Julia is a general-purpose, high-level, dynamic language, designed from the start to take advantage of techniques for executing dynamic languages at statically-compiled language speeds. As a result the language has a more powerful type system, and generally provides better type information to the compiler.
Julia is especially good at running MATLAB and R-style programs. Given its level of performance, we envision a new era of technical computing where libraries can be developed in a high-level language instead of C or FORTRAN. We have also experimented with cloud API integration, and begun to develop a web-based, language-neutral platform for visualization and collaboration. The ultimate goal is to make cloud-based supercomputing as easy and accessible as Google Docs.
View a Google Docs version of the slides HERE.
About the speaker:
Jeff Bezanson has been developing the Julia language for two and a half years with a small distributed team of collaborators. Previously, he worked as a software engineer at Interactive Supercomputing, which developed the Star-P parallel extension to MATLAB. At the company, Jeff was a principal developer of "M#", an implementation of the MATLAB language running on .NET. He is now a second-year graduate student at MIT. Jeff received an A.B. in Computer Science from Harvard University in 2004, and has experience with applications of technical computing in medical imaging.
Email: bezanson (at) mit.edu