One of Germany’s foremost scientific research centers, Jülich Forschungszentrum, will receive a €36-million infusion of government funding to advance quantum and neuromorphic computing technologies. …
We did not plan it, but today has become make-your-eyes-bleed-with-chip architecture-patent-applications day. …
Over the last several years we have seen many new hardware architectures emerge for deep learning training but this year, inference will have its turn in the spotlight. …
There are several competing processor efforts targeting deep learning training and inference but even for these specialized devices, the old performance ghosts found in other areas haunt machine learning as well. …
Ziyang Xu from Peking University in Beijing sees several similarities between the human brain and Von Neumann computing devices. …
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. …
It is difficult to shed a tear for Moore’s Law when there are so many interesting architectural distractions on the systems horizon. …
If the name Kwabena Boahen sounds familiar, you might remember silicon that emerged in the late 1990s that emulated the human retina. …
Much of the talk around artificial intelligence these days focuses on software efforts – various algorithms and neural networks – and such hardware devices as custom ASICs for those neural networks and chips like GPUs and FPGAs that can help the development of reprogrammable systems. …
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