running on Arm.

David John Gagne is a Machine Learning Scientist in the Computational and Information Systems and Research Applications Labs at NCAR. He received his PhD in Meteorology from the University of Oklahoma in 2016 and served for 2 years as an ASP Postdoc. His research focuses on developing machine learning modeling systems for high impact weather and physics parameterizations.

Notebooks, instructions and additional material
https://github.com/djgagne/ams-ml-python-course

Sameer Shende serves as the Director of the Performance Research Laboratory at the University of Oregon. His research interests include performance evaluation tools, runtime systems, instrumentation, measurement, and analysis tools, and optimizing compilers.