It is not news that offloading work from CPUs to GPUs can grant radical speedups, but what can come as a surprise is that scaling of these workloads doesn’t change just because they run faster. …
Todd Mostak, the creator of the MapD GPU-accelerated database and visualization system, made that database because he was a frustrated user of other database technologies, and as a user, he is adamant that accelerating databases and making visualization of queried data is about more than just being a speed freak. …
When it comes to deep learning innovation on the hardware front, few other research centers have been as forthcoming with their results as Baidu. …
What is good for the simulation and the machine learning is, as it turns out, also good for the database. …
Last week we described the next stage of deep learning hardware developments in some detail, focusing on a few specific architectures that capture what the rapidly-evolving field of machine learning algorithms require. …
No one knows for sure how pervasive deep learning and artificial intelligence are in the aggregate across all of the datacenters in the world, but what we do know is that the use of these techniques is growing and could represent a big chunk of the processing that gets done every millisecond of every day. …
We have heard about a great number of new architectures and approaches to scalable and efficient deep learning processing that sit outside of the standard CPU, GPU, and FPGA box and while each is different, many are leveraging a common element at all-important memory layer. …
Over the long course of IT history, the burden has been on the software side to keep pace with rapid hardware advances—to exploit new capabilities and boldly go where no benchmarks have gone before. …
Intel has planted some solid stakes in the ground for the future of deep learning over the last month with its acquisition of deep learning chip startup, Nervana Systems, and most recently, mobile and embedded machine learning company, Movidius. …
There is no workload in the datacenter that can’t, in theory and in practice, be supplied as a service from a public cloud. …
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