January 25, 2021
In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programmin Read more…
November 20, 2020
A new record for HPC scaling on the public cloud has been achieved on Microsoft Azure. Led by Dr. Jer-Ming Chia, the cloud provider partnered with the Beckman I Read more…
April 24, 2019
Panels tend to be among the livelier conference sessions and the “Containers” panel at Tabor’s Advanced Scale Forum last week in Jacksonville, Fla., was c Read more…
August 3, 2016
The Message Passing Interface (MPI) is the standard definition of a communication API that has underpinned traditional HPC for decades. The message passing programming represents distributed-memory hardware architectures using processes that send messages to each other. When first standardised in 1993-4, MPI was a major step forward from the many proprietary, system-dependent, and semantically different message-passing libraries that came before it. Read more…
May 16, 2016
Nielsen has collaborated with Intel to migrate important pieces of HPC technology into Nielsen’s big-data analytic workflows including MPI, mature numerical libraries from NAG (the Numerical Algorithms Group), as well as custom C++ analytic codes. This complementary hybrid approach integrates the benefits of Hadoop data management and workflow scheduling with an extensive pool of HPC tools and C/C++ capabilities for analytic applications. In particular, the use of MPI reduces latency, permits reuse of the Hadoop servers, and co-locates the MPI applications close to the data. Read more…
March 30, 2016
The need for extreme scale computing is driven by the seemingly forever fledgling Internet. In abstract, the entire network is already an extreme scale computin 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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