云麓散人的博客

Three-dimensional design methodologies for tree-based FPGA architecture [Pangracious, V., et al.][Springer,][2015]

Architecture exploration of FPGA based accelerators for bioinformatics applications [Varma, B.S.C., et al.][Springer,][2016] This book presents an evaluation methodology to design future FPGA fabrics incorporating hard embedded blocks (HEBs) to accelerate applications. This methodology will be useful for selection of blocks to be embedded into the fabric and for evaluating the performance gain that can be achieved by such an embedding. The authors illustrate the use of their methodology by studying the impact of HEBs on two important bioinformatics applications: protein docking and genome assembly. The book also explains how the respective HEBs are designed and how hardware implementation of the application is done using these HEBs. It shows that significant speedups can be achieved over pure software implementations by using such FPGA-based accelerators. The methodology presented in this book may also be used for designing HEBs for accelerating software implementations in other domains besides bioinformatics. This book will prove useful to students, researchers, and practicing engineers alike. Keywords BioInformatics FPGA FPGA Accelerators HEB design Hard embedded blocks

Application of FPGA to real-time machine learning - hardware reservoir computers and software image processing [Antonik, P.][Springer,][2018] This book lies at the interface of machine learning – a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail – and photonics – the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.