Scientific Computing With Perl*
Perl is use widely by scientists and engineers to solve various scientific computing problems, including linear algebra, differential equations and various kinds of minimization problems. In this talk, we will show how to solve various common problems with CPAN modules along with suggestions for best practices. This allows rapid development while avoiding the need to manage memory.
Perl is use widely by scientists and engineers to solve various scientific computing problems, including linear algebra, differential equations and various kinds of minimization problems. The ability to quickly change and prototype algorithms coupled with not needing to manage memory make Perl well-suited to the task at hand.
First we will explore the various scientific computing CPAN modules in each niche, including biology, astronomy, mathematics and physics. Then, more in-depth examples will be given about how to use Math::GSL, the Perl interface to the GNU Scientific Library. The GSL is a vast library written in C that offers thousands of functions to solve problems in linear algebra, special functions, simulated annealing, integration and many others.
Using the GSL via Perl with Math::GSL allows scientists and engineers access to fast routines written in C from Perl, which allows for rapid prototyping and does not require memory management by the developer.
Jonathan "Duke" Leto is the root commit of the PDX Git Together and has given many presentations about Git, Perl, Twitter, scientific computing, the rise of social coding and various other nerdy things.
I have given this talk before to Perl Mongers many years ago. This talk will have some of the same material, but will also go over many new CPAN modules which have come out recently.
Open Source Bridge
Duke is also a mentor and org admin for Parrot Foundation in Google Summer of Code 2013.