diff --git a/_posts/2018-10-25-osg-user-school.md b/_posts/2018-10-25-osg-user-school.md new file mode 100644 index 00000000..aec8969a --- /dev/null +++ b/_posts/2018-10-25-osg-user-school.md @@ -0,0 +1,89 @@ +--- +title: "OSG User School 2018" +date: 2018-10-25 12:00:00 -0600 +categories: School +--- + +The OSG User School 2018 was held at the University of Wisconsin–Madison on July 9–13. This year’s event set a new +record with 65 participants in total, up from 56 participants in 2017. And due to the large and record-setting number +of applicants, 140, it was also one of the most selective offerings of the School. + +Participants included mostly graduate students, post-doctoral researchers, a couple of advanced undergraduates, some +faculty, and some research staff from research institutions in the United States (and one each from Brazil, South Korea, +and Uganda). The range of scholarly domains was very diverse, including physics, biology, chemistry, medicine, several +branches of engineering, statistics, earth sciences, animal sciences, plant sciences, neuroscience, and economics. +Participants were selected by demonstrating need for large-scale computing and by being in a position to transform their +scholarly work through computation. The instructors this year were Brian Lin, and Derek Weitzel from the OSG; Bala +Desinghu, from Rutgers University (and formerly OSG staff); plus Christina Koch and Lauren Michael from the UW–Madison’s +Center for High Throughput Computing. + +This year’s curriculum continued the tradition of focusing on hands-on practice with a wide variety of user tools, +providing a solid grounding for advanced and theoretical topics later in the School as well as further learning +afterward. Much of the curriculum was carried over from 2017, with minor updates to stay current. This year, though, +there was more discussion about accessing different kinds of computing resources, such as graphics-processing units +(GPUs), and about expanding resource pools using commercial clouds, such as Amazon EC2. The larger changes reflected +both changes in the technologies involved plus improved pedagogical approaches based on experiences with past OSG User +Schools and other science end-user engagements. + +All of the training materials from the School remain available online after the event, to be available to others around +the world and to serve as reference material. Participants also received several clear options for getting ongoing help +with their large-scale computing needs. Plus, every participant left the School with at least two ways to run jobs — an +account on a UW–Madison HTCondor submit node and an OSG Connect account — so that there are as few barriers to computing +and storage resources as possible. + + +
+ Participants of the OSG User School 2018 +
Participants of the OSG User School 2018.
+
+ +From formal training evaluations to informal comments and emails, the School was clearly a success. Participants were +happy with the program, with how much they learned, and with the new paths that are now open to them. Further, many +participants completed a final written assignment after the event, describing a research computing challenge and their +plans for applying material from the School to handle the challenge using distributed high throughput computing. From +these assignments, it is clear that most participants have concrete, realistic plans to advance their research through +computing, and many have already begun doing so. + +As it takes time for the full effect of the School training to be realized — for research and computing plans to be +made, for planned work to be performed, and for results to be analyzed and written — we list here the known +publications from 2017 School participants using OSG: + +**Patrick Forscher** (University of Arkansas) and colleagues investigated whether PI names on NIH R01 grant proposals +could induce race or gender bias, the statistical sensitivity analysis for which used about 20,000 hours of computing on +OSG. The first resulting publication is: + +* Forscher, P. S., Cox, W. T. L., Brauer, M., & Devine, P. G. (in press). An experiment manipulating Principal + Investigator names finds little to no race or gender bias in the initial reviews of NIH R01 grant proposals. _Nature + Human Behaviour._ + +**Ariella Gladstein** (University of North Carolina at Chapel Hill) used whole-chromosome simulations to infer the +demographic history of the Ashkenazi Jews with Approximate Bayesian Computation and, as part of that work, developed a +tool (SimPrily) to perform such simulations and calculate population genetic summary statistics. This work was enabled +by using approximately 7 million hours of computing on OSG, XSEDE, University of Arizona, and University of Wisconsin +resources. The first two resulting publications are: + +* Gladstein, A. L., & Hammer, M. F. (2018). _Substructured population growth in the Ashkenazi Jews inferred with + Approximate Bayesian Computation._ Manuscript submitted for publication. + +* Gladstein, A. L., Quinto-Cortés, C. D., Pistorius, J. L., Christy, D., Gantner, L., & Joyce, B. L. (2018). SimPrily: + A Python framework to simplify high-throughput genomic simulations. _SoftwareX, 7,_ 335–340. + + +**Raymond Tsang** (Pacific Northwest National Laboratory) generated toy models for evaluating the suitability of various +Bayesian priors for radioassay measurement results in projecting sensitivity of low-background experiments. This work +was enabled through the use of approximately 80,000 hours of computing on OSG. The first resulting publication is: + +* Tsang, R. H. M., Arnquist, I. J., Hoppe, E. W., Orrell, J. L., & Saldanha, R. (2018). _Treatment of material + radioassay measurements in projecting sensitivity for low-background experiments._ Manuscript submitted for + publication. [arXiv:1808.05307v2](https://arxiv.org/abs/1808.05307) + +**Sarah Turner** (University of Wisconsin–Madison) processed hundreds of images and completed thousands of permutation +tests for quantitative loci mapping of forty traits of carrot to help improve breeding and genetic studies. This work +used about 900 hours of computing on OSG, showing that it does not necessarily take a large number of computing hours to +make a meaningful difference in research outcomes. The first resulting publication is: + +* Turner, S. D., Ellison, S. L., Senalik, D. A., Simon, P. W., Spalding, E. P., & Miller, N. D. (2018). _An automated, + high-throughput image analysis pipeline enables genetic studies of shoot and root morphology in carrot (Daucus carota + L.)._ Manuscript submitted for publication. + +-- Tim Cartwright diff --git a/assets/images/osg-user-school-2018.png b/assets/images/osg-user-school-2018.png new file mode 100644 index 00000000..be686d24 Binary files /dev/null and b/assets/images/osg-user-school-2018.png differ