RETRAN: a recurrent paradigm for massively parallel array computing

An applicative paradigm of parallel array processing based on recurrence relations and a data-parallel overloading of constants is presented. It is shown that the suggested principle of anti-currying together with introduction of function-based, eager arrays result in a denotational system superior to array extensions of pragmatic languages in that it can exploit spatial symmetries of arrays to unify the notation. The main novelty here is completely asynchronous treatment of arrays of arrow types (arrays of possibly array-valued functions) which lends itself nicely to a massively parallel data-flow implementation with yet static scheduling due to the imposed strictness of the array constructor. The evolution of data is defined in the tradition form of stream transformation.<>