Scaling Deep Learning on an 18,000 GPU Supercomputer
It is one thing to scale a neural network on a single GPU or even a single system with four or eight GPUs. …
It is one thing to scale a neural network on a single GPU or even a single system with four or eight GPUs. …
China represents a big and growing market opportunity for IT vendors around the world. …
There is little doubt that 2017 will be a dense year for deep learning. …
In Supercomputing Conference (SC) years past, chipmaker Intel has always come forth with a strong story, either as an enabling processor or co-processor force, or more recently, as a prime contractor for a leading-class national lab supercomputer. …
While the world awaits the AMD K12 and Qualcomm Hydra ARM server chips to join the ranks of the Applied Micro X-Gene and Cavium ThunderX processors already in the market, it could be upstart Chinese chip maker Phytium Technology that gets a brawny chip into the field first and also gets traction among actual datacenter server customers, not just tire kickers. …
Over the last couple of years, the idea that the most efficient and high performance way to accelerate deep learning training and inference is with a custom ASIC—something designed to fit the specific needs of modern frameworks. …
If there is anything that chip giant Intel has learned over the past two decades as it has gradually climbed to dominance in processing in the datacenter, it is ironically that one size most definitely does not fit all. …
Following yesterday’s acquisition of deep learning chip startup Nervana Systems by Intel, we talked with the company’s CEO, Naveen Rao, about what plans are for both the forthcoming hardware and internally developed Neon software stack now that the technology is under a much broader umbrella. …
Update – 8/9/16 1:00 p.m. Pacific – Not even 24 hours after this story was posted Intel bought Nervana Systems. …
Although the launch of Pascal stole headlines this year on the GPU computing front, the company’s Tesla K80 GPU, which was launched at the end of 2014, has been finding a home across a broader base of applications and forthcoming systems. …
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