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Introductory Lecture

This document outlines an introductory course on Linear Algebra and Optimization, covering topics such as linear equations, systems of equations, matrix forms, and solution techniques. It emphasizes the importance of high-performance computing in solving large linear systems and discusses various application areas of linear algebra. The course is structured into five modules, with references provided for further reading.

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lucky Bell
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0% found this document useful (0 votes)
10 views25 pages

Introductory Lecture

This document outlines an introductory course on Linear Algebra and Optimization, covering topics such as linear equations, systems of equations, matrix forms, and solution techniques. It emphasizes the importance of high-performance computing in solving large linear systems and discusses various application areas of linear algebra. The course is structured into five modules, with references provided for further reading.

Uploaded by

lucky Bell
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Linear Algebra and Optimisation


Introductory Lecture

N. Anil
BITS Pilani, Hyderabad Campus
anil@hyderabad.bits-pilani.ac.in

July 27, 2024

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Scope of the Course

This is an introductory course on

• Linear Algebra

• Optimisation

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Introduction to Linear Algebra

What is a linear equation ?

An equation involving one or more variables with constant coefficients

Examples: x = 4, x + y = 1, 2x + y − 3z = 5, etc.

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Introduction to Linear Algebra

What is a linear equation ?

An equation involving one or more variables with constant coefficients

Examples: x = 4, x + y = 1, 2x + y − 3z = 5, etc.

A general form :

a1 x1 + a2 x2 + a3 x3 + · · · + an xn = b

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Introduction to Linear Algebra

What is a system of linear equations ?

Several linear equations involving the same variables

(
x+y =1
Examples:
x−y =3
Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Introduction to Linear Algebra

What is a system of linear equations ?

Several linear equations involving the same variables


(  x+ y+ z =1

x+y =1 
Examples: , x − y + 3z = 3
x−y =3 
2x + 3y − 4z = 5

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Introduction to Linear Algebra

System of linear equations : General form



 a11 x1 + a12 x2 + a13 x3 + · · · + a1n xn = b1

a21 x1 + a22 x2 + a23 x3 + · · · + a2n xn = b2


.. .. ..



 . . .


am1 x1 + am2 x2 + am3 x3 + · · · + amn xn = bm

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Types of Linear System of Equations

A given system of equations can be classified into the following three groups:

• Determined system: Number of equations is same as the number of variables.

• Over-determined system: Number of equations is more than the number of


variables.

• Under-determined system: Number of equations is less than the number of


variables.

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of Equations: Existence and Uniqueness of Solution

Given a system of equations, we have the following possibilities

• Solution exists and it is unique.

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of Equations: Existence and Uniqueness of Solution

Given a system of equations, we have the following possibilities


(
x+y =1
• Solution exists and it is unique. Example:
x−y =3

• Solution exists but there are infinitely many.

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of Equations: Existence and Uniqueness of Solution

Given a system of equations, we have the following possibilities


(
x+y =1
• Solution exists and it is unique. Example:
x−y =3

(
x+ y =2
• Solution exists but there are infinitely many.
2x + 2y = 4

• No solution.

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of Equations: Existence and Uniqueness of Solution

Given a system of equations, we have the following possibilities


(
x+y =1
• Solution exists and it is unique. Example:
x−y =3

(
x+ y =2
• Solution exists but there are infinitely many.
2x + 2y = 4

(
x+y =1
• No solution. Example :
x+y =3

The essence of linear algebra is to investigate the circumstances under which these
scenarios are possible

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of equations : Matrix form

What is the role of Vectors/Matrices in linear algebra ?

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of equations : Matrix form

What is the role of Vectors/Matrices in linear algebra ?

(
x+y =1
Consider the linear system:
x−y =3

Let us define " # " # " #


1 1 x 1
A= , x= and b =
1 −1 y 3
The given system can then be written in the compact form as

Ax = b

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

System of equations : Matrix form

Another example : 
x + y + z = 1


x−y+z =2 (1)


x+y−z =3

Let us define
     
1 1 1 x 1
A = 1 −1 1  , x = y  and b = 2
     

1 1 −1 z 3

Equation (1) can be written as


Ax = b (2)

The solution of the linear system is nothing but the solution of Ax = b

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Solution techniques for Ax = b: Well-known approach

• Solution is given by x = A−1 b

• The solution exists provided A−1 exists

• A−1 = Adj(A)/Det(A)

• A−1 requires the determinant of A

• For large dimensions, computing the determinant is expensive

• Even computer algorithms do not prefer it !

