Buffer Minimization for Rate-Optimal Scheduling of Synchronous Dataflow Graphs on Multicore Systems

2016 ◽  
pp. 325-340 ◽  
Author(s):  
Mingze Ma ◽  
Rizos Sakellariou
Keyword(s):  
Optimal Scheduling ◽  
Multicore Systems ◽  
Dataflow Graphs ◽  
Synchronous Dataflow ◽  
Synchronous Dataflow Graphs ◽  
Buffer Minimization

Code-size-aware Scheduling of Synchronous Dataflow Graphs on Multicore Systems

2021 ◽  
Vol 20 (3) ◽  
pp. 1-24
Author(s):  
Mingze Ma ◽  
Rizos Sakellariou
Keyword(s):  
Scheduling Algorithm ◽  
Digital Signal ◽  
Scheduling Algorithms ◽  
Communication Delays ◽  
Multicore Systems ◽  
Code Size ◽  
Dataflow Graphs ◽  
Synchronous Dataflow ◽  
Synchronous Dataflow Graphs ◽  
Better Than

Synchronous dataflow graphs are widely used to model digital signal processing and multimedia applications. Self-timed execution is an efficient methodology for the analysis and scheduling of synchronous dataflow graphs. In this article, we propose a communication-aware self-timed execution approach to solve the problem of scheduling synchronous dataflow graphs on multicore systems with communication delays. Based on this communication-aware self-timed execution approach, four communication-aware scheduling algorithms are proposed using different allocation rules. Furthermore, a code-size-aware mapping heuristic is proposed and jointly used with a proposed scheduling algorithm to reduce the code size of SDFGs on multicore systems. The proposed scheduling algorithms are experimentally evaluated and found to perform better than existing algorithms in terms of throughput and runtime for several applications. The experiments also show that the proposed code-size-aware mapping approach can achieve significant code size reduction with limited throughput degradation in most cases.

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