October 28, 2019
Our lives are consumed by small electronics, like smartphones and smartwatches, from which we demand ever more power. The most intricate components of these dev Read more…
September 5, 2019
A years-long mission to build a microprocessor out of carbon nanotube transistors has finally succeeded thanks to a team of MIT researchers. The development comes as the sustainability of Moore’s Law is increasingly called into question. Silicon-based transistors are nearing the point when they will be unable to shrink anymore, delivering increasingly marginal improvements. Read more…
October 1, 2015
Perhaps Moore’s law isn’t doomed just yet. Maybe. IBM Research (NYSE: IBM) reported in a paper in Science today a technique for making carbon nanotube trans Read more…
June 23, 2014
With TOP500 list stagnation likely signaling the slow-down of an exponential known as Moore's law, what better time to consider alternatives to silicon-based m 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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