Large-scale urban traffic simulation with Scala and high-performance computing system

Abstract High-performance computing systems make it possible to implement large-scale simulations of natural phenomena. However, in order to develop efficacious and efficient solutions, easy-to-use software platforms and applications are required. Up until now, the most popular solutions in this area were based on the message passing interface. Next, the authors successfully tackled this problem using Erlang; now, we focus on Scala/Akka — a popular and widely used standard in parallel and distributed programming. The paper focuses on the scalable implementation of a traffic simulation system in an asynchronous and notably desynchronized way. In addition to describing the concept of the system, a series of experiments on a cluster of up to 1000 nodes (24,000 cores) is presented and discussed, showing the efficiency and scalability. The main aim of the paper is to show that the implementation of high-performance computing-grade software solutions lies at the hand of any programmer proficient in Java Virtual Machine-related technologies.

[1]  Carl Hewitt,et al.  A Universal Modular ACTOR Formalism for Artificial Intelligence , 1973, IJCAI.

[2]  Toyotaro Suzumura,et al.  Performance optimization for agent-based traffic simulation by dynamic agent assignment , 2015, 2015 Winter Simulation Conference (WSC).

[3]  Bartosz Balis,et al.  Using an Actor Framework for Scientific Computing: Opportunities and Challenges , 2016, Comput. Informatics.

[4]  Roberto Palmieri,et al.  Hyflow2: a high performance distributed transactional memory framework in scala , 2013, PPPJ.

[5]  Reza S. Abhari,et al.  GEMSim: A GPU-accelerated multi-modal mobility simulator for large-scale scenarios , 2019, Simul. Model. Pract. Theory.

[6]  Aamir Shafi,et al.  Towards Scalable Java HPC with Hybrid and Native Communication Devices in MPJ Express , 2015, International Journal of Parallel Programming.

[7]  Toyotaro Suzumura,et al.  Multi-modal traffic simulation platform on parallel and distributed systems , 2014, Proceedings of the Winter Simulation Conference 2014.

[8]  Jeffrey M. Squyres,et al.  Design and implementation of Java bindings in Open MPI , 2016, Parallel Comput..

[9]  M. Schreckenberg,et al.  Microscopic Simulation of Urban Traffic Based on Cellular Automata , 1997 .

[10]  Alexey Cheptsov,et al.  HPC in Big Data Age: An Evaluation Report for Java-Based Data-Intensive Applications Implemented with Hadoop and OpenMPI , 2014, EuroMPI/ASIA.

[11]  R. Jayakrishnan,et al.  A distributed, scalable, and synchronized framework for large-scale microscopic traffic simulation , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[12]  Serge P. Hoogendoorn,et al.  Genealogy of traffic flow models , 2015, EURO J. Transp. Logist..

[13]  Wojciech Turek Erlang-based desynchronized urban traffic simulation for high-performance computing systems , 2018, Future Gener. Comput. Syst..

[14]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[15]  Scott Shenker,et al.  Spark: Cluster Computing with Working Sets , 2010, HotCloud.

[16]  Martin Odersky,et al.  An Overview of the Scala Programming Language , 2004 .

[17]  Geoffrey C. Fox,et al.  Java thread and process performance for parallel machine learning on multicore HPC clusters , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[18]  Michael Lees,et al.  An Asynchronous Synchronization Strategy for Parallel Large-scale Agent-based Traffic Simulations , 2015, SIGSIM-PADS.

[19]  Margaret O'Mahony,et al.  Parallel implementation of a transportation network model , 2005, J. Parallel Distributed Comput..

[20]  Kay W. Axhausen,et al.  The Multi-Agent Transport Simulation , 2016 .

[21]  Milenko Vrtic,et al.  Towards a Microscopic Traffic Simulation of All of Switzerland , 2002, International Conference on Computational Science.

[22]  Anthony Ventresque,et al.  dSUMO: towards a distributed SUMO , 2013 .

[23]  Yun-Pang Flötteröd,et al.  Microscopic Traffic Simulation using SUMO , 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

[24]  Thomas Sterling,et al.  High Performance Computing: Modern Systems and Practices , 2017 .

[25]  Kai Nagel,et al.  Microscopic Traffic Modeling on Parallel High Performance Computers , 1994, Parallel Comput..

[26]  Daniel Merkle,et al.  Group communication patterns for high performance computing in scala , 2014, FHPC '14.

[27]  Kai Nagel,et al.  Dynamic traffic assignment on parallel computers in TRANSIMS , 2001, Future Gener. Comput. Syst..