Google scientists Jeff Dean and Amin Vahdat delivered a fascinating tour of major ML hardware and software design trends in their joint Hot Chips 23 opening keynote this week. The pair tackled …
The first numbers of the available bandwidth between chiplets is out – UCIe is estimating that chiplet packages could squeeze out communication speeds of 630Gbps, or 0.63Tbps, in a very tight a …
Check out our list of 108 illustrious winners across 22 different categories of HPC.
June 3, 2023
Researchers are leveraging photonics to develop and scale the hardware necessary to tackle the stringent requirements of quantum information technologies. By ex Read more…
April 19, 2023
Researchers at Meta, MIT and other institutions connected servers with a dozen Nvidia GPUs with optical switches and a robotic arm, devising a new interconnect Read more…
April 10, 2023
There are limits on the speed of how fast copper wires can move data between computers, and a transition to light speed will ultimately drive AI and high-performance computing forward. Every major chipmaker is in agreement that optical interconnects will be needed to reach zettascale computing in an energy-efficient way. That opinion was... Read more…
March 6, 2023
While quantum computing makes its way haphazardly towards practical realty, quantum key distribution (QKD) is moving quickly towards greater commercial use. Tod Read more…
March 1, 2023
Ayar Labs, founded in 2015, is pursuing optics as a means of driving higher interconnect speeds and efficiencies in computing. Now, the company is announcing th Read more…
October 18, 2022
Spun out from Google last March, SandboxAQ is a fascinating, well-funded start-up targeting the intersection of AI and quantum technology. “As the world enter Read more…
October 11, 2022
The launch of ESnet6 was announced at an event at Berkeley Lab this morning. ESnet – short for “energy sciences network” – is managed by Berkeley Lab, f Read more…
October 6, 2022
In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programmin 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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