We developed a Functional object-oriented Parallel framework (FooPar) for
high-level high-performance computing in Scala. Central to this framework are
Distributed Memory Parallel Data structures (DPDs), i.e., collections of data
distributed in a shared nothing system together with parallel operations on
these data. In this paper, we first present FooPar's architecture and the idea
of DPDs and group communications. Then, we show how DPDs can be implemented
elegantly and efficiently in Scala based on the Traversable/Builder pattern,
unifying Functional and Object-Oriented Programming. We prove the correctness
and safety of one communication algorithm and show how specification testing
(via ScalaCheck) can be used to bridge the gap between proof and
implementation. Furthermore, we show that the group communication operations of
FooPar outperform those of the MPJ Express open source MPI-bindings for Java,
both asymptotically and empirically. FooPar has already been shown to be
capable of achieving close-to-optimal performance for dense matrix-matrix
multiplication via JNI. In this article, we present results on a parallel
implementation of the Floyd-Warshall algorithm in FooPar, achieving more than
94 % efficiency compared to the serial version on a cluster using 100 cores for
matrices of dimension 38000 x 38000
