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Toronto Startup Launches HPCBOX – An Elastic HPC Cloud Platform

Today Toronto startup Drizti announced the availability of HPCBOX, a desktop-centric, intelligent workflow cloud HPC platform for automating and executing application pipelines. “HPCBOX introduces an innovative method of plugging in cloud infrastructure into application pipelines and provides a rich desktop experience, including hardware accelerated remote graphics technology for authoring workflows with its workflow editor. Users from multiple industry verticals, like Manufacturing, Packaging, Automotive, Renewable Energy, Aerospace etc., who use Simulation Engineering, AI, or Machine Learning technologies and require HPC can cut costs can immensely benefit from this turn-key HPC cloud platform.”

Job of the Week: HPC Architecture and Performance Engineer at LBNL

Lawrence Berkeley National Lab is seeking an HPC Architecture and Performance Engineer in our Job of the Week. “Berkeley Lab’s National Energy Research Scientific Computing Center (NERSC) has an opening for a Computer Systems Engineer 3. The incumbent will contribute to an on-going Advanced Technology Group (ATG) group effort to develop a complete understanding of the issues that lead to improved application and computer system performance on extreme-scale advanced architectures. As a team member, they will contribute to efforts for NERSC in evaluating existing and emerging High Performance Computing (HPC) systems by analyzing the performance characteristics of leading-edge DOE Office of Science application codes.”

There’s still Time to register for HPC User Forum in Detroit – Agenda targets AI, Autonomous Cars, & Sensor Networks

There’s still Time to register for HPC User Forum in Detroit. The meeting takes place September 4-6 in Dearborn, Michigan. Key topics include AI and other advanced analytics, automated driving systems a.k.a. self-driving vehicles, additive manufacturing and HPC in clouds (and outer space!). “If AI is in your crosshairs, you won’t want to miss the next HPC User Forum in Dearborn, Michigan. Aside from tackling leadership computing initiatives in the U.S. and around the world, the meeting will zero in on artificial intelligence use cases on prem and in the cloud, especially self-driving vehicle development and urban sensor networks.”

The Rigetti 128-qubit chip — What it means for quantum

Chad Rigetti writes that his company is building a 128-qubit quantum computer over the next 12 months. The company has already built the 128-qubit processing chip. If successful, it could be the world’s most powerful quantum computer and it could have the chance to outpace traditional supercomputers. “To drive practical use of quantum computing today, we must be able to scale and improve the performance of the chips and connect them to the electronics on which they run — which has proven to be one of the most challenging aspects of quantum computing.”

Supercomputing HIV-1 Replication at TACC

Researchers are using TACC supercomputers in the fight against HIV. In a new study published in Nature, a team led by Cornell researcher found the naturally-occurring compound IP6 promotes both assembly and maturation of HIV-1. “We discovered, in collaboration with other researchers, that HIV uses this small molecule to complete its function,” said Juan R. Perilla, Department of Chemistry and Biochemistry, University of Delaware. “This is a molecule that’s extremely available in human cells and in other mammalian cells. HIV has evolved to make use of these small molecules present in our cells to essentially be infectious.”

Julia 1.0 release Opens the Doors for a Connected World

Today Julia Computing announced the Julia 1.0 programming language release. As the first complete, reliable, stable and forward-compatible Julia release, version 1.0 is the fastest, simplest and most productive open-source programming language for scientific, numeric and mathematical computing. “During the last six and a half years, Julia has reached more than 2 million downloads and early adopters have already put Julia into production to power self-driving cars, robots, 3D printers and applications in precision medicine, augmented reality, genomics, energy trading, machine learning, financial risk management and space mission planning.”

Dr. Eng Lim Goh presents: Prediction – Use Science or History?

Dr. Eng Lim Goh from HPE gave this keynote talk at PASC18. “Traditionally, scientific laws have been applied deductively – from predicting the performance of a pacemaker before implant, downforce of a Formula 1 car, pricing of derivatives in finance or the motion of planets for a trip to Mars. With Artificial Intelligence, we are starting to also use the data-intensive inductive approach, enabled by the re-emergence of Machine Learning which has been fueled by decades of accumulated data.”

Video: New Cascade Lake Xeons to Speed Ai with Intel Deep Learning Boost

This week at the Data-Centric Innovation Summit, Intel laid out their near-term Xeon roadmap and plans to augment their AVX-512 instruction set to boost machine learning performance. “This dramatic performance improvement and efficiency – up to twice as fast as the current generation – is delivered by using a single instruction to handle INT8 convolutions for deep learning inference workloads which required three separate AVX-512 instructions in previous generation processors.”

Video: Neutrino Telescope Data Management and Analysis

In this video from PASC18, Tessa Carver from the University of Geneva presents: Neutrino Telescope Data Management and Analysis. “We will describe the data flow structure of onsite DAQ to filtered steams for various physics scopes of IceCube and ANTARES and the plans for KM3NeT. The Data formats and data management software will also be described as well as plans for making data public.”

Thierry Pellegrino on What’s New at the Dell HPC Community

In this video from the Dell EMC HPC Community Meeting, VP Thierry Pellegrino describes how AI and HPC are coming together to foster innovation. “The newly announced Dell EMC Ready Solutions for AI were built to simplify Machine Learning, deliver faster, deeper insights, and leverage Dell EMC’s proven AI expertise. Organizations no longer have to individually source and piece together their own solutions. Instead, they can rely on a Dell EMC-designed and validated set of best-of-breed technologies for software – including AI frameworks and libraries – with compute, networking and storage.”