Architecture of Computing Systems: 36th International Conference, ARCS 2023, Athens, Greece, June 13–15, 2023, Proceedings: Lecture Notes in Computer Science, cartea 13949
Editat de Georgios Goumas, Sven Tomforde, Jürgen Brehm, Stefan Wildermann, Thilo Piontecken Limba Engleză Paperback – 26 aug 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 topARCS 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.
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Specificații
ISBN-13: 9783031427848
ISBN-10: 303142784X
Pagini: 328
Ilustrații: XIX, 328 p. 125 illus., 91 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 303142784X
Pagini: 328
Ilustrații: XIX, 328 p. 125 illus., 91 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
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.