FINN- <i>R</i>
Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser et al. · 30 Sep 2018
Convolutional Neural Networks have rapidly become the most successful machine-learning algorithm, enabling ubiquitous machine vision and intelligent decisions on even embedded computing systems. While the underlying arithmetic is structurally simple, compute and memory requirements are challenging. One of the promising opportunities is leveraging reduced-precision representations for inputs, activations, and model parameters. The resulting scalability in…
VTR 7.0
Jason Luu, Jeffrey Goeders, Michael Wainberg et al. · 1 Jun 2014
Exploring architectures for large, modern FPGAs requires sophisticated software that can model and target hypothetical devices. Furthermore, research into new CAD algorithms often requires a complete and open source baseline CAD flow. This article describes recent advances in the open source Verilog-to-Routing (VTR) CAD flow that enable further research in these areas. VTR now supports…
VTR 8
Kevin E. Murray, Oleg Petelin, Sheng Zhong et al. · 1 Jun 2020
Developing Field-programmable Gate Array (FPGA) architectures is challenging due to the competing requirements of various application domains and changing manufacturing process technology. This is compounded by the difficulty of fairly evaluating FPGA architectural choices, which requires sophisticated high-quality Computer Aided Design (CAD) tools to target each potential architecture. This article describes version 8.0 of the…
[DL] A Survey of FPGA-based Neural Network Inference Accelerators
Kaiyuan Guo, Shulin Zeng, Jincheng Yu et al. · 28 Mar 2019
Recent research on neural networks has shown a significant advantage in machine learning over traditional algorithms based on handcrafted features and models. Neural networks are now widely adopted in regions like image, speech, and video recognition. But the high computation and storage complexity of neural network inference poses great difficulty on its application. It is…
Techniques for Design and Implementation of Secure Reconfigurable PUFs
Mehrdad Majzoobi, Farinaz Koushanfar, Miodrag Potkonjak · 1 Mar 2009
Physically unclonable functions (PUFs) provide a basis for many security and digital rights management protocols. PUF-based security approaches have numerous comparative strengths with respect to traditional cryptography-based techniques, including resilience against physical and side channel attacks and suitability for lightweight protocols. However, classical delay-based PUF structures have a number of drawbacks including susceptibility to guessing,…
