A Review On Implementation And Performance Analysis Of ALU Using Various Clock Gating Techniques On Various FPGA Board

Vikas K. Jathar, P. C. Bhaskar

Abstract


The need of time demands for development in high
speed and high performance Chip design systems in
networking or in communication and computing and this can
be achieved by designing and implementing of a latch free
Clock Gating Arithmetic and Logic Unit for obtaining in low
power processor design in the platform Xilinx ISE 14.5 and
Power analysis is carried out using Xilinx XPower
analyzer.In our proposed system, we are focusing on clock
gating approach to obtain reduction in clock power and total
power consumption in Arithmetic and Logic Unit and we
have analyzed power reduction on various Field
Programmable Gate Array devices. Clock power and total
power reduction by clock gating priciple in 16-bit ALU are
verified by XPower analyzer on 40-nm Virtex-6, 65-nm
Virtex-5,90- nm Virtex- 4, Spartan 3, Spartan 3E,Spartan-6
and Artix-7 target device.

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References


T. Li, M. M. Ogihara, and S. Ma, “On combining multiple clusterings: an

overview and a new perspective,” Appl. Intell., vol. 32, no. 2, pp. 207–219,

A. Goder and V. Filkov, “Consensus clustering algorithms: Comparison and

refinement,” in Proc. SIAM Workshop Algorithm Eng. Exp., pp. 109–117,

Iam-On, N. and Boongoen, T., “Improved link-based cluster ensembles,”

Proceeding of International Joint Conference on Neural Networks (IJCNN), pp.

-8, 2012.

Tsaipei Wang, “CA-Tree: A Hierarchical Structure for Efficient and Scalable

Coassociation-Based Cluster Ensembles,” IEEE Transactions on Systems, Man,

and Cybernetics, Part B: Cyberneticsm, pp. 686 – 698, Volume-41, Issue-3,

Tapas Kanungo and Nathan S. Netanyahu, “An Efficient k-Means Clustering

Algorithm: Analysis and Implementation,” IEEE Transactions on Pattern

Analysis and Machine Intelligence, Vol. 24, No. 7, 2002.

NuwanGanganath and Chi-Tsun Cheng, “Data Clustering with Cluster Size

Constraints Using a Modified k-means Algorithm,” International Conference on

Cyber-Enabled Distributed Computing and Knowledge Discovery, 2014.

NavjotKaur, JaspreetKaurSahiwal, NavneetKaur ,“Efficient K-Means

Clustering algorithm Using Ranking Method In Data Mining” International

Journal of Advance Research in Computer Engineering & Technology ,Volume

, Issue 3, May2012.

Bernard J. Jansen, Danielle L. Booth Amanda Spink “Determining the User

Intent of Web Search Engine Queries,” Proceeding of 16th International

Conference on World Wide Web, pp. 1149-1150, 2007.

Shi Na, Liu Xumin and Guan Yong, “Research on k-means clustering

algorithm: An improved K-means Clustering Algorithm,” Proceeding of 3rd

IEEE International Symposium on Intelligent Information Technology and

Security Informatics (IITSI), pp. 63-67, 2010.

Iam-On, N. and Boongoen, T., “Improved link-based cluster ensembles,”

Proceeding of International Joint Conference on Neural Networks (IJCNN), pp.

-8, 2012.

Chen-Chung Liu and Shao-Wei Chu, “A Modified K-means Algorithm -

Two-Layer K-means Algorithm,” Tenth International Conference on Intelligent

Information Hiding and Multimedia Signal Processing, 2014.

Bhatia S., “New Improved technique for initial cluster centers of k-means

clustering using Genetic Algorithm,” Proceeding of IEEE 3International

Conference for Convergence of Technology (I2CT), pp. 1-4, 2014.

Jiejhang and Jianrui Dong, “A new method on finding optimal centers for

improving k-means algorithm,” Proceeding of 27th IEEE Control and Decision

Conference (CCDC), pp-1827-1832, May, 2015.

Juntaowang and Xiaolong Su, “An improved K-means clustering

algorithm,” Proceeding of IEEE 3rd International Conference on

Communication Software and Networks (ICCSN), pp-44-46, 2011.


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