How a Christmas-1989 hobby project descended from a teaching language became the default tongue of scientific computing and machine learning — through a decade-long, self-inflicted version migration, a global interpreter lock it still fights, and a benevolent dictatorship that resigned over a walrus.
Scientific-Computing
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The Story of Python -
Fortran Is Not Dead Fortran still runs the world's most important numerical simulations. A deep technical look at why the language endures, how modern Fortran 2008/2018/2023 differs from FORTRAN 77, the parallelism story, the compiler landscape in 2026, and the honest costs of working in the ecosystem.
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MPI Programming Essentials: Collectives, Non-Blocking, and the Traps Nobody Warns You About A working engineer's guide to MPI: the mental model, point-to-point and collective communication, non-blocking patterns, derived datatypes, one-sided RMA, threading levels, MPI-IO, performance traps, and integration with SLURM.
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Julia: High-Performance Scientific Computing A technically deep guide to Julia for engineers and data scientists who already know Python — covering multiple dispatch, JIT compilation, type system, the scientific ecosystem (DifferentialEquations.jl, Flux.jl, Turing.jl), parallel computing, interoperability, and an honest Julia vs Python comparison.