The Assimilation of Dataflow David E. Culler Computer Science Division University of California, Berkeley Dataflow models of computation, dataflow machines, and dataflow languages have been actively studied and developed over the past fifteen years. This work has been approached as a ``new paradigm'' of computing, i.e, self-consistent and powerful, although the novel machines might be ill-suited to conventional languages and the novel languages ill-suited to conventional machines. The work seemed to be driven by a unique set of critical issues. This talk will discuss how the dataflow paradigm has assimilated into the mainstream of parallel computing and examine the common set of critical issues. First, we will look at how the dataflow language Id90 can be implemented efficiently on conventional distributed memory multiprocessors and address some fundamental shortcomings of dataflow machines in the process. This work involves sophisticated compilation techniques that operate on dataflow graphs to produce a collection of self-scheduling threads. Second, we will look at how latency tolerance can be incorporated into conventional parallel languages. Finally, we will describe a simple communication primitive for parallel machines, called active messages. This provides a basis for these language implementations and more conventional approaches, such as message passing or shared memory.