Custom accelerators for neural network training have garnered plenty of attention in the last couple of years, but without significant software footwork, many are still difficult to program and could leave efficiencies on the table. …
Around this time last year, we delved into a new FPGA-based architecture that targeted efficient, scalable machine learning inference from startup DeePhi Tech. …
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. …
Over the last couple of years, we have focused extensively on the hardware required for training deep neural networks and other machine learning algorithms. …
At the end of 2016, Amazon Web Services announced it would be making high-end Xilinx FPGAs available via a cloud delivery model, beginning first in a developer preview mode before branching with higher-level tools to help potential new users onboard and experiment with FPGA acceleration as the year rolls on. …
There is little doubt that this is a new era for FPGAs. …
FPGAs have been an emerging topic on the application acceleration front over the last couple of years, but despite increased attention around use cases in machine learning and other hot areas, hands have been tied due to simply on-boarding with both the hardware and software. …
Every new hardware device that offers some kind of benefit compared to legacy devices faces the task of overcoming the immense inertia that is imparted to a platform by the software that runs upon it. …
While much of the work at Baidu we have focused on this year has centered on the Chinese search giant’s deep learning initiatives, many other critical, albeit less bleeding edge applications present true big data challenges. …
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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