Format:
1 Online-Ressource(XII, 197 p. 109 illus., 101 illus. in color.)
Edition:
1st ed. 2022.
ISBN:
9783031199837
Series Statement:
Lecture Notes in Computer Science 13569
Content:
100% Visibility At MHz Speed: Efficient Soft Scan-Chain Insertion on AMD/Xilinx FPGAs -- FPGA-Accelerated Terso_ Multi-Body Potential for Molecular Dynamics Simulations -- A Runtime Programmable Accelerator for Convolutional and Multilayer Perceptron Neural Networks on FPGA -- A Multi-FPGA Scalable Framework for Deep Reinforcement Learning through Neuroevolution -- Development Progress of SWLBM a Framework Based on Lattice Boltzmann Method for Fluid Dynamics Simulation -- Entropy-based Early-exit in a FPGA-based Low-precision Neural Network -- FPGA-extended General Purpose Computer Architecture -- Multi-Spectral In-vivo FPGA-based Surgical Imaging -- Hardware-Aware Optimizations for Deep Learning Inference on Edge Devices -- IPEC: Open-Source Design Automation for Inter-Processing Element Communication -- Light-weight Permutation Generator for E_cient Convolutional Neural Network Data Augmentation -- Real-time embedded object tracking with Discriminative Correlation Filters using convolutional features -- VenOS: A virtualization framework for multiple tenant accommodation on reconfigurable platforms.
Content:
This book constitutes the proceedings of the 18th International Symposium on Applied Reconfigurable Computing, ARC 2022, held as a virtual event, in September 2022. The 13 full papers presented in this volume were reviewed and selected from 16 submissions. The papers cover a broad spectrum of applications of reconfigurable computing, from driving assistance, data and graph processing acceleration, computer security to the societal relevant topic of supporting early diagnosis of Covid infectious conditions.
Additional Edition:
ISBN 9783031199820
Additional Edition:
ISBN 9783031199844
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031199820
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031199844
Language:
English
DOI:
10.1007/978-3-031-19983-7
