Graph Databases 101

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Let’s talk about graph databases. Some industry watchers claim that they are the fastest-growing type of database. If so, maybe it’s useful to know more about them. Starting with the basics: What is a graph database, and what is it useful for? Here’s the short answer. Graph databases store data in vertices and edges versus tables, as found in relational databases. They are the most efficient way of looking for relationships between data items, patterns of relationships or interactions between multiple data items, while traditional relational database shine at queries looking for information about some item, or sums or averages of many items of the same type of information. Now let’s review what a graph database isn’t. The standard ... [ Read More ]

5 Predictions of Where Supercomputing is Heading in 2016

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From new processor technologies to quantum computing, 2016 promises to be another exciting year for supercomputing. Here are five predictions as to how the industry will push ahead in 2016:    The year of progress in new processor technologies There are a number of exciting technologies we should see in 2016, and a leader will be Intel’s next-generation Xeon Phi coprocessor – a hybrid between an accelerator and general purpose processor. This new class of processors will have a large impact on the industry with its innovative design that combines a many-core architecture with general-purpose productivity. Cray, for example, will be delivering Intel Xeon Phi processors with some of our largest systems, including those going to Los ... [ Read More ]

Top 5 Blog Posts From 2015

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Happy New Year! Check out some of the top blog posts from 2015: Why Do Better Forecasts Matter? Meteorologists have been striving to increase the accuracy of their work since the first weather forecasts were issued in the mid-19th century by pioneers such as Robert FitzRoy. In the 1950s and 1960s, the development of computers and observational technologies enabled forecast generation using the numerical weather prediction theories of Vilhelm Bjerknes and Lewis Fry Richardson. Today the numerical models that support our weather and climate forecasts are true “grand challenge” problems, requiring on the order of 10,000 billion (1016) mathematical operations and the exchange of 150 billion (1.5 x 1014) bytes of information to generate a ... [ Read More ]

Alan Turing Institute Will Lead Research in Data Science

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Cray is partnering with the Alan Turing Institute, the new U.K. data science research organization in London, to help the U.K. as it increases research in data science to benefit research and industry. Earlier this month Fiona Burgess, U.K. senior account manager, and I attended the launch of the institute. At the event, U.K. Minister for Science and Universities Jo Johnson paid tribute to Turing and his work. Institute director Professor Andrew Blake told the audience that the Turing Institute is about much more than just big data – it is about data science, analysing that data and gaining a new understanding that leads to decisions and actions. Alan Turing was a pioneering British computer scientist. He has become a household name ... [ Read More ]

Can We Make Petabytes Useful?

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A recent article in Nature, “The Power of Petabytes”, by Michael Eisenstein, reviews how exponentially increasing life science data exceeds our present abilities to process and make sense of it. Even while continuing to grow unbounded, data sets are still often not yet large enough to draw convincing conclusions. Computation is one obvious problem. “The computation scales linearly with respect to the number of people,” says Marylyn Ritchie, a genomics researcher at Pennsylvania State University in State College. “But as you add more variables, it becomes exponential as you start to look at different combinations.” To efficiently harness growing computing resources, researchers will need to leverage scalable algorithmic approaches and ... [ Read More ]