Computer Architecture and Organization

Computer Architecture and Organization

taught by Dr. Ken Williams

Computer Science department of North Carolina A&T State University

This course explores the design of computer systems and their architectures. Topics include central processing unit architecture, microcode, system interconnections, memory systems, input/output systems, interrupt handling, peripherals and communications networks

Textbook

The textbook for COMP375 Computer Architecture and Organization during the Fall 2008 semester is:

Computer Organization and Architecture: Designing for Performance, Seventh Edition,
by William Stallings, Pearson Prentice Hall, 2006, ISBN: 0131856448

Slides

an Introduction to Architecture

History of Computers Additional information

Assembler Language Additional information

More assembler

Still more assembler

Assembler function calls

Machine language

Memory Access modes

Digital logic

VLSI transistors

Arithmetic

Interrupts

Buses

Memory Technology

Memory Organization

Cache Systems

Cache Mapping

Virtual Memory

Disk operation

RAID disks

I/O controllers

Backing up your data

Microcode 1

Microcode 2

Microcode 3

Microcode 4

Pipelining

Superscalar processors

RISC

Parallel Architectures

SMP Architectures

Benchmarking

Security

Combinatorial Logic

Sequential Logic

Number Representation

Microcode Animation

Microcode Examples PDF format

Cache Simulation PDF format

Example assembler program

Notes on the Powers of 2

Notes on Metric Prefixes

Notes on Byte Ordering

Compulator Simulation

Computer Architecture -1

Introduction to Computer Architecture

taught by Dr. Ken Williams

Computer Science department of North Carolina A&T State University

This course teaches techniques for design and optimization of combinatorial logic circuits, flip-flops, counter, registers and arithmetic concepts necessary to understand computer logic. Additional topics include assembly language programming, interrupt handling, and data representation.

Text Books :

The spring 2009 textbook for COMP370 Introduction to Computer Architecture is

Fundamentals of Computer Organization and Design, by Sivarama P. Dandamudi, Springer publishing, 2003, ISBN: 038795211X

Sylabus :-

Slides

Number bases

Integer representation

Floating Point representation

Character representation

Graphic representation

Logic gates

Boolean logic

Logic Simplification

Arithmetic

Transistors and VLSI

Combinatorial Logic

Logic Arrays

Finite State Automata

FSA Design

Assembler introduction

Assembler statements and ifs

Assembler pointers and arrays

Assembler function calls

Additional assembler information

FSA example: at least three 1’s

FSA example: two or more consecutive zeroes

FSA example: two consecutive zeroes but not three

Powers of 2

Computer Architecture

Advanced Computer Architecture

	Appendix_A .ppt
	Chapter 1.ppt
	Chapter 2.ppt
	Chapter 3.ppt
	Chapter 4.ppt
	Chapter 5.ppt
	Chapter 6.ppt
	Project-1.pdf
	Project-2.pdf

Computational Sciences and Engineering2

Computational Sciences and Engineering

Course Description

Study of computer science techniques and tools that support computational sciences and engineering. Emphasis will be on visualization, performance evaluation, parallel computing, and distributed computing. Prerequisites: CS-115, CS/EE-380, and engineering standing. CS/MA/EGR 537 should be a prerequisite. All graduate students should take 537 before taking this course.

(Picture courtesy of CSEP)

Requirements and Goals

Students need knowledge of programming in a modern object oriented language and a basic knowledge of machine organization and architecture. You need to know how to make presentations in either PowerPoint or Acrobat.

Students will learn about hardware and software support for high performance computing. They will learn to select algorithms and develop code for computing in a parallel (or distributed computing) environment. They will learn about benchmarking, optimization, and visualization. The course will include a hands on component utilizing a parallel computing environment.

Textbook and Course Outline

The course will follow, where still appropriate, the lecture notes of the Computational Science Educational Project (CSEP). The lectures will cover some or all of the topics below. I may allow swapping of team members on a one for one basis as long as I approve it well in advance.

• An Overview of Computational Science (Douglas) 1/21-23
  PowerPoint PDF
• Numerical Linear Algebra (Hickey/Shields) 2/11-20
  PowerPoint PDF
• Computer Architecture (Luo/Muche) 2/20-25
  PowerPoint PDF
• Networks (Holland/Reckner) 2/27-3/4
  Powerpoint PDF
• Cache Designs and Tricks (Douglas) 3/6-11
  PowerPoint PDF
• Some High Performance Computing Issues in PDEs (Douglas) 3/11-13
  PowerPoint PDF
• MPI and OpenMP (Muche/Shields) 3/25
  PowerPoint PDF
• Scientific Visualization in High Performance Computing (Hickey/Holland) 4/8-10
  PowerPoint PDF
• Random Number Generators and Monte Carlo Methods (Luo/Reckner) 4/10
  PowerPoint PDF
  
