Top 5 Trends in HPC for the First Six Months of 2023  

July 12, 2023

Editor’s note; In light of recent updates to  Google’s Privacy Policy, “For example, we use publicly available information to help train Google’s AI mo Read more…

HPE Launches ML Development System, Swarm Learning Solution

April 27, 2022

In a one-two punch of new HPC-backed AI announcements, Hewlett Packard Enterprise (HPE) today announced its new Machine Learning Development System (MLDS) and S Read more…

White House Scientific Integrity Report Addresses AI and ML Ethics

January 26, 2022

Earlier this month, the White House Office of Science and Technology Policy (OSTP) Scientific Integrity Task Force released a report titled “Protecting the In Read more…

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MosaicML, Led by Naveen Rao, Comes Out of Stealth Aiming to Ease Model Training

October 15, 2021

With more and more enterprises turning to AI for a myriad of tasks, companies quickly find out that training AI models is expensive, difficult and time-consuming. Finding a new approach to deal with those cascading challenges is the aim of a new startup, MosaicML, that just came out of stealth... Read more…

Purdue Researchers Peer into the ‘Fog of the Machine Learning Accelerator War’

September 27, 2021

Making sense of ML performance and benchmark data is an ongoing challenge. In light of last week’s release of the most recent MLPerf (v1.1) inference results, now is perhaps a good time to review how valuable (or not) such ML benchmarks are and the challenges they face. Two researchers... Read more…

EPFL Researchers Leverage Optics to Advance Efficient, ‘Supercomputer-Level’ Machine Learning

September 3, 2021

As datasets get larger and larger, the potential of machine learning insights from those datasets grows correspondingly immense – but bottlenecks in computing Read more…

Esperanto, Silicon in Hand, Champions the Efficiency of Its 1,092-Core RISC-V Chip

August 27, 2021

Esperanto Technologies made waves last December when it announced ET-SoC-1, a new RISC-V-based chip aimed at machine learning that packed nearly 1,100 cores onto a package small enough to fit six times over on a single PCIe card. Now, Esperanto is back, silicon in-hand and taking aim... Read more…

HLRS to Advance Custom Automation Through AI

August 7, 2021

For nearly a hundred years, German-based firm Festo has delivered industrial controls and automation tools to its clients, growing to over 20,000 employees and Read more…

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Whitepaper

How Direct Liquid Cooling Improves Data Center Energy Efficiency

Data centers are experiencing increasing power consumption, space constraints and cooling demands due to the unprecedented computing power required by today’s chips and servers. HVAC cooling systems consume approximately 40% of a data center’s electricity. These systems traditionally use air conditioning, air handling and fans to cool the data center facility and IT equipment, ultimately resulting in high energy consumption and high carbon emissions. Data centers are moving to direct liquid cooled (DLC) systems to improve cooling efficiency thus lowering their PUE, operating expenses (OPEX) and carbon footprint.

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Whitepaper

Transforming Industrial and Automotive Manufacturing

Divergent Technologies developed a digital production system that can revolutionize automotive and industrial scale manufacturing. Divergent uses new manufacturing solutions and their Divergent Adaptive Production System (DAPS™) software to make vehicle manufacturing more efficient, less costly and decrease manufacturing waste by replacing existing design and production processes.

Divergent initially used on-premises workstations to run HPC simulations but faced challenges because their workstations could not achieve fast enough simulation times. Divergent also needed to free staff from managing the HPC system, CAE integration and IT update tasks.

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Sponsored by TotalCAE

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