Judges

Filippo Spiga

Filippo Spiga (@filippospiga, LinkedIn) is Staff Research Engineer at Software and Large Scale System group in Arm Research (Cambridge, UK). His work focuses on HW-SW co-design for High Performance Computing and High Performance Data Analytics. Prior Arm, he worked for 5 years at the Research Computing Services of University of Cambridge as Head of Research Software Engineering. He has been developing and contributing in various HPC codes (mainly physics, chemistry and engineering) for more than 9 years. He has also been a long-term contributor of Quantum ESPRESSO.
For the the past 4 years he has been involved with the HPC Advisory Council in co-organising and run the ISC Student Cluster Competitions.

Nitin Bhat

Nitin Bhat (Linkedin) is a software engineer at Charmworks – the startup that licenses and supports Charm++. Charm++ is a parallel programming model and adaptive runtime system that provides scalable solutions for parallel programming problems. Nitin has experience with different aspects of the Charm++ runtime system and applications, with a special focus on low level networking routines and implementations. Prior to Charmworks, he graduated from the University of Illinois Urbana-Champaign with an MS degree in Computer Science specializing in High Performance Computing and has also worked at the Supercomputing Education and Research Center at the Indian Institute of Science, Bangalore.

Scot Schultz

Scot Schultz (@scotschultz)is a HPC and AI technology specialist with broad knowledge in operating systems, machine learning frameworks, high-speed interconnects and processor technologies. Joining Mellanox in early 2013, Schultz is 30-year veteran of the computing industry. Prior to joining Mellanox, spent 17 years in various engineering and leadership roles; including strategic HPC technology ecosystem enablement. Scot has been instrumental with the growth and development of numerous industry standards-based organizations including OpenPOWER Foundation, GenZ, Open Fabrics Alliance, HPC Advisory Council and many others.

Dhabaleswar K. (DK) Panda

DK Panda is a Professor and University Distinguished Scholar of
Computer Science and Engineering at the Ohio State University. He has published over 450 papers in the area of high-end computing and networking. The MVAPICH2 (High Performance MPI and PGAS over InfiniBand, Omni-Path, iWARP and RoCE) libraries, designed and developed by his research group (http://mvapich.cse.ohio-state.edu), are currently being used by more than 3,000 organizations worldwide (in 88 countries). More than 543,000 downloads of this software have taken place from the project’s site. This software is empowering several InfiniBand clusters (including the 3rd, 14th, 17th, and 27th ranked ones) in the TOP500 list. The RDMA packages for Apache Spark, Apache Hadoop and Memcached together with OSU HiBD benchmarks from his group (http://hibd.cse.ohio-state.edu) are also publicly available. These libraries are currently being used by more than 310 organizations in 35 countries. More than 30,000 downloads of these libraries have taken place. High-performance and scalable versions of the Caffe and TensorFlow framework are available from https://hidl.cse.ohio-state.edu. Prof. Panda is an IEEE Fellow. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Dan Olds

Dan Olds is a technology industry analyst and partner at high tech strategy firm OrionX. In addition to server, storage, and network technologies, Dan closely follows AI, Cloud, Large Enterprise, and HPC markets. He co-hosts the popular Radio Free HPC podcast and is a frequent contributor to various HPC and industry publications. Dan began his career at Sequent Computer Systems, an early pioneer in high scalable business servers. He was the inaugural lead for the highly successful server consolidation program at Sun Microsystems and was at IBM in the strategically important mainframe and Power systems groups. He is a graduate of University of Chicago Booth School of Business with a focus on finance and marketing. Dan has been following and documenting Student Cluster Competitions for nearly a decade and is the go to authority on all things related to the competitions.

Anja Gerbes

Anja works at the Center for Scientific Computing and is a member of Hessian Competence Center for High Performance Computing located at Goethe University in Frankfurt/Main. A considerable part of her job role is to develop a range of courses and resources to enable users to work with the cluster. In addition, she is doing a PhD at the German Climate Research Center in Hamburg as an external member. The main topic is Compiler Optimization in High-Performance Computing with an aim to improve weather forecasting and climate modeling. The goal of her PhD is to study the compiler for deficits in terms of performance when translating HPC applications and to understand the limitations of compilers in making the necessary optimizations. These insights can then be incorporated into the compiler for future automatic compiler optimization. Automatic program transformation using source-to-source instrumentation of parallel programs will prepare HPC applications for future performance analysis.

Elizabeth Leake

Elizabeth Leake (@STEMTrek) is a consultant, correspondent and advocate who serves the global high-performance computing (HPC) and data science industries. In 2012, she founded STEM-Trek, a global, grassroots nonprofit organization that supports scholarly travel and workforce development opportunities for science, technology, engineering and mathematics (STEM) scholars from underserved regions and underrepresented groups.
As a program director, Leake has mentored hundreds of early-career professionals who are breaking cultural barriers in an effort to accelerate scientific and engineering discoveries. Her multinational programs have specific themes that resonate with global stakeholders, such as food security data science, blockchain for social good, cybersecurity/risk mitigation, and more. As a conference blogger and communicator, her work drew recognition when STEM-Trek received the 2016 and 2017 HPCwire Editors’ Choice Awards for Workforce Diversity Leadership.

Pak Lui

Pak Lui (@paklui, LinkedIn) is the Principal HPC Solution Architect for HPC at AMD. He has served in various roles in the HPC industry for about 20 years. Before AMD, he has been a Principal Architect at Futurewei Technologies, Huawei USA R&D center, who worked on the Arm HPC Solutions and served as an Partner/Associate Engineer at Linaro. Before that, Pak worked as the Senior Manager of Application Performance at Mellanox Technologies for over 7 years, and involved in demonstrating application performance on various open source and commercial applications. Pak dedicated time on the HPC Advisory Council and involved in characterizing HPC workloads, analyzing MPI profiles to optimize HPC applications, as well as exploring new technologies, solutions and their effectiveness on real HPC workloads. Prior to joining Mellanox Technologies, Pak worked as a Cluster Engineer at Penguin Computing. Pak also worked at Sun Microsystems for over 7 years in Sun’s High Performance Computing (HPC) group as a Software Engineer for Open MPI and Sun HPC ClusterTools MPI library development. Pak holds a B.Sc. in Computer Systems Engineering and a M.Sc. in Computer Science from Boston University in the United States.

Thomas Zwinger

Thomas Zwinger is a senior application specialist at the CSC - IT Center for Science Ltd. in Espoo, Finland, and adjunct professor (cryosphere physics) at Helsinki University. He holds a PhD in Mechanical Engineering (fluid mechanics). Thomas has more than 20 years of experience in HPC simulations of geophysical flows (ice sheet, glaciers, and avalanches), and co-authored more than 50 research articles in peer reviewed journals and book series. He is one of the main developers of the state-of-the-art ice sheet code Elmer/Ice (http://elmerice.elmerfem.org) based on CSC’s FEM code Elmer. Results obtained with Elmer/Ice for simulations of Earth’s large ice sheets, i.e. Greenland and Antarctica, directly contributed to sea-level rise estimations in past and ongoing UN IPCC assessment reports. By the nature of the size of these ice-masses, Thomas is involved in running computations on HPC systems as well as the optimization of Elmer and Elmer/Ice for these platforms.