IBM Highlights PowerAI, OpenPower System Scalability
The golden grail of deep learning has two handles. On the one hand, developing and scaling systems that can train ever-growing model sizes is one concern. …
The golden grail of deep learning has two handles. On the one hand, developing and scaling systems that can train ever-growing model sizes is one concern. …
Ziyang Xu from Peking University in Beijing sees several similarities between the human brain and Von Neumann computing devices. …
Supercomputing, by definition, is an esoteric, exotic, and relatively small slice of the overall IT landscape, but it is, also by definition, a vital driver of innovation within IT and in all of the segments of the market where simulation, modeling, and now machine learning are used to provide goods and services. …
Based on datacenter practices of the past two decades, it is a matter of faith that it is always better to run a large number of applications on a given set of generic infrastructure than it is to have highly tuned machines running specific workloads. …
The last couple of years has seen a steady drumbeat for the use of low precision in growing numbers of workloads driven in large part by the rise of machine learning and deep learning applications and the ongoing desire to cut back on the amount of power consumed. …
Supercomputing centers around the world are preparing their next generation architectural approaches for the insertion of AI into scientific workflows. …
Just by being the chief architect of the IBM’s BlueGene massively parallel supercomputer, which was built as part of a protein folding simulation grand challenge effort undertaken by IBM in the late 1990s, Al Gara would be someone whom the HPC community would listen to whenever he spoke. …
The novel architectures story is still shaping out for 2017 when it comes machine learning, hyperscale, supercomputing and other areas. …
There are plenty of things that the members of the high performance community do not agree on, there is a growing consensus that machine learning applications will at least in some way be part of the workflow at HPC centers that do traditional simulation and modeling. …
While AMD voluntarily exited the server processor arena in the wake of Intel’s onslaught with the “Nehalem” Xeon processors during the Great Recession, it never stopped innovating with its graphics processors and it kept enough of a hand in smaller processors used in consumer and selected embedded devices to start making money again in PCs and to take the game console business away from IBM’s Power chip division. …
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