• Need efficient algorithms for the solution of Ax = b !!

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Solution techniques for Ax = b: Alternative approaches

• Consider the following linear system


(
x+y =1
x−y =3

• We can write it as " #" # " #


1 1 x 1
=
1 −1 y 3

• Can we get the following through some manipulations (what are they ?)
" #" # " #
1 1 x 1
=
0 −2 y 2

• Now it is easy to find the solution !

• We Transformed the given matrix to a row echelon form. The first part of the
course deals with some of these basic techniques (Gauss elimination, Gauss
Jordan)

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Solution techniques for Ax = b: Abstract Concepts

Consider the same invertible system


" #" # " #
1 1 x 1
=
1 −1 y 3

• Replace a column vector in the coefficient matrix with any arbitrary vector

• What happens to the solution. Does it exist ?

• Does that vector has any relation with the existing ones. Is it dependent or
independent (what does this mean ??)

• This leads us to the concept of linear independence/dependence of vectors

• The set of vectors with some special properties is a vector space

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Solution techniques for Ax = b: Abstract Concepts

Consider the same invertible system


" #" # " #
1 1 x 1
=
1 −1 y 3

• We generalise: What are those vectors for which the solution exists !

• The concept of vector spaces and related topics precisely deal with it

• What about the eigenvalues and eigenvectors ? Do they say anything about the
nature of the solution or the column vectors ?

• Does the rank of a matrix say anything about the solution ?

• What is the role the coefficient matrix ?

• These abstract concepts give an insight into the nature of the linear system

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Linear Algebra: Role of High Performance Computing

• Solving the linear system by hand is limited to 3 or 4 equations

• Beyond this, use of computers is inevitable

• Small number of equations can be solved on a laptop/desktop

• Large number of equations can be solved on a workstation

• Very large number of equations : Cluster

• Many practical applications involve linear systems with billions of equations.


Need Terascale/Petascale/Hexascale Super Computers !!

Need more sophisticated algorithms that are robust, computationally efficient and can
be applied to very large systems with much ease

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Linear Algebra: Role of High Performance Computing

Computer implementation of algorithms in linear algebra:

• Traditional codes are based on Fortran, C, C++


• With continuous evolution in computer hardware, porting these codes on modern
HPC platforms is a challenging task
• Code developer needs to tune it frequently
• To circumvent this problem, we can use Julia or Regent
• They are architecture independent, ease code maintenance, code readability
• Regent results in Implicitly parallel solver
• Suits to hybrid parallel codes (CPUs+GPUs)

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Linear Algebra: Some of the Application Areas

• Computational biology/chemisty/physics

• Computer graphics, data mining, digital signal processing

• Audio, video and image processing

• Computational Fluid Dynamics

• Computational Structural Mechanics

• Computational Quantum Mechanics

• Computational Finance

• Other related Computational Engineering Science (CES) problems

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Numerical Linear Algebra

Numerical implementation of algorithms in linear algebra:


• Numerical algorithms for the solution of linear systems

• To perform matrix operations, inverse, determinant, eigenvalues, etc.

• Standard software library : LAPACK, LAPACK++

• LAPACK uses BLAS (Basic Linear Algebra Subprograms) libraries

• Matlab, Mathematica, Maple use LAPACK libraries

• MATLAB (Matrix Laboratory) is a fourth generation programming language.


Introduced by Cleve Moler from Univ. New Mexico.

• Apps: Wolfram

• PETSc (Portable, Extensible Toolkit for Scientific Computation)

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Course Description - Linear Algebra

The linear algebra part has five modules:

• Matrices, System of equations, determinants and inverse of a matrix

• Vector spaces and Linear transformations

• Eigenvalues and eigenvectors

• Numerical Linear Algebra: Gauss elimination and iterative methods for solving
linear systems

• Matrix eigenvalue problems and power method for eigenvalue

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Scope of the Course Introduction to Linear Algebra Topics to be covered in Linear Algebra References

Text and Reference books

• Erwin Kreyszig, Advanced Engineering Mathematics, Wiley India, 10th


Edition 2011.

• B. Dubey, Introductory Linear Algebra, Asian Books Pvt Ltd, 2007.

• K Hoffman and R Kunze, Linear Algebra, Pearson Education, 2nd Edition, 2005.

• Elementary linear algebra - S. Andrilli and David Hecker.

• Introduction to linear algebra - G. Strang.

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