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1 Preferred citation style for this presentation Waraich, Rashid (2008) Parallel Implementation of DEQSim in Java, MATSim Workshop 2008, Castasegna, September

2 Parallel Implementation of DEQSim in Java Rashid Waraich IVT ETH Zurich September 2008

3 Outline Introduction Discrete Event Simulation Parallel Discrete Event Simulation Java DEQSim Implementation Performance Tests Future Work / Challenges 3

4 Simulation in General - Continuous time model - state variables may change continuously - example: change of water temprature, filling up a glass, etc. - Descrete time model (Descrete Event Simulation - DES) - state changes at discrete points in time - examples: queueing system, simulation of customers in shopping mall, simulation of air traffic,... - How to advance simulation time? - fixed-increment time advance (Java Mobsim) - next-event time advance (DEQSim, JDEQSim) 4

5 Fixed-increment Time Advance - Useful, if events occur at fixed length invervals - Wasteful scanning - Accuracy problem / tradeoff E3 E4 E E3 E4 E

6 Next-event Time Advance - Time advancement from event to event - Simulation skips over periods of inactivity - Called event-driven DES E3 E4 E E3 E4 E

7 Parallel Descret Event Simulation (PDES) Why PDES? - DES slow - slow down factor How to make simulation parallel? - partition system into subsystems (logical processes LP), which can be simulated in parallel example: Berlin arrival at 9:45 Zurich Vienna 7

8 PDES (cont.) How to preserve causal order of events? - optimistic algorithms - e.g. Time Warp algorithm - conservative algorithms (DEQSim, Java DEQSim) - LP executes safe events only (e.g. Chandy-Misra algorithm) 8

9 Chandy-Misra Algorithm - Chandy-Misra algorithm - null messages, to prevent deadlock - problem: lots of null messages - need good/large lookahead 7? 6, ? Chandy-Misra example Deadlock 9

10 Java DEQSim - Partition network into Logical Processes (LPs) - Lookahead - Synchronization - Process Events - Synchronization between LPs 10

11 Partitioning (DEQSim) - Orthogonal recursive bisection (same number of events in each zone) - Number of zones is power of 2 - Split in middle of roads 11

12 Partitioning (Java DEQSim) - Partition network vertically, each has own queue - Partition along nodes - Same number of events per zone - Less neighbour zones - Arbitrary number of zones LP 1 LP 2 LP 1 LP 2 LP 3 12

13 Synchronization / Nullmessages / Lookahead - DEQSim only needs to synchronize at certain predefined points in time - Java DEQSim: Uses Chandy-Misra algorithm - lookahead for reducing number of null messages? - plans file knows the future - Synchronization - How handled locking of event process queue - How handeled locking of queues in each zone 13

14 Process Events initial situation (bottleneck: synchronization) CPU 1 CPU 2... synchronized (processevent) CPU N situation now (bottleneck: consumer thread too slow) CPU 1 consumer thread CPU 2... eventbuffer CPU N processevent 14

15 Synchronization between Zones option 1 (synchronized access on queue) owner LP left LP priority queue right LP option 2 (lock only queue, which needed) owner LP owner LP right LP left LP 15

16 Synchronization between Zones (cont.) option 3 (time splitting) owner LP 3s< t <4s 4s< t <5s 5s< t <6s owner LP right LP left LP other ideas? 16

17 Microsimulation Comparison (for Speed) Java MobSim DEQSim Java DEQSim Speed because of programming language Java C++ Java Integrated with rest of MATSim (e.g. no IOoverhead, immediate event handling) Yes No Yes Support for multithreading No Yes Yes Advancement of simulation time Fixed-increment time advance Next-event time advance Next-event time advance 17

18 Performance Tests I 18

19 Performance Tests II 19

20 Future Work / Challenges - Goal: One iteration in 15min, approx. 1M links, 7.2M agents, 4.6 trips in average (with approx. 100 links per trip) currently we would need around 5 hours+ for this on 8 CPUs (with DEQSim) - How to gain more speed up? - How to dimension the number of threads for microsimulation and event handling? - How to do automated performance regression testing? - Optimistic algorithms? - can potentially utilize higher parallelization - simpler for the end user to program simulations - more difficult to implement than conservative algorithms 20

21 How to Gain Speedup? Java MobSim DEQSim Java DEQSim Future? simulation + event handling read + event handling simulation event handling 21

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