Energy Efficiency Issues in Computing Systems

Author(s):  
Krishna Kant
Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 73
Author(s):  
Pedram Khalili Amiri

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 [...]


2016 ◽  
Vol 74 ◽  
pp. 66-85 ◽  
Author(s):  
Yogesh Sharma ◽  
Bahman Javadi ◽  
Weisheng Si ◽  
Daniel Sun

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4117 ◽  
Author(s):  
Andrzej Lis ◽  
Agata Sudolska ◽  
Ilona Pietryka ◽  
Adam Kozakiewicz

The dynamic growth in the use of cloud computing systems results in increasing energy consumption. Consequently, more and more attention is given to energy efficiency issues both in research and theory development as well as the business practice of cloud computing systems. In spite of the rapid development of research, the field has not been mapped from the bibliometric perspective yet. This study aims at publication profiling and mapping the thematic structure of the cloud computing energy efficiency research field. Detailed research objectives include: (1) profiling scientific publications in the field, (2) identifying and exploring thematic research areas, (3) identifying emerging topics and discussing their potential as future research lines. The aforementioned objectives are translated into the following study questions: (1) What are the most productive nations, institutions, source titles, and scholars contributing to research on energy efficiency in cloud computing? (2) What does the thematic structure of the research field look like? (3) What are the “hot” research topics attracting scholars’ attention? The research methodology toolbox includes a combination of bibliometric descriptive studies (research profiling), science mapping (keyword co-occurrence analysis), and literature reviews (systematic literature review). Bibliometric data for analysis were elicited from the Scopus database. The VOSviewer software supported bibliometric analysis and data visualization.


Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1029
Author(s):  
Anabi Hilary Kelechi ◽  
Mohammed H. Alsharif ◽  
Okpe Jonah Bameyi ◽  
Paul Joan Ezra ◽  
Iorshase Kator Joseph ◽  
...  

Power-consuming entities such as high performance computing (HPC) sites and large data centers are growing with the advance in information technology. In business, HPC is used to enhance the product delivery time, reduce the production cost, and decrease the time it takes to develop a new product. Today’s high level of computing power from supercomputers comes at the expense of consuming large amounts of electric power. It is necessary to consider reducing the energy required by the computing systems and the resources needed to operate these computing systems to minimize the energy utilized by HPC entities. The database could improve system energy efficiency by sampling all the components’ power consumption at regular intervals and the information contained in a database. The information stored in the database will serve as input data for energy-efficiency optimization. More so, device workload information and different usage metrics are stored in the database. There has been strong momentum in the area of artificial intelligence (AI) as a tool for optimizing and processing automation by leveraging on already existing information. This paper discusses ideas for improving energy efficiency for HPC using AI.


2011 ◽  
Vol 16 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Giorgio Luigi Valentini ◽  
Walter Lassonde ◽  
Samee Ullah Khan ◽  
Nasro Min-Allah ◽  
Sajjad A. Madani ◽  
...  

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