October 5, 2022
For the better part of a century, General Motors (GM) was the biggest automaker in the world. Now, amid a paradigm shift toward smarter, electrified vehicles, t Read more…
September 28, 2016
Pairing ferroelectric and ferrimagnetic materials so that their alignment can be controlled with a small electric field at near room temperatures has long been Read more…
April 2, 2015
Intel recently published a case study that demonstrates the advantages of the Intel Xeon E5-2600 v3 product family for running engineering workloads, using Read more…
January 8, 2015
The high-stakes global market place with its razor-thin margins has been a boon for innovative solutions and technologies, like high-performance computing, whic Read more…
February 26, 2014
When one thinks of major manufacturing companies, including Boeing, Proctor and Gamble, John Deere, Caterpillar, Dow, GE and others, from a systems and software 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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