February 8, 2017
UMass today rolled out its new GPU cluster – Gypsum – aimed at deep learning. Like many institutions, UMass is seeking to attract Ph.D. students drawn to deep learning and artificial intelligence. At 400 GPUs, Gypsum is on the large side for academic GPU clusters according the university. Read more…
December 6, 2012
Today's notion of safe passwords may soon be a thing of the past. Thanks to cheaper hardware, cloud software, and free password cracking programs, it's easier than ever to hack these digital keys. Just how easy? Earlier this week, a custom-built GPU cluster tore through 348 billion password hashes per second during the Passwords^12 Conference in Oslo, Norway. Read more…
July 26, 2010
This morning NVIDIA and its hosting partner PEER 1 announced that they would be delivering the industry's first large-scale hosted GPU cloud, which means, among other things, that the popular RealityServer platform might be able to infiltrate more user groups due to the shedding of GPU cluster requirements. Read more…
Data growth is relentless and inevitable, as data has come to define many aspects of research computing. Simulation data, ever more sophisticated sensor data, and now the rise of machine learning all contribute to the accelerating pace of data growth.
Learn how archive is different than backup, how much data should be archived, and how to architect a comprehensive HSM solution using new data management technologies that can handle this accelerating growth today and well into the future.
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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