Implementation-Aware Model Analysis: The Case of Buffer-Throughput Tradeoff in Streaming Applications

Models of computation abstract away a number of implementation details in favor of well-defined semantics. While this has unquestionable benefits, we argue that analysis of models solely based on operational semantics (implementation-oblivious analysis) is unfit to drive implementation design space exploration. Specifically, we study the tradeoff between buffer size and streaming throughput in applications modeled as synchronous data flow (SDF) graphs. We demonstrate the inherent inaccuracy of implementation-oblivious approach, which only considers SDF operational semantic. We propose a rigorous transformation, which equips the state of the art buffer-throughput tradeoff analysis technique with implementation awareness. Extensive empirical evaluation show that our approach results in significantly more accurate estimates in streaming throughput at the model level, while running two orders of magnitude faster than cycle-accurate simulation of implementations.