Deep learning and complex machine learning has quickly become one of the most important computationally intensive applications for a wide variety of fields. The combination of large data sets, ...

Getting into FPGA design isn’t a monolithic experience. You have to figure out a toolchain, learn how to think in hardware during the design, and translate that ...

A wave of machine-learning-optimized chips is expected to begin shipping in the next few months, but it will take time before data centers decide whether these new accelerators are worth adopting and ...

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 ...

FPGAs have long been used in the early stages of any new digital technology, given their utility for prototyping and rapid evolution. But with machine learning, FPGAs are showing benefits beyond those ...

Continued exponential growth of digital data of images, videos, and speech from sources such as social media and the internet-of-things is driving the need for analytics to make that data ...

Intel and ZTE, a leading technology telecommunications equipment and systems company, have worked together to reach a new benchmark in deep learning and convolutional neural networks (CNN). The ...

Field programmable gate arrays (FPGAs) are integrated circuits that provide the foundation to implement custom digital circuits. These highly customizable ICs make it possible to design complex ...

Mipsology’s Zebra Deep Learning inference engine is designed to be fast, painless, and adaptable, outclassing CPU, GPU, and ASIC competitors. I recently attended the 2018 Xilinx Development Forum (XDF ...

FPGAs provide a balance of performance and flexibility required in advanced video processing applications. This white paper describes benefits of FPGAs for video streaming, content creation and AI and ...