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Some Surprises in the 2018 DoE Budget for Supercomputing
The US Department of Energy fiscal year 2018 budget request is in. …
The US Department of Energy fiscal year 2018 budget request is in. …
GPU computing has deep roots in supercomputing, but Nvidia is using that springboard to dive head first into the future of deep learning. …
Enterprise spending on servers was a bit soft in the first quarter, as evidenced by the financial results posted by Intel and by its sometime rival IBM, but the hyperscale and HPC markets, at least when it comes to networking, was a bit soft, according to high-end network chip and equipment maker Mellanox Technologies. …
Energy efficiency and operating costs for systems are as important as raw performance in today’s datacenters. …
International Business Machines has gone through so many changes in its eleven decades of existence, and it is important to remember that some days. …
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. …
Ethernet switching has its own kinds of Moore’s Law barriers. The transition from 10 Gb/sec to 100 Gb/sec devices over the past decade has been anything but smooth, and a lot of compromises had to be made to even get to the interim – and unusual – 40 Gb/sec stepping stone towards the 100 Gb/sec devices that are ramping today in the datacenter. …
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. …
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