October 17, 2022
Oregon State University (OSU) is planning to launch an expansive, expensive – $200 million – new research and education center. The center will be named aft Read more…
April 12, 2021
Nvidia Corp. continues to expand its Clara healthcare platform with the addition of computational drug discovery and medical imaging tools based on its DGX A100 platform, related InfiniBand networking and its AGX developer kit. The Clara partnerships announced during... Read more…
April 12, 2021
Join HPCwire right here on Monday, April 12, at 8:30 am PT to see the Nvidia GTC21 keynote from Nvidia’s CEO, Jensen Huang, livestreamed in its entirety. Hosted by HPCwire, you can click to join the Huang keynote on our livestream to hear Nvidia’s expected news and... Read more…
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.
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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