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- W2098919005 abstract "Stochastic processes are used to study the dynamics of evolution in finite, structured populations. Simulations of such processes provide a useful tool for their study, but are currently limited by computational speed and memory bottlenecks, even when naively parallelized. This thesis proposes two novel parallelization methods for simulating a particular class of evolutionary processes known as “games on graphs.” The theoretical speed-up and scalability of these methods is analyzed across various parameters. A novel approximate parallel method is also proposed, which allows for further speed-up at the expense of some accuracy. Discussion of implementation considerations follows, and a resulting implementation in Python is used to provide empirical performance results which match closely with theoretical ones. Applications are suggested for a variety of open problems in biology, behavioral economics, political science, and linguistics." @default.
- W2098919005 created "2016-06-24" @default.
- W2098919005 creator A5014953306 @default.
- W2098919005 date "2015-04-08" @default.
- W2098919005 modified "2023-09-27" @default.
- W2098919005 title "Building N Birds With 1 Store: Parallel Simulations of Stochastic Evolutionary Processes" @default.
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- W2098919005 hasPublicationYear "2015" @default.
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