In this paper, a very simple model of parallel computation is considered, and the question of how restricting the flow of data to be one way compares with two-way flow is studied. It is shown that the one-way version is surprisingly very powerful in that it can solve problems that seemingly require two-way communication. Whether or not one-way communication is strictly weaker than two-way is an open problem, although the conjecture in this paper is in the positive. It is shown, however, that proving this conjecture is at least as hard as some well-known open problems in complexity theory.

An algorithm for convolving a k*k window of weighting coefficients with an n*n image matrix on a pyramid computer of O(n/sup 2/) processors in time O(logn+k/sup 2/), excluding the time to load the image matrix, is presented. If k= Omega ( square root log n), which is typical in practice, the algorithm has a processor-time product O(n/sup 2/ k/sup 2/) which is optimal with respect to the usual sequential algorithm. A feature of the algorithm is that the mechanism for controlling the transmission and distribution of data in each processor is finite state, independent of the values of n and k. Thus, for convolving two (0, 1)-valued matrices using Boolean operations rather than the typical sum and product operations, the processors of the pyramid computer are finite-state.>

Systolic tree architectures are presented for data structures such as stacks, queues, dequeues, priority queues, and dictionary machines. The stack, queue, and dequeue have a unit response time and a unit pipeline interval. The priority queue also has a unit response time, but the pipeline interval is 2. The response time and pipeline interval for the dictionary machine are O(log n) and O(1), respectively, where n is the number of data elements currently residing in the tree. In each node of the tree, the mechanism for controlling the transmission and distribution of data is finite state. This feature makes the designs presented here suitable for VLSI. If there are n data elements in the data structure, the depth of the tree is O(log n).>

We show that a one-way two-dimensional iterative array of finite-state machines (2-DIA) can recognize and parse strings of any context-free language in linear time. What makes this result interesting and rather surprising is the fact that each processor of the array holds only a fixed amount of information (independent of the size of the input) and communicates with its neighbors in only one direction. This makes for a simple VLSI implementation. Although it is known that recognition can be done on a 2-DIA, previous parsing algorithms require the processors to have unbounded memory, even when the communication is two-way. We also consider the problem of finding approximate patterns in strings, the string-to-string correction problem, and the longest common subsequence problem, and show that they can be solved in linear time on a 2-DIA.

We look at a very simple model of parallel computation and study the question of how restricting the flow of data to be one-way compares with two-way flow. A one-way linear iterative array (1LIA) is a finite one-dimensional array of identical finite-state machines (cells) in which information is allowed to move only in one direction- from left to right. For inputs of length n, the array uses n cells which are initially set to the quiescent state. The serial input, which is applied to the leftmost cell, is accepted if the rightmost cell ever enters an accepting state. We give results which show that 1LIA's are surprisingly very powerful in that they can accept languages which seemingly require two-way communication.