Trust Me, I’m Smart: HPC and Government Regulation in the Coming AI Age

January 17, 2024

Stephen Hawking famously said that "success in creating effective AI could be the biggest event in the history of our civilization, but unless we learn how to p Read more…

MLPerf Ascends as DAWNBench is Phased Out

January 31, 2020

As the MLPerf benchmark emerges as an industry standard for measuring the performance of machine learning models, its creators said they will phase out the foundational DAWNBench metric. Stanford University researchers announced earlier this month they will end rolling submissions—that is, finished sections of a model... Read more…

Stanford University and UberCloud Achieve Breakthrough in Living Heart Simulations

September 21, 2017

Cardiac arrhythmia can be an undesirable and potentially lethal side effect of drugs. During this condition, the electrical activity of the heart turns chaotic, Read more…

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

Stanford Researchers Tackle Cardiac Arrhythmia Detection with Machine Learning

July 12, 2017

Using machine learning techniques Stanford University researchers reported developing an algorithm for identifying cardiac arrhythmias that performs as well or Read more…

Sony Removes Folding@home Service from PS3

October 22, 2012

After a successful five-year run, Sony is ending its participation with Stanford University's Folding@home project. Read more…

A Dark Matter for Astrophysics Research

May 31, 2011

Projects like the Sloan Digital Sky Survey have provided a wealth of cosmological data for scientists to explore in detail. However, making use of those terabytes -- and generating far more data in the process of simulating and analyzing new concepts -- is highlighting the bottlenecks for scientific computing at massive scale. 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.

This paper describes how CoolIT Systems (CoolIT) meets the need for improved energy efficiency in data centers and includes case studies that show how CoolIT’s DLC solutions improve energy efficiency, increase rack density, lower OPEX, and enable sustainability programs. CoolIT is the global market and innovation leader in scalable DLC solutions for the world’s most demanding computing environments. CoolIT’s end-to-end solutions meet the rising demand in cooling and the rising demand for energy efficiency.

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Sponsored by CoolIT

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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