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Agent-based Model Simulation with Twister Bingjing Zhang, Lilian Weng, B649 Term.

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Presentation on theme: "Agent-based Model Simulation with Twister Bingjing Zhang, Lilian Weng, B649 Term."— Presentation transcript:

1 Agent-based Model Simulation with Twister Bingjing Zhang, zhangbj@indiana.eduzhangbj@indiana.edu Lilian Weng, weng@indiana.eduweng@indiana.edu B649 Term Project Presentation

2 Problem Statement Run the agent-based modeling (ABM) [1] simulation in parallel. Reason: Sequential iterations on a single machine are too slow [1] E. Bonabeau. Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99:7280–7287, 2002.

3 Experiment A model simulating Twitter mechanism: – Users are connected through the social network – Each user has a screen of messages from neighbors, and a memory of topics he is interested in. – Users send messages chosen from screen or memory C - capacity of the screen and memory. Pn - probability to introduce a new topic. Pr - probability to re-post a message from the screen. α - the priority of topics in the memory compared to the screen messages, and therefore the probability of posting about the memory topics is αPr.

4 Architecture Design of the Application

5 Broadcasting on Twister Broadcasting – Chain Broadcasting – All-to-all Minimum-spanning Tree

6 Chain Broadcasting Protocol send get ack send Driver Daemon 0 receive handle data send Daemon 1 ack receive handle data send ack receive handle data get ack ack receive handle data get ack send get ack Daemon 2 receive handle data ack receive handle data ack get ack “Handle data” is done by spawning another thread “Send” and “Receive” are done in a manner of “buffer by buffer”

7 MST broadcasting Driver sends data portions to different nodes MST Leaf Node MST Root Node Twister Driver All-to-all-MST Broadcasting Protocal

8 MST Broadcasting Protocol [3] Ernie Chan et, al. Collective Communication: Theory, Practice, and Experience. Concurrency and Computation: Practice and Experience. 2007

9 Implementation: Model Classes

10 Implementation: TwisterMessage public void fromTwisterMessage(TwisterMessage message) throws SerializationException { message.writeInt(a); … } public void toTwisterMessage(TwisterMessage message) throws SerializationException { this.a = message.readInt(); … }

11 Results: Broadcasting Efficiency 80 PG nodes, 2 switches, 50 Iterations, Data Size(Each Iteration) 200KB ~ 200MB, Data Size(Total) 1GB ~ 5GB

12 Results: Simulation Result Validation Memory Length – number of topics in memory Topic Popularity – number of distinct user who have used a certain topic Topic Prevalence – number of posts containing a certain topic

13 Thank you! Question?


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