A fine-grain parallel program is one in which processes are typically small, ranging from a few to a few hun- dred instructions. Fine-grain parallelism arises natu- rally in many situations, such as iterative grid com- putations, recursive fork/join programs, the bodies of parallel FOR loops, and the implicit parallelism in func- tional or dataflow languages. It is useful both to de- scribe massively parallel computations and as a target for code generation by compilers. However, fine-grain parallelism has long been thought to be inefficient due to the overheads of process creation, context switching, and synchronization. This paper describes a software kernel, Distributed Filaments (DF), that implements fine-grain parallelism both portably and efficiently on a workstation cluster. DF runs on existing, off-the-shelf hardware and software. It has a simple interface, so it is easy to use. DF achieves efficiency by using state- less threads on each node, overlapping communication and computation, employing a new reliable datagram communication protocol, and automatically balancing the work generated by fork/join computations.