Int. J. Adv. Res. Sci. Technol. Volume X, Issue X, 20XX, pp.xx-xx # ICV 5.14 International Journal of Advanced Research in Science and Technology ISSN 2319 – 1783 (Print) ISSN 2320 – 1126 (Online) journal homepage: www.ijarst.com Title of the article in Times New Roman font size 14 Authors Name in Italic, Times New Roman font size 9 Affiliation addresses in Bold Italic, Times New Roman font size 9 *Corresponding Author’s Email: xxxxxxxxx@xxxxxxx.xxx ARTICLEINFO Article history: Received Accepted Available online Keywords: Xxxxxxx, Xxxxxxxxxx, Xxxxx, Xxxxxxxx, xxxxxxxx. ABSTRACT An abstract must accompany each article. It should be a concise summary of the results, conclusions, and/or other significant items in the paper. Together with the title, it must be adequate as an index to all the subjects treated in the paper, and will be used as a base for indexing. Avoid displayed mathematical expressions. Define all nonstandard symbols and abbreviations. Do not use footnote indicators. 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They should be produced with a good quality laser printer and have lines, letters, numbers and symbols of uniform strength and contrast. Figures (except photographs) are often reduced to 5 x 5 cm. The final thickness of a line in a figure usually lies within the range 0.15-0.20 mm. When preparing the figures, authors should pay attention to the widths of lines and similar details, as some (e.g., dotted or thin lines) may disappear after reduction. Particular attention should be paid to line strengths in graphics prepared in vector formats. Sathya. et. al Page | 23 Int. J. Adv. Res. Sci. Technol. Volume X, Issue X, 20XX, pp.xx-xx # ICV 5.14 8. Introduction to parallel computing: design and analysis of algorithms – V. Kumar, A .Grama, A. Gupta, G. Karypis – 1994. 9. Parallel optimization: Theory, algorithms, and applications - Y Censor – 1997. 10. R. A. Finkel, “Large-Grain Parallelism: Three Case Studies”, in the Characteristics of Parallel Algorithms, Ed. L. H. Jamieson, The MIT Press, 1987. Fig: 1. Calculation of Matrix Multiplication Table: 1. The total processing time comparing to single and multithread Matrix Dimension 100 x 100 200 x 200 300 x 300 400 x 400 500 x 500 Single Thread 15 312 1652 6578 17172 Multi Thread-A 31 235 2562 6625 17203 Multi Thread - B 16 171 2000 6609 17093 RSM 12 89 986 4192 8016 Note: Units are in terms of Ms Conclusion: In Revised Simplex method, for problems whose matrix of coefficients contains a large number of zero elements the total amount of computation is reduced. The Revised simplex procedure always deals with the original coefficients, and because the computer codes can be developed to multiply only non-zero elements, the total processing time is greatly reduced when comparing to single and multithread. Also the original non-zero elements can be compactly stored in the computer memory; the original simplex procedure transforms the zero elements to non-zeros as the computational progresses. The total number of computations in the revised simplex method is, in general less than the number in the original method. References: 1. M. Baker, R. Buyya and D. Laforenza, “Grids and Grid technologies for wide-area istributed computing”, Software-Practice and Experience, Vol. 32(15), pp. 1437-1466. 2002. 2. Alexander Schrijver, Theory of Linear and Integer Programming. John Wiley & sons, 1998. 3. Jim Beveridge, Robert Wiener: Multithreading Applications in Win32, Addison-Wesley. 4. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms, Second Edition. MIT Press and McGraw-Hill, 2001. Chapter 29: Linear Programming, pp.770–821. 5. Hamdy A. Taha, Operations Research: An Introduction, Prentice Hall. Eighth edition, 2006. 6. Michael J. Todd (February 2002). "The many facets of linear programming". Mathematical Programming. 7. J. C. Cunha, O. F. Rana and P. D. Medeiros, “Future trends in distributed applications and problem-solving environments” ,Future Generation Computer Systems, Vol. 21(6), pp. 843-855, 2005. www.ijarst.com Sathya. et. al Page | 24