Architecture of Computing Systems
36th International Conference, ARCS 2023, Athens, Greece, June 13-15, 2023, Proceedings
Published on 26. August 2023
Book
Paperback/Softback
XIX, 328 pages
978-3-031-42784-8 (ISBN)
Description
This book constitutes the proceedings of the 36th International Conference on Architecture of Computing Systems, ARCS 2023, which took place in Athens, Greece, in June 2023.
The 18 full papers in this volume were carefully reviewed and selected from 35 submissions.
ARCS provides a platform covering newly emerging and cross-cutting topics, such as autonomous and ubiquitous systems, reconfigurable computing and acceleration, neural networks and artificial intelligence. The selected papers cover a variety of topics from the ARCS core domains, including energy efficiency, applied machine learning, hardware and software system security, reliable and fault-tolerant systems and organic computing. Back to topMore details
Series
Edition
1st ed. 2023
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
34 s/w Abbildungen, 91 farbige Abbildungen
XIX, 328 p. 125 illus., 91 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 19 mm
Weight
528 gr
ISBN-13
978-3-031-42784-8 (9783031427848)
DOI
10.1007/978-3-031-42785-5
Schweitzer Classification
Other editions
Additional editions
Georgios Goumas | Sven Tomforde | Jürgen Brehm
Architecture of Computing Systems
36th International Conference, ARCS 2023, Athens, Greece, June 13-15, 2023, Proceedings
E-Book
08/2023
Springer
€69.54
Available for download
Content
Accelerating Neural Networks.- Energy Efficient LSTM Accelerators for Embedded FPGAs through Parameterised Architecture Design.- A Comparative Study of Neural Network Compilers on ARMv8 Architecture.- Organic Computing Methodology (OC).- A Decision-Theoretic Approach for Prioritzing Maintenance Activities in Organic Computing Systems.- Predicting Physical Disturbances in Organic Computing Systems using Automated Machine Learning.- Self-Adaptive Diagnosis and Reconfigurationin ADNA-Based Organic Computing.- Dependability and Fault Tolerance (VERFE) Error Codes in and for Network Steganography.- Modified Cross Parity Codes For Adjacent Double Error Correction.- Computer Architecture Co-Design.- COMPESCE: A Co-design Approach for memory subsystem Performance Analysis in HPC many-cores.- Post-Silicon Customization Using Deep Neural Networks.- Computer Architectures and Operating Systems.- TOSTING: Investigating Total Store Ordering on ARM.- Back to the Core-Memory Age: Running Operating Systems in NVRAM only.- Retrofitting AMD x86 processors with active virtual machine introspection capabilities.- Organic Computing Applications 1 (OC).- Abstract Artificial DNA's Improved Time Bounds.- Evaluating the Comprehensive Adaptive Chameleon Middleware for Mixed-Critical Cyber-Physical Networks.- CoLeCTs: Cooperative Learning Classifier Tables for Resource Management in MPSoCs.- Hardware Acceleration.- Improved Condition Handling in CGRAs with Complex Loop Support.- FPGA-based Network-attached Accelerators - An Environmental Life Cycle Perspective.- Optimization of OLAP In-memory DB Management Systems with PIM.- Organic Computing Applications 2 (OC).- Real-Time Data Transmission Optimization on 5G Remote-Controlled Units using Deep Reinforcement Learning.- Autonomous ship collision avoidance trained on observational data.- Towards Dependable Unmanned Aerial Vehicle Swarms Using Organic Computing.