Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The library, largely written in Julia itself, also integrates mature, best-of-breed C and Fortran libraries for linear algebra, random number generation, signal processing, and string processing. Put simply, it looks like Matlab, which is simple to learn and familiar to most MRI researchers, but it works better and faster and is completely free. In particular, for the problem of DCE MRI, Julia's simple and flexible parallel computing model allows almost perfect parallelization of the nonlinear least squares fitting problem. In my informal testing, the intrinsic speed of Julia coupled to my parallel implementation produced a factor of 20-40 speedup over comparable Matlab and Python.