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. …
GPU computing has deep roots in supercomputing, but Nvidia is using that springboard to dive head first into the future of deep learning. …
There is increasing interplay between the worlds of machine learning and high performance computing (HPC). …
It is one thing to scale a neural network on a single GPU or even a single system with four or eight GPUs. …
If the name Kwabena Boahen sounds familiar, you might remember silicon that emerged in the late 1990s that emulated the human retina. …
One way to characterize the challenges of achieving exascale, is to look at how advancing compute, memory/storage, software, and fabric will lead to a future-generation balanced system. …
It has just been announced that there has been a shift in thinking among the exascale computing leads in the U.S. …
The race toward exascale supercomputing gets a lot of attention, as it should. …
Moore’s Law may be slowing down performance increases in compute capacity, but InfiniBand networking did not get the memo. …
In many ways, enterprises and hyperscalers have it easy. Very quickly in the wake of its announcement more than two decades ago, the Java programming language, a kind of virtualized C++, became the de facto standard for coding enterprise applications that run the business. …
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