Compile-Time Scheduling of Dynamic Contructs in Dataflow Program Graphs

Abstract

Scheduling data ow graphs onto processors consists of assigning actors to processors, ordering their execution within the processors, and specifying their firing time. While all scheduling decisions can be made at runtime, the overhead is excessive for most real systems. To reduce this overhead, compile-time decisions can be made for assigning and/or ordering actors on processors. Compile-time deci- sions are based on known profiles available for each actor at compile time. The profile of an actor such as the execution time and the communication patterns. However, a dynamic construct within a macro actor, such as a conditional and a data-dependent iteration, makes the profile of the actor unpredictable at compile time. For those constructs, we propose to assume some profile at compile-time and define a cost to be minimized when deciding on the profile un- der the assumption that the runtime statistics are available at compile-time. Our decisions on the profiles of dynamic constructs are shown to be optimal under some bold as- sumptions, and expected to be near-optimal in most cases. The proposed scheduling technique has been implemented as one of the rapid prototyping facilities in Ptolemy. This paper presents the preliminary results on the performance with synthetic examples.