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A Bayesian Inference Benchmark Suite
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README.md
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setup.R

README.md

BayesSuite

BayesSuite

A Bayesian Inference Benchmark Suite

If you find BayesSuite useful, please cite our paper:

Yu Wang, Yuhao Zhu, Glenn G. Ko, Brandon Reagen, Gu-Yeon Wei, and David Brooks. “Demystifying
Bayesian Inference Workloads.” International Symposium on Performance Analysis of Systems and
Software (ISPASS), 2019.

The paper profiles the computational characteristics of BayesSuite using single-core and multi-core CPU. It also has a last level cache miss prediction model based on the model and the datasets.

Workloads

Name Model Application
12cities Poisson Regression Does lowering speed limits save pedestrian lives?
ad Logistic Regression Advertising attribution in the movie industry
ode Friberg-Karlsson Semi-Mechanistic Solving ordinary differential equations of non-linear systems
memory Hierarchical Bayesian Modeling memory retrieval in sentence comprehension
votes Hierarchical Gaussian Processes Forecasting presidential votes
tickets Logistic Regression Do police officers alter the ticket writing to match departmental targets?
disease Logistic Regression Measuring the continually worsening progression of Alzheimer’s disease
racial Hierarchical Bayesian Testing for racial bias in vehicle searches by police
butterfly Hierarchical Bayesian Estimating butterfly species richness and accumulation
survival Cormack-Jolly-Seber Estimating animal survival probabilities

Getting Started

  1. After git clone this repo, please run
git submodule init
git submodule update
  1. To create BayesSuite and generate run scripts
cd scripts
bash start.sh
  1. To install R packages
Rscript setup.R

Trouble Shooting

If getting publickey issues when running git submodule update, you need to generate a new SSH key and add it to the ssh-agent and add the new SSH key to your GitHub account.

Licensing

All of the example models are copyrighted by their author(s). The scripts in this repository are under Apache License 2.0.

Yu (Emma) Wang 3/14/2019

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