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Architecture of Computing Systems - ARCS 2017

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Cover of 'Architecture of Computing Systems - ARCS 2017'

Table of Contents

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    Book Overview
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    Chapter 1 Effectiveness of Software-Based Hardening for Radiation-Induced Soft Errors in Real-Time Operating Systems
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    Chapter 2 Fault-Tolerant Execution on COTS Multi-core Processors with Hardware Transactional Memory Support
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    Chapter 3 OpenCL-Based 6D-Vision on Heterogeneous System on Chips
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    Chapter 4 Hardware-Accelerated Radix-Tree Based String Sorting for Big Data Applications
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    Chapter 5 Boosting Java Performance Using GPGPUs
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    Chapter 6 A Low Noise Unikernel for Extrem-Scale Systems
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    Chapter 7 A New Approach to Detecting Execution Phases Using Performance Monitoring Counters
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    Chapter 8 Adaptive and Scalable Predictive Page Policies for High Core-Count Server CPUs
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    Chapter 9 A Method for Fast Evaluation of Sharing Set Management Strategies in Cache Coherence Protocols
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    Chapter 10 HBM-Resident Prefetching for Heterogeneous Memory System
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    Chapter 11 Reduced Complexity Many-Core: Timing Predictability Due to Message-Passing
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    Chapter 12 Parallel Forwarding for Efficient Bandwidth Utilization in Networks-on-Chip
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    Chapter 13 PLSS: A Scheduler for Multi-core Embedded Systems
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    Chapter 14 Exploring ILP and TLP on a Polymorphic VLIW Processor
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    Chapter 15 Scheduling of Datacompression on Distributed Systems with Time- and Event-Triggered Messages
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    Chapter 16 Semi-partitioned Mixed-Criticality Scheduling
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    Chapter 17 DVFS Space Exploration in Power Constrained Processing-in-Memory Systems
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    Chapter 18 Reducing Data Center Resource Over-Provisioning Through Dynamic Load Management for Virtualized Network Functions
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    Chapter 19 Dynamic Power Management in a Heterogeneous Processor Architecture
Overall attention for this book and its chapters
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Mentioned by

2 tweeters

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Architecture of Computing Systems - ARCS 2017
Published by
Springer International Publishing, March 2017
DOI 10.1007/978-3-319-54999-6
978-3-31-954998-9, 978-3-31-954999-6

Jens Knoop, Wolfgang Karl, Martin Schulz, Koji Inoue, Thilo Pionteck

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 6%
Student > Master 1 6%
Unknown 15 88%
Readers by discipline Count As %
Computer Science 1 6%
Engineering 1 6%
Unknown 15 88%