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Published on Apr 10, 2015
Fast and flexible linear algebra in Julia Andreas Noack, MIT CSAIL, firstname.lastname@example.org
Applied scientists often develop computer programs exploratively, where data examination, manipulation, visualization and code development are tightly coupled. Traditionally, the programming languages used are slow, with performance critical computations relegated to library code written in languages on the other side of Ousterhout's dichotomy, e.g. LAPACK. I will introduce the Julia programming language and argue that it is well suited for computational linear algebra. Julia provides features for exploratory program development, but the language itself can be almost as fast as C and Fortran. Furthermore, Julia's rich type system makes it possible to extend linear algebra functions with user defined element types, such as finite fields or strings with algebraic structured attached. I will show examples of Julia programs that are relatively simple, yet fast and flexible at the same time. Finally, the potential and challenges for parallel linear algebra in Julia will be discussed.