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Exascale Computing Project updates Extreme-Scale Scientific Software Stack

Exascale computing is only a few years away. Today the Exascale Computing Project (ECP) put out the second release of their Extreme-Scale Scientific Software Stack. The E4S Release 0.2 includes a subset of ECP ST software products, and demonstrates the target approach for future delivery of the full ECP ST software stack. Also available are […]

XTREME-Stargate: The New Era of HPC Cloud Platforms

In this video from the 2019 Stanford HPC Conference, Naoki Shibata from XTREME-D presents: XTREME-Stargate: The New Era of HPC Cloud Platforms. “XTREME-D is an award-winning, funded Japanese startup whose mission is to make HPC cloud computing access easy, fast, efficient, and economical for every customer. The company recently introduced XTREME-Stargate, which was developed as a cloud-based bare-metal appliance specifically for high-performance computations, optimized for AI data analysis and conventional supercomputer usage.”

Quantum Computing: From Qubits to Quantum Accelerators

Koen Bertels from Delft University of Technology gave this talk at HiPEAC 2019. “In my talk, I will introduce what quantum computers are but also how they can be used as a quantum accelerator. I will discuss why a quantum computer can be more powerful than any classical computer and what the components are of its system architecture. In this context, I will talk about our current research topics on quantum computing, what the main challenges are and what is available to our community.”

NVIDIA steps up with Nsight Systems Performance Analysis Tool

Today NVIDIA announced that NVIDIA Nsight Systems 2019.1 is now available for download. As a system-wide performance analysis tool. With it, developers can visualize application algorithms, identify large optimization opportunities, and tune/scale efficiently across CPUs and GPUs. “In this release, we introduce a wide range of new features, refinements, and fixes. The enhancements aim to improve a user’s ability to analyze neural network performance, locate graphical stutter, and increase pattern discoverability.”

Podcast: What is an Ai Supercomputer?

In this podcast, the Radio Free HPC team asks whether a supercomputer can or cannot be a “AI Supercomputer.” The question came up after HPE announced a new AI system called Jean Zay that will double the capacity of French supercomputing. “So what are the differences between a traditional super and a AI super? According to Dan, it mostly comes down to how many GPUs the system is configured with, while Shahin and Henry think it has something to do with the datasets.”

Video: Speeding up Programs with OpenACC in GCC

Thomas Schwinge from Mentor gave this talk at FOSDEM’19. “Requiring only few changes to your existing source code, OpenACC allows for easy parallelization and code offloading to accelerators such as GPUs. We will present a short introduction of GCC and OpenACC, implementation status, examples, and performance results.”

Video: Frontiers of AI Deployments in HPC on Arm

In this video from Arm HPC Asia 2019, Elsie Wahlig leads a panel discussion on Frontiers of AI deployments in HPC on Arm. “Topics at the workshop covered all aspects of the Arm server ecosystem, from chip design, hardware, software architecture and standardization to performance tuning, and applications in biology, medicine, meteorology, astronomy, geography etc. It is exciting to see that Arm servers are being used in so many areas, contributing significantly to the global economy.”

Job of the Week: Computer Scientist at the Jülich Supercomputing Centre

The Jülich Supercomputing Centre in Germany is seeking a Computer Scientist in our Job of the Week. “The institute of Bio- and Geosciences – Agrosphere contributes to an improved understanding and reliable prediction of hydrologic and biogeochemical processes in terrestrial systems. You will develop and apply advanced geoscientific simulation software in high-performance computing environments of the Jülich Supercomuting Centre.”

Video: OpenHPC Update

Adrian Reber from Red Hat gave this talk at the FOSDEM’19 conference. “In this talk I want to give an introduction about the OpenHPC project. Why do we need something like OpenHPC? What are the goals of OpenHPC? Who is involved in OpenHPC and how is the project organized? What is the actual result of the OpenHPC project? It also has been some time (it was FOSDEM 2016) since OpenHPC was part of the HPC, Big Data and Data Science devroom, so that it seems a good opportunity for an OpenHPC status update and what has happened in the last three years.”

Rapids: Data Science on GPUs

Christoph Angerer from NVIDIA gave this talk at FOSDEM’19. “The next big step in data science will combine the ease of use of common Python APIs, but with the power and scalability of GPU compute. The RAPIDS project is the first step in giving data scientists the ability to use familiar APIs and abstractions while taking advantage of the same technology that enables dramatic increases in speed in deep learning. This session highlights the progress that has been made on RAPIDS, discusses how you can get up and running doing data science on the GPU, and provides some use cases involving graph analytics as motivation.”