Conclusions¶
Julia¶
- well-designed open-source scientific programming language
- great numeric types, libraries
- great general-purpose types, libraries
- modern, dynamic, flexible
- roughly as fast as compiled C
- easy learning curve
- dynamism and metaprogramming make new things possible
- solves the two-language problem: from tinkering to HPC
Didn't cover¶
- parallel computing
- general-purpose libraries: Strings, Sets, Arrays, Tuples, Dicts, Time, Streams, Network, Tasks,...
- documentation
- installation
- required libraries: LLVM, OpenBLAS, LAPACK, ARPACK, FFTW, GNU arb-size int & float, ...
- calling C and Fortran
- modules and package manager
- documentation
- code hosting on git
- running Julia on JuliaBox or from command-line
Acknowledgements¶
- David Sanders, Physics, Universidad Nacional Autónoma de México
- Andreas Noack, CS and AI Lab, MIT
- The Julia team
- NSF grant #1554149