More than five years ago, Nvidia, driven by its co-founder and CEO, Jensen Huang, turned its considerable focus to developing technologies for the revitalized and burgeoning artificial intelligence space. …
When it comes to machine learning, a lot of the attention in the past six years has focused on the training of neural networks and how the GPU accelerator radically improved the accuracy of networks, thanks to its large memory bandwidth and parallel compute capacity relative to CPUs. …
A research team from Nvidia has provided interesting insight about using mixed precision on deep learning training across very large training sets and how performance and scalability are affected by working with a batch size of 32,000 using recurrent neural networks. …
The Barcelona Supercomputing Center is one of the flagship HPC facilities in Europe and it arguably has the most elegant and spiritual of datacenters in the world, located inside of Torre Girona Chapel. …
With Intel having significant difficulties in ramping up its 10 nanometer manufacturing processes and not really talking much about its plans for 7 nanometers, there has never been a better time for its few remaining rivals in chip manufacturing to give their respective CPU and GPU customers and edge to carve out some market share in the datacenter and on the desktop, which helps cover the cost of being in the datacenter because it helps ramp advanced processes. …
Nvidia got a little taste of hardware, and the company’s top brass have decided that they like having a lot of iron in their financial diet. …
Even if Nvidia had not pursued a GPU compute strategy in the datacenter a decade and a half ago, the company would have turned in one of the best periods in its history as the first quarter of fiscal 2019 came to a close on April 29. …
At the GPU Technology Conference last week, we told you all about the new NVSwitch memory fabric interconnect that Nvidia has created to link multiple “Volta” GPUs together and that is at the heart of the DGX-2 system that the company has created to demonstrate its capabilities and to use on its internal Saturn V supercomputer at some point in the future. …
When Nvidia co-founder and chief executive officer Jensen Huang told the assembled multitudes at the keynote opening to the GPU Technology Conference that the new DGX-2 system, weighing in at 2 petaflops at half precision using the latest Tesla GPU accelerators, would cost $1.5 million when it became available in the third quarter, the audience paused for a few seconds, doing the human-speed math to try to reckon how that stacked up to the DGX-1 servers sporting eight Teslas. …
It has happened time and time again in computing in the past three decades in the datacenter: A device scales up its capacity – be it compute, storage, or networking – as high as it can go, and then it has to go parallel and scale out. …
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