Embedded Computer Systems: Architectures, Modeling, and Simulation, Kartoniert / Broschiert
Embedded Computer Systems: Architectures, Modeling, and Simulation
- 22nd International Conference, SAMOS 2022, Samos, Greece, July 3-7, 2022, Proceedings
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Alex Orailoglu, Marc Reichenbach, Matthias Jung
- Verlag:
- Springer, 08/2022
- Einband:
- Kartoniert / Broschiert, Paperback
- Sprache:
- Englisch
- ISBN-13:
- 9783031150739
- Artikelnummer:
- 11026838
- Umfang:
- 452 Seiten
- Nummer der Auflage:
- 22001
- Ausgabe:
- 1st edition 2022
- Gewicht:
- 680 g
- Maße:
- 235 x 155 mm
- Stärke:
- 24 mm
- Erscheinungstermin:
- 14.8.2022
- Serie:
- Lecture Notes in Computer Science - Band 13511
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
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Klappentext
High Level Synthesis.- High-Level Synthesis of Digital Circuits from Template Haskell and SDF-AP 1 H. H. .- Implementing Synthetic Aperture Radar Backprojection in Chisel - A Field Report.-EasyHBM: Simple and Fast HBM Access for FPGAs using High-Level Synthesis.- Memory Systems.- TREAM: A Tool for Evaluating Error Resilience of Tree-based Models using Approximate Memory.-Split'n'Cover: ISO 26262 Hardware Safety Analysis with SystemC.- Tagged Geometric History Length Access Interval Prediction for Tightly Coupled Memory Systems.- Processor Architecture.-NanoController: A Minimal and Flexible Processor Architecture for UltraLow-Power.- ControlPULP: A RISC-V Power Controller for HPC Processors with Parallel Control-Law Computation Acceleration.- Embedded Software Systems and beyond.-CASA: An Approach for exposing and documenting Concurrency-related Software Properties.- High-Level Simulation of Embedded Software Vulnerabilities to EM SideChannel Attacks.- Deep Learning Optimization I.-A Design Space Exploration Methodology for Enabling Tensor Train Decomposition in Edge Devices.- Study of DNN-based Ragweed Detection from Drones.- PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-Core MCUs through Performance-Driven Autotuning.-Extra-functional Property Estimation.- The Impact of Dynamic Storage Allocation on CPython Execution Time, Memory Footprint and Energy Consumption: An Empirical Study.- Application runtime estimation for AURIX embedded MCU using deep learning.-A Hybrid Performance Prediction Approach for Fully-Connected Artificial Neural Networks on Multi-Core Platforms.- Deep Learning Optimization I.- A Smart HW-Accelerator for Non-Uniform Linear Interpolation of MLActivation Functions.-Hardware-Aware Evolutionary Filter Pruning.- Innovative Architectures and tools for Security.- Obfuscating the Hierarchy of a Digital IP.-On the effectiveness of true random number generators implemented on FPGAs.- Power and Energy.- SIDAM: A Design Space Exploration Framework for Multi-Sensor Embedded Systems Powered by Energy Harvesting.- A Data-Driven Approach to Lightweight DVFS-Aware Counter-Based Power Modeling for Heterogeneous Platforms.
Biografie (Matthias Jung)
Jahrgang 1961, evangelischer Pfarrer und Erziehungswissenschaftler, seit 1990 in Voerde/NiederrheinGemeindepfarrer und fast genauso lang nebenamtlicher Mitarbeitender im KDA (Kirchlicher Dienst in der Arbeitswelt), leidenschaftlicher Prediger, Hobby-Fotograf und Radsportler.