scholarly journals Editorial for the Special Issue on Emerging Memory and Computing Devices in the Era of Intelligent Machines

Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 73
Author(s):  
Pedram Khalili Amiri
Keyword(s):  
Energy Efficiency ◽  
System Level ◽  
Special Issue ◽  
Computing Systems ◽  
Intelligent Machines ◽  
Emerging Memory ◽  
Overall Performance

Computing systems are undergoing a transformation from logic-centric toward memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, bandwidth, latency, and energy efficiency of the memory, rather than the logic sub-system [...]

scholarly journals Energy Efficiency in Smart Homes and Smart Grids

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2054
Author(s):  
Anna Fensel ◽  
Juan Miguel Gómez Berbís
Keyword(s):  
Energy Efficiency ◽  
Smart Grids ◽  
Smart Homes ◽  
Special Issue

Here, we overview the Energies journal special issue that is dedicated to the topic of “Energy Efficiency in Smart Homes and Smart Grids” (https://www [...]

scholarly journals Towards Neuromorphic Learning Machines Using Emerging Memory Devices with Brain-Like Energy Efficiency

2018 ◽  
Vol 8 (4) ◽  
pp. 34 ◽  
Author(s):  
Vishal Saxena ◽  
Xinyu Wu ◽  
Ira Srivastava ◽  
Kehan Zhu
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
Deep Learning ◽  
Large Scale ◽  
Learning Algorithms ◽  
Memory Devices ◽  
Cognitive Computing ◽  
Mixed Signal ◽  
Von Neumann ◽  
Emerging Memory

The ongoing revolution in Deep Learning is redefining the nature of computing that is driven by the increasing amount of pattern classification and cognitive tasks. Specialized digital hardware for deep learning still holds its predominance due to the flexibility offered by the software implementation and maturity of algorithms. However, it is being increasingly desired that cognitive computing occurs at the edge, i.e., on hand-held devices that are energy constrained, which is energy prohibitive when employing digital von Neumann architectures. Recent explorations in digital neuromorphic hardware have shown promise, but offer low neurosynaptic density needed for scaling to applications such as intelligent cognitive assistants (ICA). Large-scale integration of nanoscale emerging memory devices with Complementary Metal Oxide Semiconductor (CMOS) mixed-signal integrated circuits can herald a new generation of Neuromorphic computers that will transcend the von Neumann bottleneck for cognitive computing tasks. Such hybrid Neuromorphic System-on-a-chip (NeuSoC) architectures promise machine learning capability at chip-scale form factor, and several orders of magnitude improvement in energy efficiency. Practical demonstration of such architectures has been limited as performance of emerging memory devices falls short of the expected behavior from the idealized memristor-based analog synapses, or weights, and novel machine learning algorithms are needed to take advantage of the device behavior. In this article, we review the challenges involved and present a pathway to realize large-scale mixed-signal NeuSoCs, from device arrays and circuits to spike-based deep learning algorithms with ‘brain-like’ energy-efficiency.

THE LANDSCAPE OF INCONSISTENCY: A PERSPECTIVE

2011 ◽  
Vol 05 (03) ◽  
pp. 235-256 ◽  
Author(s):  
DU ZHANG ◽  
ÉRIC GRÉGOIRE
Keyword(s):  
Cloud Computing ◽  
Social Computing ◽  
Special Issue ◽  
Computing Systems ◽  
Semantic Computing

The focus of this introduction to this special issue is to draw a picture as comprehensive as possible about various dimensions of inconsistency. In particular, we consider: (1) levels of knowledge at which inconsistency occurs; (2) categories and morphologies of inconsistency; (3) causes of inconsistency; (4) circumstances of inconsistency; (5) persistency of inconsistency; (6) consequences of inconsistency; (7) metrics for inconsistency; (8) theories for handling inconsistency; (9) dependencies among occurrences of inconsistency; and (10) problem domains where inconsistency has been studied. The take-home message is that inconsistency is ubiquitous and handling inconsistency is consequential in our endeavors. How to manage and reason in the presence of inconsistency presents a very important issue in semantic computing, cloud computing, social computing, and many other data-rich or knowledge-rich computing systems.

scholarly journals Guest Editorial Special Issue on Multimedia Services Provision Over Future Mobile Computing Systems

2018 ◽  
Vol 12 (1) ◽  
pp. 12-15 ◽  
Author(s):  
George Mastorakis ◽  
Evangelos Pallis ◽  
Constandinos X. Mavromoustakis ◽  
Lei Shu ◽  
Joel J. P. C. Rodrigues
Keyword(s):  
Mobile Computing ◽  
Guest Editorial ◽  
Special Issue ◽  
Multimedia Services ◽  
Computing Systems ◽  
Editorial Special Issue
Sign in / Sign up

Export Citation Format

Share Document