The computational complexity of universal hashing

Summary form only given. Any implementation of Carter-Wegman universal hashing from n-b strings to m-b strings requires a time-space tradeoff of TS= Omega (nm). The bound holds in the general Boolean branching program model, and thus in essentially any model of computation. As a corollary, computing a+b*c in any field F requires a quadratic time-space tradeoff, and the bound holds for any representation of the elements of the field. Other lower bounds on the complexity of any implementation of universal hashing are given as well: quadratic AT/sup 2/ bound for VLSI implementation; Omega (log n) parallel time bound on a CREW PRAM; and exponential size for constant depth circuits. The results on VLSI implementation are proved using information transfer bounds derived from the definition of a universal family of hash functions.<<ETX>>

[1]  Yaacov Yesha,et al.  Time-Space Tradeoffs for Matrix Multiplication and the Discrete Fourier Transform on any General Sequential Random-Access Computer , 1984, J. Comput. Syst. Sci..

[2]  Andrew Chi-Chih Yao,et al.  The entropic limitations on VLSI computations(Extended Abstract) , 1981, STOC '81.

[3]  Stephen A. Cook,et al.  Upper and Lower Time Bounds for Parallel Random Access Machines without Simultaneous Writes , 1986, SIAM J. Comput..

[4]  Michael Sipser,et al.  A complexity theoretic approach to randomness , 1983, STOC.

[5]  Shafi Goldwasser,et al.  Private coins versus public coins in interactive proof systems , 1986, STOC '86.

[6]  C. Thomborson,et al.  A Complexity Theory for VLSI , 1980 .

[7]  Noam Nisan,et al.  Constant depth circuits, Fourier transform, and learnability , 1989, 30th Annual Symposium on Foundations of Computer Science.

[8]  J. Spencer Probabilistic Methods in Combinatorics , 1974 .

[9]  Allan Borodin,et al.  A time-space tradeoff for sorting on non-oblivious machines , 1979, 20th Annual Symposium on Foundations of Computer Science (sfcs 1979).

[10]  Ravi B. Boppana,et al.  The Complexity of Finite Functions , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.

[11]  Russell Impagliazzo,et al.  How to recycle random bits , 1989, 30th Annual Symposium on Foundations of Computer Science.

[12]  Allan Borodin,et al.  Parallel Computation for Well-Endowed Rings and Space-Bounded Probabilistic Machines , 1984, Inf. Control..

[13]  Alan Siegel,et al.  On universal classes of fast high performance hash functions, their time-space tradeoff, and their applications , 1989, 30th Annual Symposium on Foundations of Computer Science.

[14]  Tak Wah Lam,et al.  Tradeoffs between communication and space , 1989, STOC '89.

[15]  Karl R. Abrahamson Time-space tradeoffs for branching programs contrasted with those for straight-line programs , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).

[16]  Prasoon Tiwari The communication complexity of distributed computing and a parallel algorithm for polynomial roots , 1986 .

[17]  V. M. Khrapchenko Method of determining lower bounds for the complexity of P-schemes , 1971 .

[18]  Peter Frankl,et al.  Complexity classes in communication complexity theory , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).

[19]  Larry Carter,et al.  Universal Classes of Hash Functions , 1979, J. Comput. Syst. Sci..