KEYNOTE SESSIONSSaudi HPC/AI Conference 2022:Using HPC & AI to accelerate and improve medical research (September 27-29, 2022)
Dr. Othmane Bouhali
Texas A&M University in Qatar
High Performance Computing and artificial intelligence in medical physics applications
Short DescriptionModelling in medical physics and nuclear medicine has witnessed significant increase thanks to the development of computational resources in the past decade. In this talk we will present our ongoing research in areas of radiotherapy and internal dosimetry. We will show that Monte Carlo tools coupled with HPC resources and methods have been a game changer in the fields of medical imaging and diagnosis.
Moreover, we will also address the benefit that AI provides to improve medical imaging capabilities and achieve dose optimization in treatment of cancer and other diseases.
HPC EMEA Director, Intel
HPC & AI with Intel in the New Era of Supercomputing
Short DescriptionHPC, AI, and Analytics users ask more of their HPC-AI systems than ever before. High Performance Computing is the foundation of research and discovery. Artificial Intelligence is adding to it. Intel’s deep investments in developer ecosystems, tools, technology and an open platform are clearing the path forward to scale artificial intelligence everywhere. Intel has made AI more accessible and scalable for developers through extensive optimizations of popular libraries and frameworks on Intel® Xeon® Scalable processors. Intel’s investment in multiple AI architectures to meet diverse customer requirements, using an open standards-based programming model, makes it easier for developers to run more AI workloads in more use cases. Let’s look at Intel HPC-AI strategy and new innovations including the latest Intel® Xeon® Scalable processors, data center GPUs and powerful software tools. Together, let’s accelerate the next era of innovation in HPC-AI.
Facilities Director, Research Computing Core Labs, KAUST
HPC and AI services and applications at KAUST
Short DescriptionAs Supercomputers are becoming an essential universal tool for scientific discoveries, HPC was embedded in the KAUST DNA since its first year of operation. With the latest increased interest in AI, KAUST has adopted a strategy to provide the necessary tools and support for its AI researchers. In this talk, an overview of KAUST HPC and AI infrastructure, associated services and applications will be given. Some collaborations especially with Saudi organizations will also be highlighted.
Dhabaleswar K. (DK) Panda
Professor and University Distinguished Scholar, The Ohio State University
High-Performance Deep Learning, Machine Learning, and Data Science on Modern HPC Systems
Short DescriptionThis talk will start with an overview of challenges being faced by the AI community to achieve high-performance Deep Learning (DL), Machine Learning (ML), and Data Science on Modern HPC systems with both scale-up and scale-out strategies. Next, we will focus on a range of solutions to address these challenges:
(1) MPI-driven Deep Learning on CPU and GPU-based systems,
(2) Out-of-core DNN training and exploiting Hybrid (Data and Model) parallelism for training large models and data,
(3) High-performance MPI Runtime for cuML to support GPU-accelerated ML applications, and
(4) High-Performance Dask for supporting data science applications. Case studies to accelerate DL, ML, and data science applications on modern HPC systems will be presented.
Director, Research Computing Services, Cambridge University, UK
Short DescriptionPaul Calleja is the Director of the Cambridge Open Exascale Lab and of Research Computing Services at the University of Cambridge. Dr Calleja obtained his Ph.D. in computational bio-physics at the University of Bath. After obtaining a post-doctoral research position at Birkbeck, University of London, he moved into private industry, where he spearheaded the early commercialisation of High Performance Computing cluster solutions in the UK.
Following six years in the commercial sector – during which time he led the market transition from proprietary SMP systems to commodity cluster-based solutions – Dr. Calleja returned to academia. At Imperial College London, Dr Calleja led the formation of a new HPC service, before moving in 2006 to the University of Cambridge to direct a major reorganisation of research computing services. This has resulted in University-wide HPC capabilities using a novel pay-per-use cloud computing model. The University of Cambridge is now home to the fastest academic supercomputer in the UK.
Muataz Al Barwani
Senior Director, Center for Research Computing, New York University Abu Dhabi, Abu Dhabi, UAE
Research Computing @ NYUAD