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Narendra Karmarkar

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Narendra Krishna Karmarkar
Born1956 (age 67–68)
Alma materIIT Bombay (BTech)
California Institute of Technology (MS)
University of California, Berkeley (PhD)
Known forKarmarkar's algorithm
Scientific career
FieldsMathematics, computing science
InstitutionsBell Labs
Thesis Coping with NP-Hard Problems  (1983)
Doctoral advisorRichard M. Karp[1]

Narendra Krishna Karmarkar (born circa 1956) is an Indian mathematician. Karmarkar developed Karmarkar's algorithm. He is listed as an ISI highly cited researcher.[2]

He invented one of the first provably polynomial time algorithms for linear programming, which is generally referred to as an interior point method. The algorithm is a cornerstone in the field of linear programming. He published his famous result in 1984 while he was working for Bell Laboratories in New Jersey.

Biography

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Karmarkar received his B.Tech in Electrical Engineering from IIT Bombay in 1978, M.S. from the California Institute of Technology in 1979,[3] and Ph.D. in Computer Science from the University of California, Berkeley in 1983 under the supervision of Richard M. Karp.[4] Karmarkar was a post-doctoral research fellow at IBM research (1983), Member of Technical Staff and fellow at Mathematical Sciences Research Center, AT&T Bell Laboratories (1983–1998), professor of mathematics at M.I.T. (1991), at Institute for Advanced study, Princeton (1996), and Homi Bhabha Chair Professor at the Tata Institute of Fundamental Research in Mumbai from 1998 to 2005. He was the scientific advisor to the chairman of the TATA group (2006–2007). During this time, he was funded by Ratan Tata to scale-up the supercomputer he had designed and prototyped at TIFR. The scaled-up model ranked ahead of supercomputer in Japan at that time and achieved the best ranking India ever achieved in supercomputing. He was the founding director of Computational Research labs in Pune, where the scaling-up work was performed. He continues to work on his new architecture for supercomputing.

Work

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Karmarkar's algorithm

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Karmarkar's algorithm solves linear programming problems in polynomial time. These problems are represented by a number of linear constraints involving a number of variables. The previous method of solving these problems consisted of considering the problem as a high-dimensional solid with vertices, where the solution was approached by traversing from vertex to vertex. Karmarkar's novel method approaches the solution by cutting through the above solid in its traversal. Consequently, complex optimization problems are solved much faster using the Karmarkar's algorithm. A practical example of this efficiency is the solution to a complex problem in communications network optimization, where the solution time was reduced from weeks to days. His algorithm thus enables faster business and policy decisions. Karmarkar's algorithm has stimulated the development of several interior-point methods, some of which are used in current implementations of linear-program solvers.

Galois geometry

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After working on the interior-point method, Karmarkar worked on a new architecture for supercomputing, based on concepts from finite geometry, especially projective geometry over finite fields.[5][6][7][8]

Awards

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References

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  1. ^ Narendra Karmarkar at the Mathematics Genealogy Project.
  2. ^ Thomson ISI. "Karmarkar, Narendra K., ISI Highly Cited Researchers". Archived from the original on 23 March 2006. Retrieved 20 June 2009.
  3. ^ "Eighty-Fifth Annual Commencement" (PDF). California Institute of Technology. 8 June 1979. p. 13.
  4. ^ Narendra Karmarkar at the Mathematics Genealogy Project
  5. ^ Karmarkar, Narendra (1991). "A new parallel architecture for sparse matrix computation based on finite projective geometries". Proceedings of the 1991 ACM/IEEE conference on Supercomputing – Supercomputing '91. pp. 358–369. doi:10.1145/125826.126029. ISBN 0897914597. S2CID 6665759.
  6. ^ Karmarkar, N. K., Ramakrishnan, K. G. "Computational results of an interior point algorithm for large scale linear programming". Mathematical Programming. 52: 555–586 (1991).
  7. ^ Amruter, B. S., Joshi, R., Karmarkar, N. K. "A Projective Geometry Architecture for Scientific Computation". Proceedings of International Conference on Application Specific Array Processors, IEEE Computer Society, p. 6480 (1992).
  8. ^ Karmarkar, N. K. "A New Parallel Architecture for Scientific Computation Based on Finite Projective Geometries". Proceeding of Mathematical Programming, State of the Art, p. 136148 (1994).
  9. ^ "Golden Plate Awardees of the American Academy of Achievement". www.achievement.org. American Academy of Achievement.
  10. ^ "Whiz kids rub elbows with right stuff" (PDF). Rocky Mountain News. 30 June 1985.
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