MATH+ student research group: Graph partitioning for large-scale agent-based simulations S23
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Description

Starting point of this MATH+ student research group is the Vahana framework for large-scale
agent-based models, i.e. models that define a (social) system at the micro level of actors and
their interactions with each other and with their environment. Vahana represents an agent-based
model as an extended synchronous graph dynamical system (SysGDS), where agents are nodes
in the graph and edges determine neighborhoods or interactions. To run large-scale agent-based
models, a simulation must be parallelized, that is, the graph must be partitioned, so that each
computational process is only responsible for updating the states of a subset of the agents. This
research group seminar aims to improve the graph partitioning strategies of Vahana.
 

In this course, small groups of students shall work on
• implementing an example ABM using Vahana; the programming language is Julia
• obtaining an overview of graph partitioning algorithms and the study of one particular algo-
rithm in view of Vahana
• adjusting an algorithm to the extended SysGDS structure and implementing it, again in Julia

Basic Course Info

Course No Course Type Hours
19247511 Seminar 2

Time Span 18.04.2023 - 18.07.2023
Instructors
Steffen Fürst
Steffen Fürst
Sarah Wolf

Study Regulation

0089c_MA120 2014, MSc Informatik (Mono), 120 LPs
0280c_MA120 2018, MSc Mathematik (Mono), 120 LP

MATH+ student research group: Graph partitioning for large-scale agent-based simulations S23
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Main Events

Day Time Location Details
Tuesday 16-18 1.1.26 Seminarraum E1 2023-04-18 - 2023-07-18

MATH+ student research group: Graph partitioning for large-scale agent-based simulations S23
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MATH+ student research group: Graph partitioning for large-scale agent-based simulations S23
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