FPGAs or GPUs, that is the question. Since the popularity of using machine learning algorithms to extract and process the information from raw data, it has been a race between FPGA and GPU vendors to ...

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 ...

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 ...

There has been much written about the potential for FPGAs to take a leadership role in accelerating deep learning but in practice, the hurdles of getting from concept to high performance hardware ...

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 ...

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 ...

Field Programmable Gate Arrays (FPGAs) have notched some noticeable wins as a platform for machine learning, Microsoft’s embrace of the technology in Azure being the most notable example. But for this ...

What’s the killer app for FPGAs? For some people, the allure is the ultra-high data throughput for parallelizable tasks, which can enable some pretty gnarly projects. But what if you’re just starting ...

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 ...

[KF5N] admits he’s not a digital design engineer; he’s more into the analog RF side of things. But he’s recently taken on a project to communicate between a Ubuntu box and an Intel MAX10 FPGA. He did ...