While we all spend a lot of time talking about the massive supercomputers that cultivate new architectures, and precisely for that reason, it is the more modest cluster that makes use of these technologies many years hence that actually cultivates a healthy and vibrant HPC market. …
SGI has always had scalable technology that should have been deployed more broadly in the academic, government, and enterprise datacenters of the world. …
Over the last year in particular, we have documented the merger between high performance computing and deep learning and its various shared hardware and software ties. …
The ultimate success of any platform depends on the seamless integration of diverse components into a synergistic whole – well, as much as is possible in the real world – while at the same time being flexible enough to allow for components to be swapped out and replaced by others to suit personal preferences. …
At the annual Supercomputing Conference (SC16) last week, the emphasis was on deep learning and its future role as part of supercomputing applications and systems. …
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. …
The future “Summit” pre-exascale supercomputer that is being built out in late 2017 and early 2018 for the US Department of Energy for its Oak Ridge National Laboratory looks like a giant cluster of systems that might be used for training neural networks. …
It is hard to tell which part of the HPC market is more competitive: compute, networking, or storage. …
Every new hardware device that offers some kind of benefit compared to legacy devices faces the task of overcoming the immense inertia that is imparted to a platform by the software that runs upon it. …
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