This paper initiates the study of communication complexity when the processors have limited work space. The following tradeoffs between number C of communications steps and space S are proved: (1) For multiplying two n×n matrices in the arithmetic model with two-way communication, CS = Θ(n3). (2) For convolution of two degree n polynomials in the arithmetic model with two-way communication, CS = Θ(n2). (3) For multiplying an n × n matrix by an n-vector in the Boolean model with one-way communication, CS = Θ(n2).link_to_subscribed_fulltex
AbstractThis paper establishes time-space tradeoffs for some algebraic problems in the branching pro...
Matrix Mf has entries Mf [x, y] = f (x, y). A submatrix is monochromatic if f is constant on inputs...
Communication complexity studies the amount of communication necessary to compute a function whose v...
AbstractThis paper initiates the study of communication complexity when the processors have limited ...
Abstract. This paper introduces communicating branching programs and develops a general technique fo...
textA central goal of theoretical computer science is to characterize the limits of efficient compu...
We present lower bounds on the amount of communication that matrix multiplication algorithms must pe...
In this paper we propose a new approach to the study of the communication requirements of distribute...
Communication is a universal process by which two or more individuals exchange information. A commun...
Ph.D. Thesis, Computer Science Dept., U. Rochester, Gary L. Peterson, thesis advisor; simultaneously...
In this paper we propose a new approach to the study of the communication requirements of distribute...
To efficiently scale dense linear algebra problems to future exascale systems, communication cost mu...
We derive lower bounds for tradeoffs between the communication C and space S for communicating circu...
We study the effect of limited communication throughput on parallel computation in a setting where t...
This lecture builds on the material from our first lecture, providing more tools for studying commun...
AbstractThis paper establishes time-space tradeoffs for some algebraic problems in the branching pro...
Matrix Mf has entries Mf [x, y] = f (x, y). A submatrix is monochromatic if f is constant on inputs...
Communication complexity studies the amount of communication necessary to compute a function whose v...
AbstractThis paper initiates the study of communication complexity when the processors have limited ...
Abstract. This paper introduces communicating branching programs and develops a general technique fo...
textA central goal of theoretical computer science is to characterize the limits of efficient compu...
We present lower bounds on the amount of communication that matrix multiplication algorithms must pe...
In this paper we propose a new approach to the study of the communication requirements of distribute...
Communication is a universal process by which two or more individuals exchange information. A commun...
Ph.D. Thesis, Computer Science Dept., U. Rochester, Gary L. Peterson, thesis advisor; simultaneously...
In this paper we propose a new approach to the study of the communication requirements of distribute...
To efficiently scale dense linear algebra problems to future exascale systems, communication cost mu...
We derive lower bounds for tradeoffs between the communication C and space S for communicating circu...
We study the effect of limited communication throughput on parallel computation in a setting where t...
This lecture builds on the material from our first lecture, providing more tools for studying commun...
AbstractThis paper establishes time-space tradeoffs for some algebraic problems in the branching pro...
Matrix Mf has entries Mf [x, y] = f (x, y). A submatrix is monochromatic if f is constant on inputs...
Communication complexity studies the amount of communication necessary to compute a function whose v...