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Video: Why UIC Uses Containers for HPC Applications on GPUs

In this video from the GPU Technology Conference, John Stone from the University of Illinois describes how container technology in the NVIDIA GPU Cloud help the University distribute accelerated applications for science and engineering. “Containers are a way of packaging up an application and all of its dependencies in such a way that you can install them collectively on a cloud instance or a workstation or a compute node. And it doesn’t require the typical amount of system administration skills and involvement to put one of these containers on a machine.”

Video: HPC Use for Earthquake Research

Christine Goulet from the Southern California Earthquake Center gave this talk at the HPC User Forum in Tucson. “SCEC coordinates fundamental research on earthquake processes using Southern California as its principal natural laboratory. The SCEC community advances earthquake system science through synthesizing knowledge of earthquake phenomena through physics-based modeling, including system-level hazard modeling and communicating our understanding of seismic hazards to reduce earthquake risk and promote community resilience.”

Charliecloud: Unprivileged Containers for User-Defined Software Stacks

“What if I told you there was a way to allow your customers and colleagues to run their HPC jobs inside the Docker containers they’re already creating? or an easily learned, easily employed method for consistently reproducing a particular application environment across numerous Linux distributions and platforms? There is. In this talk/tutorial session, we’ll explore the problem domain and all the previous solutions, and then we’ll discuss and demo Charliecloud, a simple, streamlined container runtime that fills the gap between Docker and HPC — without requiring HPC Admins to lift a finger!”

Video: Addressing Key Science Challenges with Adversarial Neural Networks

Wahid Bhimji from NERSC gave this talk at the 2018 HPC User Forum in Tucson. “Machine Learning and Deep Learning are increasingly used to analyze scientific data, in fields as diverse as neuroscience, climate science and particle physics. In this page you will find links to examples of scientific use cases using deep learning at NERSC, information about what deep learning packages are available at NERSC, and details of how to scale up your deep learning code on Cori to take advantage of the compute power available from Cori’s KNL nodes.”

Introducing the SPEC High Performance Group and HPC Benchmark Suites

Robert Henschel from Indiana University gave this talk at the Swiss HPC Conference. “In this talk, I will present an overview of the High Performance Group as well as SPEC’s benchmarking philosophy in general. Most everyone knows SPEC for the SPEC CPU benchmarks that are heavily used when comparing processor performance, but the High Performance Group specifically focusses on whole system benchmarking utilizing the parallelization paradigms common in HPC, like MPI, OpenMP and OpenACC.”

Ceph on the Brain: Storage and Data-Movement Supporting the Human Brain Project

Adrian Tate from Cray and Stig Telfer from StackHPC gave this talk at the 2018 Swiss HPC Conference. “This talk will describe how Cray, StackHPC and the HBP co-designed a next-generation storage system based on Ceph, exploiting complex memory hierarchies and enabling next-generation mixed workload execution. We will describe the challenges, show performance data and detail the ways that a similar storage setup may be used in HPC systems of the future.”

Scratch to Supercomputers: Bottoms-up Build of Large-scale Computational Lensing Software

Gilles Fourestey from EPFL gave this talk at the Swiss HPC Conference. “LENSTOOL is a gravitational lensing software that models mass distribution of galaxies and clusters. It is used to obtain sub-percent precision measurements of the total mass in galaxy clusters and constrain the dark matter self-interaction cross-section, a crucial ingredient to understanding its nature.”

Shifter – Docker Containers for HPC

Alberto Madonaa gave this talk at the Swiss HPC Conference. “In this work we present an extension to the container runtime of Shifter that provides containerized applications with a mechanism to access GPU accelerators and specialized networking from the host system, effectively enabling performance portability of containers across HPC resources. The presented extension makes possible to rapidly deploy high-performance software on supercomputers from containerized applications that have been developed, built, and tested in non-HPC commodity hardware, e.g. the laptop or workstation of a researcher.”

Accelerating Ceph with RDMA and NVMe-oF

Haodong Tang from Intel gave this talk at the 2018 Open Fabrics Workshop. “Efficient network messenger is critical for today’s scale-out storage systems. Ceph is one of the most popular distributed storage system providing a scalable and reliable object, block and file storage services. As the explosive growth of Big Data continues, there’re strong demands leveraging Ceph build high performance & ultra-low latency storage solution in the cloud and bigdata environment. The traditional TCP/IP cannot satisfy this requirement, but Remote Direct Memory Access (RDMA) can.”

Amazon and Libfabric: A case study in flexible HPC Infrastructure

Brian Barrett from Amazon gave this talk at the 2018 OpenFabrics Workshop. “As network performance becomes a larger bottleneck in application performance, AWS is investing in improving HPC network performance. Our initial investment focused on improving performance in open source MPI implementations, with positive results. Recently, however, we have pivoted to focusing on using libfabric to improve point to point performance.”