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1.Course name:FUNDAMENTAL TO COMPUTATIONAL SCIENCE

2. Course code: FCS 0244

3.Academic staff name:

4.Rationality of including course/module into the programme: COURSE CORE

5.Year and semester offered:

6.

Total of Student

Learning Time (SLT)Implementation

Total of Guided and

Independent Learning

L = LectureL T/P O

T = Tutorial

P = Practical

O = Others

7.Credit hour: 4

8.Prerequisite (if any):

Please refer the teaching plan for the following sections:

9. Course Synopsis

10.Learning outcome

12.References

13.Implementations

14. Evaluations

15.Student Learning Time (SLT)

16.Course/module content and SLT for every topic

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TEACHING PLAN

COURSE NAME FUNDAMENTAL TO COMPUTATIONAL SCIENCE

COURSE CODE FCS 0244

CREDIT HOURS 4

PREREQUISITE

COURSE SYNOPSIS

Fundamental concepts of computational science are very useful to every

computer scientist and engineers. This subject prepares the student to

understand and utilize fundamental concepts of computational science such

as precision of numerical representation, error analysis, numericaltechniques, system dynamic models, the modeling process, computer

simulations, parallel and concurrent architectures for hight performance

computing and scientific applications. At the same time, students who take

courses have an opportunity to apply those techniques in a wide range of

application areas, such as: molecular and fluid dynamics, celestial mechanics,

economics, biology, geology, medicine, and social network analysis.

Konsep asas sains pengiraan adalah sangat berguna kepada setiap saintiskomputer dan jurutera. Subjek ini menyediakan pelajar untuk memahami dan

menggunakan konsep-konsep asas sains pengiraan seperti ketepatan

perwakilan berangka, analisis ralat, teknik berangka, model sistem dinamik,

proses pemodelan, simulasi komputer, senibina selari dan serentak untuk

aplikasi pengkomputeran berprestasi tinggi dan saintifik. Pada masa yang

sama, pelajar yang mengambil kursus ini mempunyai peluang untuk

mengaplikasikan teknik dalam pelbagai aplikasi seperti: molekul dan cecair

dinamik, mekanik cakerawala, ekonomi, biologi, geologi, perubatan, dananalisis rangkaian sosial.

LEARNINGOUTCOMES

By the end of this subject, students should be able to:1. Explain the concept of computational science, modeling and simulation.

(A3, C3, LL)

2. Choose an appropriate modeling approach and simulation technique for a

given problem or situation. (A3, C3, LL, CS)

3. Compare parallel and concurrent programming paradigms, recognizing the

strengths and weaknesses of each. (A3, CTPS3, P2)

Di akhir subjek ini, pelajar akan dapat :

1.

Menerangkan konsep sains model pengiraan dan simulasi. (A3, C3)

2.

Memiilih satu pendekatan pemodelan dan teknik simulasi yang sesuai bagi

masalah atau situasi yang diberikan. (A3, C3)

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3. Andreas Hohmann, Peter Deuflhard, Numerical Analysis in Modern

Scientific Computing: An Introduction (Texts in Applied Mathematics,

2010, ISBN: 978-1441929907.

4.

Richard LeSar, Introduction to Computational Materials Science:Fundamentals to Applications, 2013, ISBN : 978-0521845878.

5. Gilbert Strang, Computational Science and Engineering, 2007, ISBN :

978-0961408817.

IMPLEMENTATIONS

i)

Lecture

2 hours per week for 14 weeks (Total = 28 hours)

ii)

Tutorial

2 hours per week for 14 weeks (Total = 28 hours)

EVALUATIONS

Coursework Percentage

Mid Semester Examination 20%

Quiz 10%

Individual Assignment 20%

Group Project 20%

Total Coursework 70%

Final Examination 30%Total 100%

STUDENT LEARNING TIME (SLT)

No. Session Hour Freq.

Official

Contact

SLT

Hours Freq.

