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Hardware & Software Platforms for HPC, AI and ML

Gunter Roeth from NVIDIA gave this talk at the UK HPC Conference. “Today, NVIDIA’s tensor core GPU sits at the core of most AI, ML and HPC applications, and NVIDIA software surrounds every level of such a modern application, from CUDA and libraries like cuDNN and NCCL embedded in every deep learning framework and optimized and delivered via the NVIDIA GPU Cloud to reference architectures designed to streamline the deployment of large scale infrastructures.”

Progress and Challenges for the Use of Deep Learning to Improve Weather Forecasts

Peter Dueben from ECMWF gave this talk at the UK HPC Conference. “I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will then talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future.”

Convergence for Scientific Method: HPC, AI, Simulation and Experiment

Alan Real from Durham University gave this talk at the UK HPC Conference. “This talk will discuss how advances in instrumentation have caused many new areas to embrace HPC and AI in order to successfully conduct and understand their experiments.”

Video: InfiniBand In-Network Computing Technology and Roadmap

Rich Graham from Mellanox gave this talk at the UK HPC Conference. “In-Network Computing transforms the data center interconnect to become a “distributed CPU”, and “distributed memory”, enables to overcome performance barriers and to enable faster and more scalable data analysis. HDR 200G InfiniBand In-Network Computing technology includes several elements – Scalable Hierarchical Aggregation and Reduction Protocol (SHARP), smart Tag Matching and rendezvoused protocol, and more. This session will discuss the InfiniBand In-Network Computing technology and performance results, as well as view to future roadmap.”

Video: The Cambridge Research Computing Service

Paul Calleja from the University of Cambridge gave this talk at the UK HPC Conference. “With unprecedented access to increasing volumes of data, our research ranges from the underlying fundamentals in mathematics and computer science, to data science applications across all six University Schools of Arts and Humanities, Biological Sciences, Clinical Medicine, Humanities and Social Sciences, Physical Sciences, and Technology.”

Designing Scalable HPC, Deep Learning, Big Data, and Cloud Middleware for Exascale Systems

DK Panda from Ohio State University gave this talk at the UK HPC Conference. “This talk will focus on challenges in designing HPC, Deep Learning, Big Data and HPC Cloud middleware for Exascale systems with millions of processors and accelerators. For the HPC domain, we will discuss about the challenges in designing runtime environments for MPI+X (PGAS – OpenSHMEM/UPC/CAF/UPC++, OpenMP, and CUDA) programming models by taking into account support for multi-core systems (Xeon, ARM and OpenPower), high-performance networks, and GPGPUs (including GPUDirect RDMA).”

Accelerating Research and Enterprise Solutions by Bridging HPC and AI

Venkatesh Kannan from ICHEC gave this talk at the UK HPC Conference. “The presentation will highlight the need to address the symbiotic relationship between HPC and AI at different levels – technology development, education & training, and policy making – in order to enable the adoption and accelerating the development of AI solutions by the research and enterprise communities. A number of efforts and projects that are undertaken at the Irish Centre for High-End Computing towards enabling and achieving this in the Irish and European context will be presented.”

The Eco-System of AI and How to Use It

Glyn Bowden from HPE gave this talk at the UK HPC Conference. “This presentation walks through HPE’s current view on AI applications, where it is driving outcomes and innovation, and where the challenges lay. We look at the eco-system that sits around an AI project and look at ways this can impact the success of the endeavor.”