Cantitate/Preț
Produs
Total produse
Vezi coșul
Architecture of Computing Systems: 36th International Conference, ARCS 2023, Athens, Greece, June 13–15, 2023, Proceedings de Georgios Goumas

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 Pionteck
en Limba Engleză Paperback – 26 aug 2023
T​his 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 top
Citește tot Restrânge

Din seria Lecture Notes in Computer Science

Preț: 42041 lei

Preț vechi: 52551 lei
-20% Nou

Puncte Express: 631
Preț estimativ în valută:
8046€ • 8329$ • 6800£

Carte tipărită la comandă

Livrare economică 06-20 martie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

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

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.