Thermal-aware on-line task allocation for 3D multi-core processor throughput optimization

Author(s):  
Chiao-Ling Lung ◽  
Yi-Lun Ho ◽  
Ding-Ming Kwai ◽  
Shih-Chieh Chang
2013 ◽  
Vol 6 (4) ◽  
pp. 1783-1807
Author(s):  
Patricia Kristine Sheridan ◽  
Pawel Kosicki ◽  
Goldie Nejat ◽  
Beno Benhabib

2017 ◽  
Vol 19 ◽  
pp. 112-120 ◽  
Author(s):  
Sumarga Kumar Sah Tyagi ◽  
Deepak Kumar Jain ◽  
Steven Lawrence Fernandes ◽  
Pranab K. Muhuri

2013 ◽  
Vol 23 (01) ◽  
pp. 1350002
Author(s):  
FRANK DEHNE ◽  
HAMIDREZA ZABOLI

On-line Analytical Processing (OLAP) has become one of the most powerful and prominent technologies for knowledge discovery in VLDB (Very Large Database) environments. Central to the OLAP paradigm is the data cube, a multi dimensional hierarchy of aggregate values that provides a rich analytical model for decision support. Various sequential algorithms for the efficient generation of the data cube have appeared in the literature. However, given the size of contemporary data warehousing repositories, multi-processor solutions are crucial for the massive computational demands of current and future OLAP systems. In this paper we discuss the development of MCMD-CUBE, a new parallel data cube construction method for multi-core processors with multiple disks. We present experimental results for a Sandy Bridge multi-core processor with four parallel disks. Our experiments indicate that MCMD-CUBE achieves very close to linear speedup. A critical part of our MCMD-CUBE method is parallel sorting. We developed a new parallel sorting method termed MCMD-SORT for multi-core processors with multiple disks which outperforms other previous methods.


2010 ◽  
Vol 38 (4) ◽  
pp. 307-311
Author(s):  
Deshi Ye ◽  
Guochuan Zhang
Keyword(s):  
On Line ◽  

Author(s):  
Cody Hao Yu ◽  
Chiao-Ling Lung ◽  
Yi-Lun Ho ◽  
Ruei-Siang Hsu ◽  
Ding-Ming Kwai ◽  
...  

Author(s):  
William Krakow

In the past few years on-line digital television frame store devices coupled to computers have been employed to attempt to measure the microscope parameters of defocus and astigmatism. The ultimate goal of such tasks is to fully adjust the operating parameters of the microscope and obtain an optimum image for viewing in terms of its information content. The initial approach to this problem, for high resolution TEM imaging, was to obtain the power spectrum from the Fourier transform of an image, find the contrast transfer function oscillation maxima, and subsequently correct the image. This technique requires a fast computer, a direct memory access device and even an array processor to accomplish these tasks on limited size arrays in a few seconds per image. It is not clear that the power spectrum could be used for more than defocus correction since the correction of astigmatism is a formidable problem of pattern recognition.


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