AI

Cray Sharpens Approach to Large-Scale Graph Analytics

For those in enterprise circles who still conjure black and white images of hulking supercomputers when they hear the name “Cray,” it is worth noting that the long-standing company has done a rather successful job of shifting a critical side of its business to graph analytics and large-scale data processing.

AI

Future Cray Clusters to Storm Deep Learning

Supercomputer maker Cray might not roll out machines for deep learning anytime in 2016, but like other system vendors with deep roots in high performance computing, which leverages many of the same hardware elements (strong interconnect and GPU acceleration, among others), they are seeing how to loop their expertise into a future where machine learning rules.

AI

National Lab Pushes Graph Platforms to New Points

While graph analytics is not a likely replacement for the standard relational databases that many companies will stick with for many years to come, the value of graphs for a particular set of knowledge discovery applications has become clearer with a widening set of use cases in areas ranging from security, fraud detection, medical research, financial services, and a number of other segments.

Compute

Inside Future “Knights Landing” Xeon Phi Systems

Without any new plain vanilla processors from Intel, IBM, Fujitsu, AMD, or the relative handful of ARM server chip makers, and with Nvidia launching its Tesla M4 and M40 accelerators aimed at hyperscalers and those looking for cheap single-precision flops ahead of SC15, the “Knights Landing” Xeon Phi chip was pretty much the star of the high performance conference as far as compute is concerned.