Distributed communication in ML

We present our experience in implementing a group communication toolkit in Objective Caml, a dialect of the ML family of programming languages. We compare the toolkit both quantitatively and qualitatively to a predecessor toolkit which was implemented in C. Our experience shows that using the high-level abstraction features of ML gives substantial advantages. Some of these features, such as automatic memory management and message marshalling, allowed us to concentrate on those pieces of the implementation which required careful attention in order to achieve good performance. We conclude with a set of suggested changes to both the ML language and the particular implementation we used.