Exascale Supercomputers Signal a New Era

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The road to exascale computing started out as a journey. Now, we find ourselves at the beginning of a new era. Last week Cray and the U.S. Department of Energy (DOE) announced Frontier ― an exascale supercomputer being developed for Oak Ridge National Laboratory (ORNL). Slated for delivery in 2021, Frontier is expected to be the world’s most powerful computer. It will advance science and innovation far beyond anything currently possible. For us at Cray, the announcement of Frontier is a thrilling ― and humbling ― moment. The system is the third contract win for our new Shasta™ architecture and Cray Slingshot™ interconnect. It validates our belief in and commitment to our Shasta technology. But more importantly, ... [ Read More ]

Critical Role of HPC Storage in Autonomous Vehicle Development

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Self-driving cars were once only the stuff of science fiction. But thanks to recent computing advances, they are becoming more of a reality every day. Still, a number of issues need addressing before fully autonomous vehicles share our roadways. And one of the largest is capturing and processing the data generated by fleets of training cars. This massive amount of data creates an unprecedented storage challenge that autonomous vehicle development companies cannot overcome using their existing enterprise storage architectures. Luckily, here at Cray we’ve made it our mission to provide technology that solves the world’s most complex computing challenges, so this problem is right in our wheelhouse. First, a little background. Driving a ... [ Read More ]

How Hyperparameter Optimization Improves Machine Learning Accuracy

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In January, a team of Cray developers and researchers published a paper, “Recombination of Artificial Neural Networks,” on arXiv.org, highlighting the hyperparameter optimization (HPO) capability Cray announced in November. We cover their findings in this blog post. Using a variety of high-performance computing systems and neural network models, the Cray team demonstrated that the hyperparameter optimization capabilities introduced in the Cray® Urika®-CS and Urika®-XC AI and analytics software suites improve the time-to-accuracy as well as final accuracy of machine learning models trained on Cray systems. The table below, excerpted from the paper, highlights the improvements achieved using Cray’s HPO capability across a range of ... [ Read More ]

Your Own Supercomputer — in the Azure Cloud

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Your organization relies on technology for a competitive advantage. You need fast, reliable performance. But high-performance computing can be a big investment, and challenging to manage as part of your IT infrastructure. Cray and Microsoft make it easy — and you get Cray supercomputing in the Microsoft Azure cloud. This convergence of supercomputing capabilities and the ease of cloud management enables disruptive innovation for new categories of companies. It alleviates the management burden and reduces barriers of entry to HPC. Supercomputing is no longer out of reach for smaller enterprises and organizations that can’t or don’t want to maintain their own datacenters. Get details about Cray in the cloud in this white paper by ... [ Read More ]

Cray Graph Engine Takes on a Trillion Triples

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One trillion. That’s quite a large number. It’s 132 times the number of people on Earth; five times the number of tweets posted in a year on Twitter; the number of search engine queries Google serves in five months; and now equivalent to the number of triples we’ve loaded, inferenced and queried using our own Cray Graph Engine. At last week’s Cray User Group (CUG) meeting, a paper submitted by a team of Cray engineers — Chris Rickett, Utz-Uwe Haus, Jim Maltby and Kristi Maschhoff — received the 2018 Best Paper Award for “Loading and Querying a Trillion RDF Triples with Cray Graph Engine on the Cray XC.” I am a marketing guy, so I think of achievements in terms of “first, only or best.” We know Cray isn’t your only option for graph ... [ Read More ]