Theoretical studies on various cell partitioning methods are lucidly presented in the current research pertaining to design and development of VLSI circuits. Owing to the difficulties in designing complex VLSI systems, it is extremely crucial to partition the large circuit into tiny logic blocks to reduce time complexity, space complexity and power consumption. To envisage the same, this communication scrutinizes a heuristic technique by using various data mining algorithms such as K-means algorithms, K-Nearest Neighbor (K-NN), Fuzzy c-means and Support Vector Machine (SVM) for resolution of complexity in VLSI circuits, where K-NN and SVM are employed for classification purpose and Fuzzy c-means and K-means methodologies are deployed for clustering purpose. The upshot of the research revealed that K-NN and Fuzzy c-means methods bestow optimum result pertaining to VLSI cell partitioning.

K-means algorithms, K-nearest neighbor, Fuzzy c-means, The Support Vector Machines, Partitioning, and Data mining

[1] Brian Von Herzen,VLSI Partitioning of a 2-Gs/s Digital Spectrometer, IEEE journal of solid-state circuits, VOL. 26, NO. 5, MAY1991.
[2] Gan, Guojun, Chaoqun Ma, and Jianhong Wu, Data Clustering: Theory, Algorithms, and Applications, ASA-SIAM Series on Statistics and AppliedProbability, SIAM, Philadelphia, ASA, Alexandria, VA,2007.
[3] RajineSwetha R, B. ShekarBabu, SumithraDevi K.A, A Survey of Various Algorithms for Vlsi Physical Design, World Academy of Science, Engineering and Technology International Journal of Electronics and Communication Engineering Vol:5, No:3,2011
[4] Sharadindu Roy, Samar SenSarma, improvement of the quality of VLSI circuit partitioning problem using genetic algorithm, Journal of Global Research in Computer Science, , Volume 3, No. 12, pp. 18-22,2012.
[5] Ramalakshmi and S. Saravanan, Multiple Scan Base Partitioning Technique to Increase the Throughput in VLSI Testing, Indian Journal of Science and Technology, Vol9(29), DOI: 10.17485/ijst/2016/v9i29/90862, August2016
[6] Maninder Kaur , Pradip Kumar Sharma, On solving partition driven standard cell placement problem using firefly-based metaheuristic approach, International Journal of Bio-Inspired Computation,9(2), pp.121–127
[7] Shikha Arora, Neerumalhotra,Rajan Vohra, RajdeepSingh, Hybrid Algorithm PSO and SA in Achieving Partitioning Optimization for VLSI Applications , International Journal of P2P Network Trends and Technology (IJPTT) - Volume 2 Issue 1,pp.1-4,2012
[8] MilonMahapatra, M Malathi and B Srinath. An Interconnectivity based Efficient Partitioning Algorithm of Combinational CMOS Circuits. IJCA Proceedings on National Conference on VLSI and Embedded Systems NCVES(1):18-21, March2013
[9] Indu Saini, Dilbag Singh, ArunKhosla. Detection of QRS-complex using K-nearest neighbor algorithm, Int. J. Medical Engineering and Informatics, 5(1),81-101,2013.
[10] Platt J. Fast Training of Support Vector Machines using Sequential Minimal Optimization. In: Scholkopf B, Burges C, Smola A, editors. Advances in Kernel Methods: Support Vector Learning. Cambridge, MA: MIT Pressn,pp.185–208,1999.
[11] SubhagataChattopadhyay, Dilip Kumar Pratihar, SanjibChandra De Sarkar, A Comparative study of fuzzy c-means algorithm and entropy-based fuzzy clustering algorithms, Computing and Informatics,vol30,pp. 701–720,2011.
[12] Ganesh K. Venayagamoorthyet al., Particle swarm-based optimal partitioning algorithm for combinational CMOS circuits,Engineering Applications of Artificial Intelligence (2006), doi: 10.1016/j.engappai.2006.06.011.
[13] Ratnesh Kumar Shukla,An Introduction of Face Recognition and Face Detection for Blurred and Noisy Images ,International Journal of Scientific Research in Research Paper . Computer Science and Engineering Vol.6, Issue.3, pp.39-43 , June 2018.
[14] T. Dheepak, Low Power Distributed MAC Protocol Against Various Kinds Of Attacks By Using Traffic Analysis Methodology, International Journal of Scientific Research ,Computer Science and Engineering Vol.6, Issue.3, pp. 1-7 , June 2018