Architecture of Computing Systems : 35th International Conference, ARCS 2022, Heilbronn, Germany, September 13-15, 2022, Proceedings

Schulz, Martin

ISBN 10: 303121868X / ISBN 13: 9783031218682

Published by Springer 2022-12, 2022

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Seller Inventory # 6666-IUK-9783031218682

Bibliographic Details

• Title: Architecture of Computing Systems : 35th International Conference, ARCS 2022, Heilbronn, Germany, September 13-15, 2022, Proceedings
• Publisher: Springer 2022-12
• Publication Date: 2022
• Language: English
• ISBN 10: 303121868X
• ISBN 13: 9783031218682
• Binding: PF
• Condition: New

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Synopsis

Energy Efficiency.- Energy Efficient Frequency Scaling on GPUs in Heterogeneous HPC Systems.- Dual-IS: Instruction Set Modality for Efficient Instruction Level Parallelism.- Pasithea-1: An Energy-Efficient Self-Contained CGRA With RISC-Like ISA.- Applied Machine Learning.- Orchestrated Co-Scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning.- FPGA-based Dynamic Deep Learning Acceleration for Real-time Video Analytics.- Advanced Computing Techniques.- Effects of Approximate Computing on Workload Characteristics.- QPU-System Co-Design for Quantum HPC Accelerators.- Hardware and Software System Security.- Protected Functions: User Space Privileged Function Calls.- Using Look Up Table Content as Signatures to Identify IP Cores in Modern FPGAs.- Hardware Isolation Support for Low-Cost SoC-FPGAs.- Reliable and Fault-tolerant systems.- Memristor based FPGAs: Understanding the Effect of Configuration Memory Faults.- On the Reliability of Real-time Operating System on Embedded Soft Processor for Space Applications.- Special Track: Organic Computing.- NDNET: a Unified Framework for Anomaly and Novelty Detection.- Organic Computing to Improve the Dependability of an Automotive Environment.- A context aware and self-improving monitoring system for field vegetables.- Semi-Model-Based Reinforcement Learning in Organic Computing Systems.- Deep Reinforcement Learning with a Classifier System - First Steps.- GAE-LCT: A run-time GA-based Classifier Evolution Method for Hardware LCT controlled SoC Performance-Power Optimization.