In this video, SGI’s Dr. Eng Lim Goh presents the company’s plans to use the Intel MIC architecture on the road to Exascale computing by 2018. Recorded at the Intel Exascale briefing at ISC’11 in Hamburg on June 20, 2011.
Industry Perspectives
Podcast: Deep Learning for Scientific Data Analysis
In this NERSC News Podcast, Debbie Bard from NERSC describes how Deep Learning can help scientists accelerate their research. "Deep learning is enjoying unprecedented success in a variety of commercial applications, but it is also beginning to find its footing in science. Just a decade ago, few practitioners could have predicted that deep learning-powered systems would surpass human-level performance in computer vision and speech recognition tasks." [Read More...]
White Papers
Parallel File System Delivers Better Strategies, Faster
A parallel file system offers several advantages over a single direct attached file system. By using fast, scalable, external disk systems with massively parallel access to data, researchers can perform analysis against much larger datasets than they can by batching large datasets through memory. To Learn More about the Parallel File Systems download this guide
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