Training Videos on Scientific Computing and DEAL.II

DEAL.II

I have written about DEAL.II last year. I intended to try it but never got started. Part of my excuse was unavailability of some good starting tutorials.

Well today that excuse is no more.

Wolfgang Bangerth, Professor in the Department of Mathematics at Texas A&M University and principal author and maintainer of Deal.II, a publicly available Open Source library written in C++ for the numerical solution of partial differential equations has released 40 lectures on how to use Deal.II

These lectures not only talk about how to use deal.ii but also are lectures on which solver to take, which preconditioners to use, adaptive mesh refinement, time dependent problems, parallel computing, using tools such as Visit, Paraview and Eclipse, debugging, etc and all of the topics one encounters in scientific computing.

Click here to view the videos

Here’s the list of the lectures, click on anything that interests you. Must watch for anyone interested in scientific computing!!

Lecture
1

Course overview; why consider existing software libraries

Lecture
2

A real brief overview of deal.II

Lecture
3

Obtaining and installing deal.II

Lecture
4

The building blocks of a finite element code

Lecture
5

step-1, part 1: Simple meshes

Lecture
6

step-1, part 2: Playing with meshes

Lecture
7

Learning to use modern tools, part 1 – Eclipse: an Integrated
Development Environment (IDE), fragment 1

Lecture
8

Learning to use modern tools, part 1 – Eclipse: an Integrated
Development Environment (IDE), fragment 2

Lecture
9

step-2: Degrees of freedom, sparsity in finite element matrices

Lecture
10

step-3: A first Laplace solver

Lecture
11

Learning to use modern tools, part 2 – Visit: a visualization
tool

Lecture
12

A little bit of C++: Templates

Lecture
13

step-4: A dimension-independent Laplace solver

Lecture
14

step-5: Computing on successively refined meshes

Lecture
15

Adaptively refined meshes

Lecture
16

Hanging nodes and other constraints

Lecture
17

step-6: Adaptive meshes

Lecture
18

Debug vs. optimized mode

Lecture
19

Problems with more than one solution variable

Lecture
20

step-20: The mixed Laplace equation

Lecture
21

Block structured solvers for vector-valued problems

Lecture
22

Some data structure design considerations

Lecture
23

Learning to use modern tools, part 3 – doxygen: a documentation
tool

Lecture
24

Best programming practices: Defensive programming and other ways
to avoid bugs

Lecture
25

More on debugging using Eclipse’s built-in debugger

Lecture
26

Time dependent problems: A taxonomy

Lecture
27

Time discretizations for parabolic problems

Lecture
28

Time discretizations for second-order hyperbolic problems

Lecture
29

The step-26 tutorial program — the heat equation. Part 1: The
basics

Lecture
30

The step-26 tutorial program — the heat equation. Part 2:
Adaptive meshes for time dependent problems

Lecture
31

First-order hyperbolic systems

Lecture
32

Learning to use modern tools, part 4 – Paraview, an alternative
visualization tool

Lecture
34

What solver to use

Lecture
35

What preconditioner to use — Introduction and Parts 1+2: Simple
preconditioners for simple problems

Lecture
37

What preconditioner to use — Part 4: Simple preconditioners for
complex problems

Lecture
38

What preconditioner to use — Part 5: Complex
("physics-based"/"block") preconditioners for complex
problems

Lecture
39

Parallelization: Introduction

Lecture
40

Parallelization on a single, shared memory machine

Lecture
42

Beyond computational methods — Part 1: Workflows in scientific
computing

Lecture
43

Beyond computational methods — Part 2: Issues with developing
large software

 

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