Performance issues in dataflow machines

Issues affecting the performance of dataflow computers at the machine and language levels are explored. It is suggested that performance is dictated by the nature and the means of identification, distribution and control of workload in the hardware system. Dataflow is an asynchronous concurrent notation based on fine-grain message-passing in graphical programs. Dataflow machines comprise multiple processing elements and structure store modules connected together via a packet-based switching network. Workload is in the form of finegrain data packets which trigger instruction-level activity in the various components of the hardware architecture. Workload is identified by a compiler for a high-level, single-assignment language, and is distributed across the hardware components dynamically at run-time. The amount of work at any instant can be controlled by a parallelism "'throttle". The paper studies the performance of one example of a dataflow computer, the Manchester Dataflow Machine (MDFM).