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DTSTART:19700308T020000
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DTSTAMP:20181221T160726Z
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DTSTART;TZID=America/Chicago:20181111T140000
DTEND;TZID=America/Chicago:20181111T140300
UID:submissions.supercomputing.org_SC18_sess160_ws_whpc108@linklings.com
SUMMARY:High Performance Computing in Dynamic Traffic Simulation
DESCRIPTION:Workshop\nDiversity, Education, Hot Topics, Workshop Reg Pass\
 n\nHigh Performance Computing in Dynamic Traffic Simulation\n\nUgirumurera
 , Gomes, Li, Bayen\n\nDynamic traffic simulation enables to emulate the tr
 affic congestion, which is a necessary aspect of traffic evolution.  Howev
 er, dynamic traffic simulations must compute in seconds if they are to be 
 used in real-time traffic management systems. High performance computing (
 HPC) resources provide the power and computation to significantly speed up
  these simulations, thus enabling their use in instantaneous traffic contr
 ol.\n\nMacroscopic dynamic simulation uses continuum traffic-flow models t
 hat are based on traffic volume, density and speed. Though there have been
  many works that apply parallel computation in HPC for agent-based microsc
 opic dynamic simulation, parallel macroscopic simulation has not been stud
 ied adequately. Hence, we devised a parallel strategy for the Berkeley Adv
 anced Traffic Simulator (BeATS), which a simulation framework for macrosco
 pic dynamic simulation. Given n cores, the parallel simulation begins by h
 aving the root core (processor 0) partitioning the network into n minimum-
 cut partitions using the METIS program. Core i loads the ith partition and
  computes the corresponding traffic states. The cores use graph-based MPI 
 interface to communicate boundary information to other cores that have adj
 acent network partitions. \n\nWe implemented the parallel BeATS simulator 
 on Cori supercomputer at NERSC (nersc.gov).  The parallel BeATS simulator 
 was tested on a synthetic grid network with 2500 nodes, 10000 links, and o
 ver 600 origin-destination pairs. Results showed linear speed-up as the nu
 mber of compute cores grew from 1 up to 8 cores. The simulation time was r
 educed from 28 minutes to 25 seconds with 256 cores.
URL:https://sc18.supercomputing.org/presentation/?id=ws_whpc108&sess=sess1
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