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 problem of multi-objective mapping of SDF graphs onto heterogeneous multi-processor platforms. The primary contributions include (1) an integer linear programming (ILP) model that globally optimizes throughput, latency and cost; (2) a low-complexity two-stage heuristic based on a combination of an evolutionary algorithm with an ILP to generate either a single sub-optimal mapping solution or a Pareto front for design space optimization. In our simulations, the proposed heuristic shows a 10−6 gap from the ILP optimal solution, with up to 12x better run-time efficiency.