This paper presents lower bound results on Boolean function complexity under two different models. The first is an abstraction of tradeoffs between chip area and speed in very large scale integrated (VLSI) circuits. The second is the ordered binary decision diagram (OBDD) representation used as a data structure for symbolically representing and manipulating Boolean functions. These lower bounds demonstrate the fundamental limitations of VLSI as an implementation medium, and OBDDs as a data structure. They also lend insight into what properties of a Boolean function lead to high complexity under these models. Related techniques can be...

This is the nineteenth edition of a (usually) quarterly column that covers new developments in the theory of NP-completeness. The presentation is modeled on that used by M. R. Garey and myself in our book ‘‘Computers and Intractability: A Guide to the Theory of NP-Completeness,’ ’ W. H. Freeman & Co., New York, 1979 (hereinafter referred to as ‘‘[G&J]’’; previous columns will be referred to by their dates). A background equivalent to that provided by [G&J] is assumed, and, when appropriate, cross-references will be given to that book and the list of problems (NP-complete and harder) presented there. Readers who have results they would like mentioned (NP-hardness, PSPACE-hardness, polynomial-time-solvability, etc.) or open problems they would like publicized, should

A vast amount of work has been done in recent years on the design, analysis, implementation and verification of special purpose parallel computing systems. This paper presents a survey of various aspects of this work. A long, but by no means complete, bibliography is given. 1. Introduction Turing [365] demonstrated that, in principle, a single general purpose sequential machine could be designed which would be capable of efficiently performing any computation which could be performed by a special purpose sequential machine. The importance of this universality result for subsequent practical developments in computing cannot be overstated. It showed that, for a given computational problem, the additional efficiency advantages which could be gained by designing a special purpose sequential machine for that problem would not be great. Around 1944, von Neumann produced a proposal [66, 389] for a general purpose storedprogram sequential computer which captured the fundamental principles of...

We present several results regarding randomized one-round communication complexity. Our results include a connection to the VCdimension, a study of the problem of computing the inner product of two real valued vectors, and a relation between \simultaneous" protocols and one-round protocols. Key words. Communication Complexity; One-round and simultaneous protocols; VC-dimension; Subject classications. 68Q25. 1.

Theoretical computer science treats any computational subject for which a good model can be created. Research on formal models of computation was initiated in the 1930s and 1940s by Turing, Post, Kleene, Church, and others. In the 1950s and 1960s programming languages, language translators, and operating systems were under development and therefore became both the subject and basis for a great deal of theoretical work. The power of computers of this period was limited by slow processors and small amounts of memory, and thus theories (models, algorithms, and analysis) were developed to explore the efficient use of computers as well as the inherent complexity of problems. The former subject is known today as algorithms and data structures, the latter computational complexity. The focus of theoretical computer scientists in the 1960s on languages is reflected in the first textbook on the subject, Formal Languages and Their Relation to Automata by John Hopcroft and Jeffrey Ullman. This influential book led to the creation of many languagecentered theoretical computer science courses; many introductory theory courses today continue to reflect the content of this book and the interests of theoreticians of the 1960s and early 1970s. Although

We extend the conventional BDD-based model checking algorithms to verify systems with non-linear arithmetic constraints. We represent each constraint as a BDD variable, using the information from a constraint solver to prune the BDDs by removing paths that correspond to infeasible constraints. We illustrate our technique with a simple example, which has been analyzed with our prototype implementation. 1

The complexity of two problems of distributed computation and decision-making is studied. It is shown that deciding whether two distant agents can arrive at compatible decisions without any communication can be done in polynomial time if there are two possible decisions for each agent, but is NP-complete if one agent has three or more alternatives. It is also shown that minimizing the amount of communication necessary for the distributed computation of a function, when two distant computers receive each a part of the input, is NP-complete. This proves a conjecture due to A. Yao. 1.

Abstract. A new model of computation for VLSI, based on the assumption that time for propagating information is at least linear in the distance, is proposed. While accommodating for basic laws of physics, the model is designed to be general and technology independent. Thus, from a complexity viewpoint, it is especially suited for deriving lower bounds and trade-offs. New results for a number of problems, including fan-in, transitive functions, matrix multiplication, and sorting are presented. As regards upper bounds, it must be noted that, because of communication costs, the model clearly favors regular and pipelined architectures (e.g., systolic arrays).

This paper introduces communicating branching programs, and develops a general technique for demonstrating communication-space tradeoffs for pairs of communicating branching programs. This technique is then used to prove communication-space tradeoffs for any pair of communicating branching programs that hashes according to a universal family of hash functions. Other tradeoffs follow from this result. As an example, any pair of communicating Boolean branching programs that computes matrix-vector products over GF(2) requires communication-space product Ω(n 2), provided the space used is o(n / log n). These are the first examples of communication-space tradeoffs on a completely general model of communicating processes.

A linear array network consists of k + 1 processors P 0 ; P 1 ; : : : ; P k with links only between P i and P i+1 (0 i ! k). It is required to compute some boolean function f(x; y) in this network, where initially x is stored at P 0 and y is stored at P k . Let D k (f) be the (total) number of bits that must be exchanged to compute f in worst case. Clearly, D k (f) k \Delta D(f ), where D(f) is the standard two-party communication complexity of f . Tiwari proved that for almost all functions D k (f) k(D(f) \Gamma O(1)) and conjectured that this is true for all functions. In this paper we disprove Tiwari's conjecture, by exhibiting an infinite family of functions for which D k (f) is essentially at most 3 4 k \Delta D(f ). Our construction also leads to progress on another major problem in this area: It is easy to bound the two-party communication complexity of any function, given the least number of monochromatic rectangles in any partition of the input space. How tight are suc...