It is hard to find a more hyperbolic keynote title than, “A New Computing Model” but given the recent explosion in capabilities in both hardware and algorithms that have pushed deep learning to the fore, Nvidia’s CEO keynote at this morning’s GPU Technology Conference kickoff appears to be right on target. …
Well before the Intel acquisition of Altera and the news about Microsoft’s use of the Catapult servers, which feature FPGAs to power their Bing search engine and other key applications, it has been clear that the FPGA future is just starting to unfold. …
When it comes to leveraging existing Hadoop infrastructure to extend what is possible with large volumes of data and various applications, Yahoo is in a unique position–it has the data and just as important, it has the long history with Hadoop, MapReduce and other key tools in the open source big data stack close at hand and manned with seasoned experts. …
Whether in the brain or in code, neural networks are shaping up to be one of the most critical areas of research in both neuroscience and computer science. …
If the last year of stories here from research labs at the forefront of deep learning hasn’t made it clear, the accelerator of choice for training the models that will feed the next generation of speech and image recognition (not to mention a wealth of other application areas) is certainly GPUs. …
While many consumers in the U.S. might not have heard much about Baidu, when it comes to engineers and computer scientists, the Chinese company is on par with Google, Facebook, and their ilk when it comes to massively scaled distributed computing. …
Stanford University PhD candidate, Song Han, who works under advisor and networking pioneer, Dr. …
For Google, Baidu, and a handful of other hyperscale companies that have been working with deep neural networks and advanced applications for machine learning well ahead of the rest of the world, building clusters for both the training and inference portions of such workloads is kept, for the most part, a well-guarded secret. …
The future of hyperscale datacenter workloads is becoming clearer and as that picture emerges, if one thing is clear, it is that the content is heavily driven by a wealth of non-text content—much of it streamed in for processing and analysis from an ever-growing number of users of gaming, social network, and other web-based services. …
For more than a decade, graphics processor maker Nvidia has been championing the adoption of GPU accelerators as heavy-lifting compute engines for an increasing array of applications that can take advantage of the parallel processing inherent in a GPU. …
All Content Copyright The Next Platform