On-chip sensor-driven efficient thermal profile estimation algorithms

2010 ◽  
Vol 15 (3) ◽  
pp. 1-27 ◽  
Author(s):  
Yufu Zhang ◽  
Ankur Srivastava ◽  
Mohamed Zahran
Pramana ◽  
1986 ◽  
Vol 26 (2) ◽  
pp. 151-159 ◽  
Author(s):  
S K Khanna ◽  
M Sekar ◽  
A Michael David ◽  
K Govinda Rajan ◽  
P Bhaskar Rao

Author(s):  
Man Prakash Gupta ◽  
Minki Cho ◽  
Saibal Mukhopadhyay ◽  
Satish Kumar

Transition from single core to multicore technology has brought daunting challenge for thermal management of microprocessor chips. The issue of power dissipation in next generation chip will be far more critical as further transition from multicore to many-core processors is soon to be expected. It is very important to obtain uniform on-chip thermal profile with low peak temperature for improved performance and reliability of many-core processors. In this paper, a proactive thermal management technique called ‘power multiplexing’ is explored for many-core processors. Power multiplexing involves redistribution of locations of power dissipating cores at regular time intervals to obtain uniform thermal profile with low peak temperature. Three different migration policies namely random, cyclic and global coolest replace have been employed for power multiplexing and their efficacy in reducing the peak temperature and thermal gradient on chip is investigated. A comparative study of these policies has been performed enlisting their limits and advantages from the thermal and implementation perspective considering important relevant parameters such as migration frequency. For a given migration frequency, global coolest replace policy is found to be the most effective among the three policies considered as this policy leads to 10 °C reduction in peak temperature and 20 °C reduction in maximum spatial temperature difference on a 256 core chip. Proximity of active cores or power configuration on chip is characterized by a parameter ‘proximity index’ which emerges as an important parameter to represent the spatial power distribution on a chip. Global coolest replace policy optimizes the power map on chip taking care of not only the proximity of active cores but also the finite-size effect of chip and the 3D system of electronic package leading to almost uniform thermal profile on chip with lower average temperature.


2020 ◽  
Vol 477 (14) ◽  
pp. 2679-2696
Author(s):  
Riddhi Trivedi ◽  
Kalyani Barve

The intestinal microbial flora has risen to be one of the important etiological factors in the development of diseases like colorectal cancer, obesity, diabetes, inflammatory bowel disease, anxiety and Parkinson's. The emergence of the association between bacterial flora and lungs led to the discovery of the gut–lung axis. Dysbiosis of several species of colonic bacteria such as Firmicutes and Bacteroidetes and transfer of these bacteria from gut to lungs via lymphatic and systemic circulation are associated with several respiratory diseases such as lung cancer, asthma, tuberculosis, cystic fibrosis, etc. Current therapies for dysbiosis include use of probiotics, prebiotics and synbiotics to restore the balance between various species of beneficial bacteria. Various approaches like nanotechnology and microencapsulation have been explored to increase the permeability and viability of probiotics in the body. The need of the day is comprehensive study of mechanisms behind dysbiosis, translocation of microbiota from gut to lung through various channels and new technology for evaluating treatment to correct this dysbiosis which in turn can be used to manage various respiratory diseases. Microfluidics and organ on chip model are emerging technologies that can satisfy these needs. This review gives an overview of colonic commensals in lung pathology and novel systems that help in alleviating symptoms of lung diseases. We have also hypothesized new models to help in understanding bacterial pathways involved in the gut–lung axis as well as act as a futuristic approach in finding treatment of respiratory diseases caused by dysbiosis.


2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.


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