Kristen Perez – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-18T18:06:24Z http://www.open-lab.net/blog/feed/ Kristen Perez <![CDATA[New Video: Pioneering Climate Tech and Mitigating the Impact of Natural Disasters]]> http://www.open-lab.net/blog/?p=78716 2024-05-07T17:51:53Z 2024-03-05T19:17:25Z In 2022, the city of Lismore, Australia bore the brunt of devastating floods, leaving over 3K homes damaged and communities shattered. With $6B in losses, this...]]>

In 2022, the city of Lismore, Australia bore the brunt of devastating floods, leaving over 3K homes damaged and communities shattered. With $6B in losses, this was the second-costliest event in the world for insurers in 2022 and the most expensive disaster in Australian history. With each passing year, natural disaster events such as those experienced in Lismore grow in rate and scale across…

Source

]]>
Kristen Perez <![CDATA[Strategies for Maximizing Data Center Energy Efficiency]]> http://www.open-lab.net/blog/?p=65020 2023-06-09T20:25:50Z 2023-05-23T15:00:00Z Data centers are an essential part of a modern enterprise, but they come with a hefty energy cost. To complicate matters, energy costs are rising and the need...]]>

Data centers are an essential part of a modern enterprise, but they come with a hefty energy cost. To complicate matters, energy costs are rising and the need for data centers continues to expand, with a market size projected to grow 25% from 2023 to 2030. Globally, energy costs are already negatively affecting data centers and high-performance computing (HPC) systems. To alleviate the energy…

Source

]]>
0
Kristen Perez <![CDATA[Physics-Informed Machine Learning Platform NVIDIA PhysicsNeMo Is Now Open Source]]> http://www.open-lab.net/blog/?p=62168 2025-03-18T18:06:24Z 2023-03-23T16:00:00Z Physics-informed machine learning (physics-ML) is transforming high-performance computing (HPC) simulation workflows across disciplines, including computational...]]>

Physics-informed machine learning (physics-ML) is transforming high-performance computing (HPC) simulation workflows across disciplines, including computational fluid dynamics, structural mechanics, and computational chemistry. Because of its broad applications, physics-ML is well suited for modeling physical systems and deploying digital twins across industries ranging from manufacturing to…

Source

]]>
0
���˳���97caoporen����