Nature

FPGA-Accelerated Object Detection with Deep Learning Techniques

Field-programmable gate arrays (FPGAs) have emerged as a vital class of reconfigurable hardware accelerators, offering a compelling balance of performance, power efficiency and flexibility for ...
Nature

FPGA-Based Acceleration of Deep Learning Networks

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.
Semiconductor Engineering

Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud

“FPGAs have shown great potential in providing low-latency and energy-efficient solutions for deep neural network (DNN) inference applications. Currently, the majority of FPGA-based DNN accelerators ...
Network World

Microsoft’s new Catapult v2 server design is targeted at AI

For years, Microsoft has been delivering speedy and accurate Bing results with experimental servers called Project Catapult, which have now received an architectural upgrade. The Catapult servers use ...
Semiconductor Engineering

New Ways To Optimize GEMM-Based Applications Targeting Two Leading AI-Optimized FPGA Architectures

A technical paper titled “Efficient Approaches for GEMM Acceleration on Leading AI-Optimized FPGAs” was published by researchers at The University of Texas at Austin and Arizona State University.