Getting AI Leverage With GPU-Optimized Systems
The artificial intelligence revolution is quickly changing every industry, and modern data centers must be equipped to capitalize on these extraordinary new capabilities. …
The artificial intelligence revolution is quickly changing every industry, and modern data centers must be equipped to capitalize on these extraordinary new capabilities. …
Researchers at Volkswagen have been at the cutting edge of implementing D-Wave quantum computers for a number of complex optimization problems, including traffic flow optimization, among other potential use cases. …
The hyperscalers of the world have to deal with dataset sizes – both streaming and at rest – and real-time processing requirements that put them into an entirely different class of computing. …
The first step in rolling out a massive supercomputer installed at a government sponsored HPC laboratory is to figure out when you want to get it installed and doing useful work. …
If you are running applications in the HPC or AI realms, you might be in for some sticker shock when you shop for GPU accelerators – thanks in part to the growing demand of Nvidia’s Tesla cards in those markets but also because cryptocurrency miners who can’t afford to etch their own ASICs are creating a huge demand for the company’s top-end GPUs. …
Details about the technologies being used in Canada’s newest and most powerful research supercomputer have been coming out in a piecemeal fashion over the past several months, but now the complete story. …
The general consensus, for as long as anyone can remember, is that there is an insatiable appetite for compute in the datacenter. …
Since its inception, the OpenStack cloud controller co-created by NASA and Rackspace Hosting, with these respective organizations supplying the core Nova compute and Swift object storage foundations, has been focused on the datacenter. …
The rapid proliferation of connected devices and the huge amounts of data they are generating is forcing tech vendors and enterprises alike to cast their eyes to the network edge, which has become a focus of the distributed computing movement as more compute, storage, network, analytics and other resources are moving closer to where these devices live. …
There is no question right now that if you have a big computing job in either high performance computing – the colloquial name for traditional massively parallel simulation and modeling applications – or in machine learning – the set of statistical analysis routines with feedback loops that can do identification and transformation tasks that used to be solely the realm of humans – then an Nvidia GPU accelerator is the engine of choice to run that work at the best efficiency. …
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