Student

Learning

Time

(SLT)

1 Lecture 2 14 28 2 14 28

2 Tutorial/Lab 2 14 28 2 14 28

3 Quiz 0.5 2 1 1 2 2

4 Theoretical Test 2 1 2 8 1 8

5 Lab Test 0 0 0 0 0 0

6 Mini ProjectGroup 0.25 1 0.25 1 1 1

7 Mini Project Individual 0 0 0 0 0 0

9 Assignment Group 0 0 0 0 0 0

10 A i I di id l 0 5 4 2 4 4 16

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WEEKLY SCHEDULE

Week Content Session

1 Introduction to Computational Science LectureLab / Tutorial

2Introduction to Modeling Process, Model Classification

Steps of Modeling Process.

Lecture

Lab / Tutorial

3

Errors Part 1 :

Fundamentals of Errors, Data, Modeling and Implementation

Errors, Precision, Absolute and Relative Errors.

Lecture

Lab / Tutorial

4

Errors Part 2 :

Round-off Error, Overflow and Underflow, Arithmetic Errors,

Error Propagation, Violation of Numeric Properties, Comparison of

Floating Point Numbers, Truncation Error.

LectureLab / Tutorial

5

Rate of Change :

Introduction, Velocity, Derivative, Slope of Tangent Line,

Differential Equations , Second Derivative.

Lecture

Lab / Tutorial

6

Fundamental Concepts of Integral Calculus :

Introduction, Total Distance Traveled and Area, Definite Integral

Total Change, Fundamental Theorem of Calculus, Differential

Equations Revisited.

Lecture

Lab / Tutorial

7 Mid Semester Examination

8 MID SEMESTER BREAK

9

Unconstrained Growth and Decay :

Introduction, Differential Equation, Difference Equation,

Simulation Program, Analytical Solution Introduction,

Indefinite Integrals (with and without ), Completion of Analytical

Solution and Unconstrained Decay.

LectureLab / Tutorial

10

Constrained Growth:

Introduction, Carrying Capacity, Revised Model, Equilibrium and

Stability.

System Dynamic Tools

Lecture

Lab / Tutorial

11 Simulation Technique :Euler's Method, Runge-Kutta 2 Method, Runge-Kutta 4 Method LectureLab / Tutorial

12 System Dynamic ModelsLecture

Lab / Tutorial

13High Permormance Computing :

Concurrent Processing, Parallel Algorithms,

Lecture

Lab / Tutorial

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FUNDAMENTAL TO COMPUTATIONAL SCIENCE (FCS 0244)

Matrix Course LO vs. Faculty PO & Taxonomy

Matrix Course LO vs.

Faculty POMatrix Course LO vs. Taxonomy Level

Faculty PO Cognitive (C) Psychomotor (P) Affective (A)

No. Course LO 1 2 3 4 5 6 7 1 2 3 4 5 6 1 2 3 4 5 6 7 1 2 3 4 5

1Explain the concept of computational

science, modeling and simulation. (A3, C3, LL)

xx x x x x x

2

Choose an appropriate modeling approach

and simulation technique for a given problem

or situation. (A3, C3, LL, CS)

x xx x x x x x

3

Compare parallel and concurrent

programming paradigms, recognizing the

strengths and weaknesses of each. (A3,

CTPS3, P2)

xx x x x x

Subject : FUNDAMENTAL TO

COMPUTATIONAL SCIENCE

x x x x x x x x x x x x

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Matrix LO vs. Soft Skills (LO & SS)

LL CS CTPS ES TPS K TS EM LS

No. Course LO 1 2 3 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 1 2 3 4 1 1 1 2 3 4 5 1 2 3 1 2 3 4

1

Explain the concept of computational

science, modeling and simulation. (A3,

C3, LL)

x

2

Choose an appropriate modelingapproach and simulation technique

for a given problem or situation. (A3,

C3, LL, CS)

x x x

3

Compare parallel and concurrent

programming paradigms, recognizing

the strengths and weaknesses of each.

(A3, CTPS3, P2)

x x x

Subject : FUNDAMENTAL TOCOMPUTATIONAL SCIENCE

x x x x x x