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. …
Increasing parallelism is the only way to get more work out of a system. …
The hyperscalers of the world are increasingly dependent on machine learning algorithms for providing a significant part of the user experience and operations of their massive applications, so it is not much of a surprise that they are also pushing the envelope on machine learning frameworks and systems that are used to deploy those frameworks. …
Google has always been a company that thinks big. After all, its mission since Day One was to organize and make accessible all of the world’s information. …
The rumors have been running around for years, and they turned out to be true. …
If you want real competition among vendors who supply stuff to you, then sometimes you have to make it happen by yourself. …
Ever so slowly, and not so fast as to give competitor Intel too much information about what it is up to, but just fast enough to build interest in the years of engineering smarts that has gone into its forthcoming “Naples” X86 server processor, AMD is lifting the veil on the product that will bring it back into the datacenter and that will bring direct competition to the Xeon platform that dominates modern computing infrastructure. …
There are not a lot of second chances in the IT racket. …
The Global Scientific Information and Computing Center at the Tokyo Institute of Technology has been at the forefront of accelerated computing, and well before GPUs came along and made acceleration not only cool but affordable and normal. …
We spend a lot of time contemplating what technologies will be deployed at the heart of servers, storage, and networks and thereby form the foundation of the next successive generations of platforms in the datacenter for running applications old and new. …
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