ENV["GKSwstype"]="100" #src

#md # # Who am I ?
#md #
#md #  - My name is *Pierre Navaro*
#md #
#md #  - **Fortran 77 + PVM** : during my PhD 1998-2002 (Université du Havre)
#md #
#md #  - **Fortran 90-2003 + OpenMP-MPI** : Engineer in Strasbourg (2003-2015) at IRMA
#md #
#md #  - **Numpy + Cython, R + Rcpp** : Engineer in Rennes (2015-now) at IRMAR
#md #
#md #  - **Julia v1.0** since July 2018
#md #
#md #  ## Instructions to open the notebook and slides
#md #
#md #  - https://github.com/pnavaro/JuliaSMAI2021
#md #  - https://pnavaro.github.io/JuliaSMAI2021
#md #

#md # ---

#md #
#md # # Why Julia?
#md #
#md # - Started in 2009 and first version was released in 2012.
#md # - High-level languages like Python and R let one explore and experiment rapidly, but can run slow.
#md # - Low-level languages like Fortran/C++ tend to take longer to develop, but run fast.
#md # - This is sometimes called the "two language problem" and is something the Julia developers set out to eliminate.
#md # - Julia's promise is to provide a "best of both worlds" experience for programmers who need to develop novel algorithms and bring them into production environments with minimal effort.
#md #

#md # **Julia: A Fresh Approach to Numerical Computing**
#md # 
#md # *Jeff Bezanson, Alan Edelman, Stefan Karpinski, Viral B. Shah*
#md # 
#md # SIAM Rev., 59(1), 65–98. (34 pages) 2012

# **SciML Scientific Machine Learning Software** https://sciml.ai/citing/
#
# **Differentialequations.jl--a performant and feature-rich ecosystem for solving differential equations in julia,**
# 
# *Christopher Rackauckas and Qing Nie*,
#
# Journal of Open Research Software,, volume 5, number 1, 2017.

#md # ---
