Yale University.  
Computer Science.  
     
Computer Science
Main Page
Academics
Graduate Program
Undergraduate Program
Course Information
Course Catalog
Course Web Pages
Research
Our Research
Research Areas
Research Projects
Publications
People
Faculty
Graduate Students
Research and Technical Staff
Administrative Staff
Alumni
Resources
Calendars
Computing Facilities
Yale Computer Science FAQ
Yale Workstation Support
Computing Lab
AfterCollege Job Resource
Department Information
Contact Us
History
Life in the Department
Life About Town
Directions
Job Openings
Faculty Positions
Useful Links
City of New Haven
Yale Applied Mathematics
Yale Faculty of Engineering
Yale University Home Page
Google Search
Yale Info Phonebook
Internal
Internal
 

Theory Talk
Thursday, November 5, 2009
4:00 p.m., AKW 200

Speaker:
René Peralta, National Institute of Standards and Technology (NIST)
Title: Small Circuits for Boolean Functions

Abstract: We consider the problem of building efficient circuits using arithmetic modulo 2. This problem is highly intractable for any meaningful measure of “efficiency”. Thus, we can only hope to develop heuristics. We propose the following approach:

1. find a circuit with as few multiplications as possible; then
2. optimize the linear pieces of this circuit.

The multiplicative complexity of a function is the number of multiplications necessary and sufficient to compute it.

For example, the function: f(x1,x2,x3) = x1x2 + x1x3 + x2x3 can be computed using only one multiplication:



Too easy? Then try the following one using 3 multiplications only:



I will discuss known bounds on the multiplicative complexity of functions. Some of these results are constructive, and thus can be used in the first step of our circuit optimization method.

The second part of the talk considers the problem of optimizing the linear parts of a circuit. In this problem, we are given a binary m-by-n matrix M, and the task is to build a circuit for computing Mx (where x is an n-bit input). It turns out most work in this area makes an implicit assumption that turns out to be false. When one sheds this assumption, it becomes clear that new heuristics are needed. We have coded one such heuristic. I will report on how it fares compared to traditional methods. This is joint work with Joan Boyar, of the University of Southern Denmark.