'Introduction to Modern Scientific Programming and Numerical Methods' summary by author

Join me as a I summarize a recently published book "Introduction to Modern Scientific Programming and Numerical Methods", CRC Press, 2024, co-authored by me, Dr. Lubos Brieda, and also Prof. Joseph Wang from the USC Viterbi Department of Astronautical Engineering, and Rob Martin, a former colleague of mine from my AFRL days.

This book came out lecture notes for the ASTE-404 class I teach at USC as a part-time faculty member. The motivation for starting the class - and writing this book - was to introduce upper level undergraduate engineering students to the complex world of scientific computing by covering topics beyond the usual "linear systems with Matlab" curriculum encountered in engineering programs. The text covers many different topics having to do with essentially everything that we came across during our own careers as developers of simulation codes.

This includes:
• Numerical integrations, finite difference, linear solvers in Python
• Jacobi and Gauss-Seidel method, Successive Over Relaxation
• Data fitting, filtering, quadrature, non-linear system
• Intro to C++, object oriented programming, operator overloading
• Data visualization using Paraview
• Particle-based Lagrangian simulations, free molecular flow, Direct Simulation Monte Carlo, Particle in Cell
• Eulerian methods, advection-diffusion equation, Crank Nicolson, streamfunction-vorticity method
• The Finite Volume method
• HTML and Javascript interactive applications, canvas, WebGL
• debugging, software libraries, verification and validation, sensitivity analysis, version control, unit testing
• LaTeX
• Parallel programming with multithreading, MPI, and CUDA
• Optimization, machine learning, back propagation
• Arduino microcontrollers, FPGAs,
• Summary of Fortran 77 syntax.

We hope you find this text useful! Please leave a comment or reach out over email with any questions.

Contents:
00:00 Introduction
02:04 Chapter 1: Scientific Computing Basics
07:13 Chapter 2: Finite Difference and Linear Algebra
11:12 Chapter 3: Numerical Analysis
13:13 Chapter 4: Introduction to C++
19:48 Chapter 5: Kinetic Methods
23:14 Chapter 6: Eulerian Methods
30:25 Chapter 7: Interactive Applications
38:08 Chapter 8: Software Engineering
41:20 Chapter 9: High Performance Computing
48:12 Chapter 10: Optimization and Machine Learning
52:10 Chapter 11: Embedded Systems
57:10 Appendix: Fortran 77 Syntax
57:56 Outro

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