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Nvidia Launches AI Enterprise Suite for VMware vSphere
Nvidia and VMware are bringing together the new Nvidia AI Enterprise software tool suite with VMware’s latest vSphere 7 Update 2 virtualization platform to make it easier for enterprises to vir …
IBM Continues Mainstreaming Power Systems and Integrating Red Hat in Pivot to Cloud
As IBM continues its massive pivot to the cloud, its Power-microprocessor-based products are being mainstreamed and realigned with the corporate-wide strategy. HPC, while not out, is being de-emp …
Announcing the 2023 Readers’ and Editors’ Choice Awards!
Check out our list of 108 illustrious winners across 22 different categories of HPC.
Using AI to Solve One of the Most Prevailing Problems in CFD
October 17, 2019
How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…
DARPA Looks to Unclog Networks
October 1, 2019
DARPA will seek to unclog the networking bottlenecks that are hindering wider use of powerful hardware in computing-intensive applications. The Pentagon research agency has unveiled another in a series of post-Moore’s Law computing initiatives... Read more…
SC19 Preview: 12 Invited Talks Over Three Days
September 3, 2019
The SC19 Invited Talks will be held over three days starting on Nov. 19 through Nov. 21, 2019, in Denver, Colorado. Read more…
HPC in Life Sciences Part 1: CPU Choices, Rise of Data Lakes, Networking Challenges, and More
February 21, 2019
For the past few years HPCwire and leaders of BioTeam, a research computing consultancy specializing in life sciences, have convened to examine the state of HPC (and now AI) use in life sciences. Without HPC writ large, modern life sciences research would quickly grind to a halt. It’s true most life sciences research computing... Read more…
OpenHPC Gathers Steam, Preps New Release for SC18
November 1, 2018
You may recall at SC15 an Intel-led group introduced OpenHPC – an effort to build a community project around an open source, plug-and-play HPC stack. One goal Read more…
SC17: Singularity Preps Version 3.0, Nears 1M Containers Served Daily
November 1, 2017
Just a few months ago about half a million jobs were being run daily using Singularity containers, the LBNL-founded container platform intended for HPC. That wa Read more…
Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration
September 12, 2017
Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…
Rethinking HPC Platforms for ‘Second Gen’ Applications
February 22, 2017
Just what constitutes HPC and how best to support it is a keen topic currently. A new paper posted last week on arXiv.org – Rethinking HPC Platforms: Challeng Read more…
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Whitepaper
Penguin Computing Scyld Cloud Central™: A New Cloud-First Approach to HPC and AI Workloads
Making the Most of Today’s Cloud-First Approach to Running HPC and AI Workloads With Penguin Scyld Cloud Central™
Bursting to cloud has long been used to complement on-premises HPC capacity to meet variable compute demands. But in today’s age of cloud, many workloads start on the cloud with little IT or corporate oversight. What is needed is a way to operationalize the use of these cloud resources so that users get the compute power they need when they need it, but with constraints that take costs and the efficient use of existing compute power into account. Download this special report to learn more about this topic.
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QCT POD- An Adaptive Converged Platform for HPC and AI
Data center infrastructure running AI and HPC workloads requires powerful microprocessor chips and the use of CPUs, GPUs, and acceleration chips to carry out compute intensive tasks. AI and HPC processing generate excessive heat which results in higher data center power consumption and additional data center costs.
Data centers traditionally use air cooling solutions including heatsinks and fans that may not be able to reduce energy consumption while maintaining infrastructure performance for AI and HPC workloads. Liquid cooled systems will be increasingly replacing air cooled solutions for data centers running HPC and AI workloads to meet heat and performance needs.
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