Nvidia Bolsters Omniverse for HPC, Announces NOAA-Lockheed Partnership

November 14, 2022

Over the past months, Nvidia has put a spotlight on its OVX hardware – purpose-built systems aimed at its Omniverse digital twins platform. Now, at SC22, Nvid Read more…

Eyeing Nvidia’s Omniverse for Fusion Reactor Design

March 25, 2022

With climate change accelerating and fossil fuel supplies proving increasingly contentious, ensuring a secure supply of clean energy is top-of-mind for many res Read more…

How [email protected] Identified (and Visualized) SARS-CoV-2’s Weak Spots

October 14, 2020

[email protected]’s crowdsourced network of volunteer computers has boomed during the pandemic, now comprising some one million citizen scientists who regularly do Read more…

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Whitepaper

A New Standard in CAE Solutions for Manufacturing

Today, manufacturers of all sizes face many challenges. Not only do they need to deliver complex products quickly, they must do so with limited resources while continuously innovating and improving product quality. With the use of computer-aided engineering (CAE), engineers can design and test ideas for new products without having to physically build many expensive prototypes. This helps lower costs, enhance productivity, improve quality, and reduce time to market.

As the scale and scope of CAE grows, manufacturers need reliable partners with deep HPC and manufacturing expertise. Together with AMD, HPE provides a comprehensive portfolio of high performance systems and software, high value services, and an outstanding ecosystem of performance optimized CAE applications to help manufacturing customers reduce costs and improve quality, productivity, and time to market.

Read this whitepaper to learn how HPE and AMD set a new standard in CAE solutions for manufacturing and can help your organization optimize performance.

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Sponsored by HPE

Whitepaper

Porting CUDA Applications to Run on AMD GPUs

A workload-driven system capable of running HPC/AI workloads is more important than ever. Organizations face many challenges when building a system capable of running HPC and AI workloads. There are also many complexities in system design and integration. Building a workload driven solution requires expertise and domain knowledge that organizational staff may not possess.

This paper describes how Quanta Cloud Technology (QCT), a long-time Intel® partner, developed the Taiwania 2 and Taiwania 3 supercomputers to meet the research needs of the Taiwan’s academic, industrial, and enterprise users. The Taiwan National Center for High-Performance Computing (NCHC) selected QCT for their expertise in building HPC/AI supercomputers and providing worldwide end-to-end support for solutions from system design, through integration, benchmarking and installation for end users and system integrators to ensure customer success.

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Sponsored by AMD

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