Semiconductor Engineering

Scaling Open-Source HW Accelerator for Deep NN Inference (UDE, Fraunhofer IMS)

Researchers from University of Duisburg-Essen and Fraunhofer Institute for Microelectronic Circuits and Systems have ...
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.
Nature

FPGA-Based Hardware Acceleration for Computer Vision Applications

Field-Programmable Gate Arrays (FPGAs) have emerged as a versatile platform for accelerating computer vision tasks by exploiting fine-grained parallelism, deep pipelining and reconfigurable logic.
Semiconductor Engineering

Automated MLIR-based HLS framework That Generates FPGA HW Designs From A Variety of CNN Layers (TU Dresden)

“Driven by the increasing demand for low-latency and real-time processing, machine learning applications are steadily migrating toward edge computing platforms, where Field-Programmable Gate Arrays ...