November 16, 2022
For a few moments, the atmosphere was more Rock Concert than Supercomputing Conference with many members of a packed audience standing, cheering, and waving signs as Jack Dongarra took the stage to deliver the annual ACM Turing Award lecture at SC22. Read more…
July 15, 2022
The direction that exascale supercomputing will need to follow and the continuing value of visual and other non-computational experts in computer visualizations were the focus of the final two plenary sessions at the PEARC22 conference in Boston on July 13. Jack Dongarra, director of research staff and professor at the Oak Ridge National Laboratory and the University of Tennessee, Knoxville... Read more…
June 16, 2016
Jack Dongarra, one of today’s most distinguished HPC leaders, is adding two awards to his long list. The Association for Computer Machinery (ACM) recently honored Dongarra with the High Performance Parallel and Distributed Computing Achievement Award at the annual High Performance and Distributed Computing Conference in Kyoto, Japan, while the Institute of Electrical and Electronics Engineers (IEEE) will bestow him with the Super Computing (SC) 2016 Test of Time Award at its conference in November. 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.
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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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