Communication-Aware Heterogeneous Multiprocessor Mapping for Real-time Streaming Systems

Real-time streaming signal processing systems typically desire high throughput and low latency. Many such systems can be modeled as synchronous data flow graphs. In this paper, we address the prob-lem of multi-objective mapping of SDF graphs onto heterogeneous multiprocessor platforms, where we account for the overhead of bus-based inter-processor communi-cation. The primary contributions include (1) an inte-ger linear programming (ILP) model that globally optimizes throughput, latency and cost; (2) low-complexity two-stage heuristics based on a combination of an evo-lutionary algorithm with an ILP to generate either a single suboptimal mapping solution or a Pareto front for design space optimization. In our simulations, the proposed heuristic shows up to 12x run-time efficiency compared to the global ILP while maintaining a 10−6 optimality gap in throughput