Numbers, Algorithms and Machines: 6 decades of personal computing

Our speaker John Nash has seen the evolution of modern computing as a confluence of people and developments good and bad, lucky and unlucky. While much of computer science has evolved away from (numerical) computing, he has remained in that sphere and contributes to
several progressive efforts. This talk will review the speaker’s journey with personal computers. Specifically in and through the presenters direct experience with the R project which has in the last two decades become the most popular tool for computational statistics, and as a result we can find direct application in ostensibly every related field of research.

Support for this visit arose out of the R-Consortium funded histoRicalg
project. The projects aim is to document, test and possibly re-implement older algorithms that form parts of the underlying computational infrastructure of R and other (numerical) systems. The project has a growing membership of volunteer students and scientists who are interested in numerics and algorithms.

Our intent at Dalhousie is to provide a hands-on workshop to present some of recent progress and early successes related to the histoRicalg project, using short tasks that look at some of the algorithms and explore their peculiarities and features related to their implementation in code.

Dr. Nash, D.Phil. (Oxon.), is the author of several books on scientific and statistical computation, most recently "Nonlinear Parameter Optimization Using R Tools", as well as numerous scientific and popular articles. Since his formal retirement from the University of Ottawa Tefler School of Management, Prof. Nash has been actively working on Free/Libre software initiatives, in particular the R statistical system, in which several of his optimization codes are prominent, and for which he has mentored several Google Summer of Code students and assisted in administering the R component of this initiative.

[1] https://onlinelibrary.wiley.com/doi/book/10.1002/9781118884003
[2] https://gitlab.com/nashjc/histoRicalg
[3] https://archive.org/details/@nashjc
[4] https://r-project.org