High Times for Low-Precision Hardware
Processor makers are pushing down the precision for a range of new and forthcoming devices, driven by a need that balances accuracy with energy-efficient performance for an emerging set of workloads. …
Processor makers are pushing down the precision for a range of new and forthcoming devices, driven by a need that balances accuracy with energy-efficient performance for an emerging set of workloads. …
The need for speed to process neural networks is far less a matter of processor capabilities and much more a function of memory bandwidth. …
Over the last two years, there has been a push for novel architectures to feed the needs of machine learning and more specifically, deep neural networks. …
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 computing industry is facing a number of challenges as Moore’s Law improvements in circuitry slow down, and they don’t all have to do with transistor counts and memory bandwidth and such. …
When it comes to deep learning innovation on the hardware front, few other research centers have been as forthcoming with their results as Baidu. …
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. …
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. …
Over the last couple of years, the idea that the most efficient and high performance way to accelerate deep learning training and inference is with a custom ASIC—something designed to fit the specific needs of modern frameworks. …
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