2022/04/13 by Volker Wenzel, Wenzel, Volker, Lars Bauer +5
Computer Science · #Cloud Computing and Resource Management #Constraint Satisfaction and Optimization #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Multiagent Systems (cs.MA)
paper · pdf · doi:10.48550/arxiv.2204.06603
openalex publication_date 2022/04/13 · openalex created_date 2022/04/19 · openalex updated_date 2026/07/28
For efficiency reasons, manycore systems are increasingly heterogeneous, which makes the mapping of complex workloads a key problem with a high optimization potential. Constraints express the application requirements like which core type to choose, how many cores to choose, exclusively or non-exclusively, using a certain core, etc. In this work, we propose a decentralized solution for solving application resource constraints by means of an agent-based approach in order to obtain scalability. We translate the constraints into a Distributed Constraint Optimization Problem (DCOP) and propose a local search algorithm RESMGM to solve them. For the first time, we demonstrate the viability and efficiency of the DCOP approach for heterogeneous manycore systems. Our RESMGM algorithm supports a far wider range of constraints than state-of-the-art, leading to superior results, but still has comparable overheads w.r.t. computation and communication.