November 27, 2020
As HPE’s chief technology officer for artificial intelligence, Dr. Eng Lim Goh devotes much of his time talking and consulting with enterprise customers about Read more…
November 19, 2020
SC20’s keynote was delivered by renowned meteorologist and climatologist Bjorn Stevens, a director at the Max Planck Institute for Meteorology since 2008 and a professor at the University of Hamburg. In his keynote, Stevens traced the history of climate science from its earliest days through... Read more…
September 23, 2020
A bit over a year ago, the United States’ Global Forecast System (GFS) received a major upgrade: a new dynamical core – its first in 40 years – called the finite-volume cubed-sphere, or FV3. Now, the National Oceanic and Atmospheric Administration (NOAA) is bringing the FV3 dynamical core to... Read more…
May 21, 2020
Hurricane formation has long remained shrouded in mystery, with meteorologists unable to discern exactly what forces cause the devastating storms (also known as Read more…
August 26, 2019
Hurricane Harvey was a watershed moment for extreme weather modeling. Operational models made some accurate predictions – storm path, flooding potential – b Read more…
July 19, 2019
As climate change looms, researchers are scrambling to answer the question of how a warming planet will affect the frequency and severity of already-deadly hurr Read more…
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.
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.
QCT worked with Intel to develop the QCT QoolRack, a rack-level direct-to-chip cooling solution which meets data center needs with impressive cooling power savings per rack over air cooled solutions, and reduces data centers’ carbon footprint with QCT QoolRack smart management.
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