Abstract
Linda is a coordination language inverted by David Gelernter at Yale University, which when combined with a computation language (like C) yields a high-level parallel programming language for MIMD machines. Linda is based on a virtual shared associative memory containing objects called tuples. Skeptics have long claimed that Linda programs could not be efficient on distributed memory architectures. In this paper, we address this claim by discussing C-Linda's performance in solving a particular scientific computing problem, the shallow water equations, and make comparisons with alternatives available on various shared and distributed memory parallel machines.