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Architecture of Computing Systems

Overview of attention for book
Architecture of Computing Systems
Springer International Publishing

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Energy Efficient Frequency Scaling on GPUs in Heterogeneous HPC Systems
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    Chapter 2 Dual-IS: Instruction Set Modality for Efficient Instruction Level Parallelism
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    Chapter 3 Pasithea-1: An Energy-Efficient Self-contained CGRA with RISC-Like ISA
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    Chapter 4 Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning
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    Chapter 5 FPGA-Based Dynamic Deep Learning Acceleration for Real-Time Video Analytics
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    Chapter 6 Effects of Approximate Computing on Workload Characteristics
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    Chapter 7 QPU-System Co-design for Quantum HPC Accelerators
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    Chapter 8 Protected Functions: User Space Privileged Function Calls
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    Chapter 9 Using Look Up Table Content as Signatures to Identify IP Cores in Modern FPGAs
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    Chapter 10 Hardware Isolation Support for Low-Cost SoC-FPGAs
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    Chapter 11 Memristor Based FPGAs: Understanding the Effect of Configuration Memory Faults
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    Chapter 12 On the Reliability of Real-Time Operating System on Embedded Soft Processor for Space Applications
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    Chapter 13 NDNET: A Unified Framework for Anomaly and Novelty Detection
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    Chapter 14 Organic Computing to Improve the Dependability of an Automotive Environment
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    Chapter 15 A Context Aware and Self-improving Monitoring System for Field Vegetables
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    Chapter 16 Semi-model-Based Reinforcement Learning in Organic Computing Systems
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    Chapter 17 Deep Reinforcement Learning with a Classifier System – First Steps
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    Chapter 18 GAE-LCT: A Run-Time GA -Based Classifier E volution Method for Hardware LCT Controlled SoC Performance-Power Optimization
Attention for Chapter 4: Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
4 X users

Citations

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3 Dimensions

Readers on

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3 Mendeley
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Chapter title
Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning
Chapter number 4
Book title
Architecture of Computing Systems
Published in
arXiv, January 2022
DOI 10.1007/978-3-031-21867-5_4
Book ISBNs
978-3-03-121866-8, 978-3-03-121867-5
Authors

Saba, Issa, Arima, Eishi, Liu, Dai, Schulz, Martin, Issa Saba, Eishi Arima, Dai Liu, Martin Schulz

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 33%
Unknown 2 67%
Readers by discipline Count As %
Engineering 1 33%
Unknown 2 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 May 2024.
All research outputs
#17,397,869
of 26,434,713 outputs
Outputs from arXiv
#330,628
of 1,019,050 outputs
Outputs of similar age
#302,517
of 532,712 outputs
Outputs of similar age from arXiv
#9,251
of 25,753 outputs
Altmetric has tracked 26,434,713 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,019,050 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 62% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 532,712 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25,753 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.