March 4, 2014 Dr. Faming Liang Professor Statistics Texas A&M University Title: A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data Abstract: Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their compute-intensive nature, which typically require a large number of iterations and a […]
January 23, 2014 Matthias Katzfuss Assistant Professor Department of Statistics Texas A&M University Title: Statistical inference for massive distributed spatial data using low-rank models Abstract Due to rapid data growth, it is becoming increasingly infeasible to move massive datasets, and statistical analyses have to be carried out where the data reside. If several datasets stored in separate […]
January 21, 2014 Dr. Edward R. Dougherty Robert M. Kennedy ’26 Chair Director, Center for Bioinformatics and Genomic Systems Engineering Distinguished Professor, Department of Electrical and Computer Engineering Texas A&M University Title: The Impoverishment of Scientific Education Abstract There are two basic questions concerning scientific education: What is the aim of education? And how does the […]
Xingfu Wu Abstract Using Parallel R can significantly shorten the time for spending waiting for experimental results. Why parallel programming with R Parallel R Packages Basic concepts of popular Rmpi and snow packages How to use Rmpi to parallelize a R program Some examples using Rmpi and snow Try to parallelize your own code […]
STAPL April 18, 2013 2:30 p.m. Nathan Thomas Abstract In this talk, I will provide an overview of the major components of STAPL and demonstrate how they can be used to compose a parallel application with scalable performance. I then show performance evaluation for a collection of generic parallel algorithms and applications written using STAPL. […]