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Details

Karthik Ram will speak on R's role in facilitating open science.

and

Norm Matloff will reprise the Rth portion of his Invited Use-R talk

Agenda:

6:30PM Networking and pizza
7:00 Announcements
7:05 Rth
7:20 R and Open Science
8:30 Event ends

R and open science In recent years the open science movement has gained considerable support among academics and partner organizations such as publishers and grant agencies. In particular, the rise in the number of open access publications and associated data repositories have not just made it possible to reach a wider audience, but also introduce a greater degree of transparency and reproducibility to scientific research. The R statistical language is poised to play a very significant role in the open science movement over the coming years. In addition to being one of the most widely used statistical tools in the academic community, R's popularity is driven primarily by the ever growing suite of user-contributed packages. Many of these packages facilitate rapid data discovery, re-use, visualization, and reproducibility. In this talk I will describe how these new tools play an important role in facilitating open science.

About the presenter: Karthik Ram is currently a postdoctoral fellow in Environmental Science and Policy at UC Berkeley. In addition to carrying out research in population & community ecology, Karthik has been involved in a collaborative effort to develop R based tools to facilitate open science.

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Rth

Rth is a new R package which will be an R interface to Thrust. The latter is in turn an interface NVIDIA provides for CUDA GPU coding, but for which the user also can also take multicore CPU as the backend. Unlike CUDA, OpenCL, OpenMP and the like, Thrust operates at a high level, offering operations as sorting, reduction, prefix sum, search and so on, all usable either on GPUs or multicore CPUs (producing either CUDA or OpenMP code). Rth will thus provide R users will easy access to these operations in a cross-platform manner, much like Magma does for matrices. I will argue that this kind of hybrid approach (if not this particular implementation) may enabling the R community to “hedge their bets” in the face of the uncertain hardware situation.

Norman Matloff is Professor of Computer Science University of California, Davis, a BARUG organizer, author of the book the Art of R Programming (http://www.amazon.com/The-Art-Programming-Statistical-Software/dp/1593273843/ref=sr_1_1?ie=UTF8&qid=1340410632&sr=8-1&keywords=art+of+r+programming), and long-time R champion.