RT info:eu-repo/semantics/conferenceObject
T1 MARL-Ped+Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays
A1 Rodríguez Gutiez, Eduardo
A1 Martinez Gil, Francisco
A1 Orduña Huertas, Juan Manuel
A1 González Escribano, Arturo
AB Multi-agent systems allow the modelling of complex, heterogeneous, and distributed systems in a realistic way. MARL-Ped is a multi-agent system tool, based on the MPI standard, for the simulation of different scenarios of pedestrians who autonomously learn the best behavior by Reinforcement Learning. MARL-Ped uses one MPI process for each agent by design, with a fixed fine-grain granularity. This requirement limits the performance of the simulations for a restricted number of processors that is lesser than the number of agents. On the other hand, Hitmap is a library to ease the programming of parallel applications based on distributed arrays. It includes abstractions for the automatic partition and mapping of arrays at runtime with arbitrary granularity, as well as functionalities to build flexible communication patterns that transparently adapt to the data partitions. In this work, we present the methodology and techniques of granularity selection in Hitmap, applied to the simulations of agent systems. As a first approximation, we use the MARL-Ped multi-agent pedestrian simulation software as a case of study for intra-node cases. Hitmap allows to transparently map agents to processes, reducing oversubscription and intra-node communication overheads. The evaluation results show significant advantages when using Hitmap, increasing the flexibility, performance, and agent-number scalability for a fixed number of processing elements, allowing a better exploitation of isolated nodes.
PB Springer
YR 2016
FD 2016
LK http://uvadoc.uva.es/handle/10324/29121
UL http://uvadoc.uva.es/handle/10324/29121
LA eng
NO ICA3PP 2016: Algorithms and Architectures for Parallel Processing
NO Producción Científica
DS UVaDOC
RD 22-nov-2024