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 ...

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 into working Verliog. The end goal is ...

Field programmable gate arrays (FPGAs) have emerged as flexible hardware platforms for accelerating deep learning networks, offering high energy efficiency, low latency and reconfigurable parallelism.

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 ...

Hardware and device makers are in a mad dash to create or acquire the perfect chip for performing deep learning training and inference. While we have yet to see anything that can handle both parts of ...

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 ...

An EDA tool that turns code into real hardware inside a chip—design, test, and run custom FPGA systems before anything is ...

Altera University aims to affordably and easily introduce students to the world of FPGAs and digital logic programming tools by unveiling the curriculum, tutorials, and lab exercises that bridge the ...