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 ...

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 ...

In the last couple of years, we have written and heard about the usefulness of GPUs for deep learning training as well as, to a lesser extent, custom ASICs and FPGAs. All of these options have shown ...

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 ...

A technical paper titled “Application of Machine Learning in FPGA EDA Tool Development” was published by researchers at the University of Texas Dallas. “With the recent advances in hardware ...

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, ...

Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). Developed with ZTE, a leading technology telecommunications equipment and systems ...

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 ...

Achronix’s Speedcore Gen 4 can be tailored for machine-learning applications as well as to deliver high-performance FPGA connectivity for embedded FPGAs. 1. Processor performance is starting to level ...

This afternoon Microsoft announced Brainwave, an FPGA-based system for ultra-low latency deep learning in the cloud. Early benchmarking indicates that when using Intel Stratix 10 FPGAs, Brainwave can ...