Docker Completes Its Platform With DIY Linux
It all started with a new twist on an old idea, that of a lightweight software container running inside Linux that would house applications and make them portable. …
It all started with a new twist on an old idea, that of a lightweight software container running inside Linux that would house applications and make them portable. …
Scaling the performance of machine learning frameworks so they can train larger neural networks – or so the same training a lot faster – has meant that the hyperscalers of the world who are essentially creating this technology have had to rely on increasingly beefy compute nodes, these days almost universally augmented with GPUs. …
So you are a system architect, and you want to make the databases behind your applications run a lot faster. …
The fields where machine learning and neural networks can have positive impacts seem almost limitless. …
Intel might have its own thoughts about the trajectory of Moore’s Law, but many leaders in the industry have views that variate slightly from the tick-tock we keep hearing about. …
Google created quite a stir when it released architectural details and performance metrics for its homegrown Tensor Processing Unit (TPU) accelerator for machine learning algorithms last week. …
If you can’t beat the largest cloud players at economies of scale, the only option is to try to outrun them in performance, capabilities, or price. …
If you want an object lesson in the interplay between Moore’s Law, Dennard scaling, and the desire to make money from selling chips, you need look no further than the past several years of Intel’s Xeon E3 server chip product lines. …
While a lot of the applications in the world run on clusters of systems with a relatively modest amount of compute and memory compared to NUMA shared memory systems, big iron persists and large enterprises want to buy it. …
Four years ago, Google started to see the real potential for deploying neural networks to support a large number of new services. …
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