Abstract
We describe design and implementation of an abstraction for parallel arrays of data-driven objects. The arrays may be multi-dimensional, and the number of elements in an array is independent of the number of processors. The elements are mapped to processors by a user-controllable mapping function. The mapping may be changed during the parallel computation, which facilitates load balancing, and communication optimization, for example. Asynchronous method invocation is supported, with multicast, broadcast, and dimension-wide broadcast. The abstraction is illustrated using examples in fluid dynamics and molecular simulations.