The traditional argument for applicative languages has been programmability. Indeed, due to high‐level abstractions and the implicit parallelism provided by applicative languages, programmers are free to concentrate on the implementation of the algorithm at hand without being burdened with low‐level machine execution details. However, it has long been believed that the implementation and raw performance of applicative languages would be their downfall. We report here that it is easy to deliver both programmability and performance through applicative programming. To demonstrate the viability of applicative programming in the context of parallel computing, quantitative results from an experiment which consists of developing a multigrid elliptic Partial Differential Equation (PDE) solver are presented.