• Case Study: Ocean Modeling (Douglas) 1/30-2/4
  PowerPoint PDF
• Case Study: Sports Lighting (Douglas) 2/6
  PowerPoint PDF Report: Word PDF
• Case Study: Dust Particle Movement (Douglas) 4/1-3
  PowerPoint PDF
• Case study: Flame Simulation (Douglas) 4/15
  PDF Figures (see Ern, Douglas, and Smooke)
• Case Study: Semiconductor Modeling (Class reading) 4/17
  HTML
• Case Study: Nanomaterials (Hickey/Luo/Muche) 4/22-24
  PowerPoint PDF
• Case Study: Bioinformatics (Holland/Reckner/Shields) 4/29-5/1
  PowerPoint PDF
  

Computational Sciences and Engineering

Computational Sciences and Engineering

Course Description

Study of computer science techniques and tools that support computational sciences and engineering. Emphasis will be on visualization, performance evaluation, parallel computing, and distributed computing. Prerequisites: CS-115, CS/EE-380, and engineering standing.

Publish Post

(Picture courtesy of CSEP)

Requirements and Goals

Students need a knowledge of programming in a modern object oriented language and a basic knowledge of machine organization and architecture.

Students will learn about hardware and software support for high performance computing. They will learn to select algorithms and develop code for computing in a parallel (or distributed computing) environment. They will learn about benchmarking, optimization, and visualization. The course will include a hands on component utilizing a parallel computing environment.

Textbook and Course Outline

The course will follow, where still appropriate, the lecture notes of the Computational Science Educational Project (CSEP). The lectures will cover the following topics:

• An Overview Of Computational Science (Douglas)
  Powerpoint Html
• Scientific Visualization in High Performance Computing (Payne/Hsiao)
  Powerpoint Html
• Networks (Snyder/Petty)
  Powerpoint Html
• Computer Architecture (Petty/Snyder)
  Powerpoint Html
• Cache Designs and Tricks (Douglas)
  Powerpoint Html
• Tutorials for Network and Visualization Tools (Hsiao/Payne)
  Powerpoint Html
• Tutorials for MPI (Satish/Douglas)
  Powerpoint Html
  and OpenMP (Satish/Douglas)
  Powerpoint Html
• Numerical Linear Algebra (Walters/Douglas)
  Powerpoint Html
• Mathematical Optimization (Hsiao/Walters)
  Powerpoint Html
• Ordinary Differential Equations (Carr/Douglas)
  Powerpoint Html
• Some High Performance Computing Issues in PDEs (Douglas/Walters)
  Powerpoint Html
• Random Number Generators (Snyder/Satish)
  Powerpoint Html
• Monte Carlo Methods (Payne/Petty)
  Powerpoint Html
• Case Studies
  • Ocean Models (Snyder)
    Powerpoint Html
  • Chaos from Nonlinear Mappings (Carr)
    Powerpoint Html
  • Mutational Meltdown of Endangered Species (Walters)
    Powerpoint Html
  • Seismic Wave Propagation and Inversion (Petty)
    Powerpoint Html
  • Direct and Inverse Bioelectric Fields Problems (Payne)
    Html
  • Monte Carlo Surface to Surface Particle Transport (Satish/Hsiao)

Computational Number Theory

Computational Number Theory

Authors-
This is a course I have taken at IITK for my MSc credits in CMI. It is offered by Piyush P Kurur. The notes are quite detailed. I missed the first few classes of this course where he discussed the extended euclid's algorithm and an introduction to groups, fields, rings


Click here to download the files :

The source/sty files are available here. Or one could just keep files.tar.gz of the source files and the pdfs. The notes are quite detailed and might contain a lot of typos or big blunders. If you notice something seriously wrong with some parts of the notes, please let me know.

Lecture 5 and 6	:	Chinese Remaindering	[PDF]	[TeX]
Lecture 7	:	Towards Factorization over Finite Fields	[PDF]	[TeX]
Lecture 8	:	More on Finite Fields	[PDF]	[TeX]
Lecture 9	:	Uniqueness of F_q	[PDF]	[TeX]
Lecture 10	:	Distinct Degree Factorization	[PDF]	[TeX]
Lecture 11	:	Cantor-Zassenhaus Algorithm	[PDF]	[TeX]
Lecture 12	:	Berlekamp's Algorithm	[PDF]	[TeX]
(midsem 1 syllabus ends here)
Lecture 13	:	Codes: An Introduction	[PDF]	[TeX]
Lecture 14	:	BCH Codes	[PDF]	[TeX]
		Midsem 1 (and solutions)	[PDF]
Lecture 15 and 16	:	BCH Codes: Error correction	[PDF]	[TeX]
Lecture 17	:	Primality is in NP and coNP	[PDF]	[TeX]
Lecture 18	:	Quadratic Reciprocity	[PDF]	[TeX]
Lecture 19	:	Quadratic Reciprocity (contd.)	[PDF]	[TeX]
Lecture 20 and 21	:	Solovay-Strassen Primality Testing	[PDF]	[TeX]
Lecture 22	:	A Discussion on ERH and Toward AKS	[PDF]	[TeX]
Lecture 23 and 24	:	The Cyclotomic Polynomial	[PDF]	[TeX]
Lecture 25	:	The AKS Primality Test	[PDF]	[TeX]
Lecture 26	:	Hensel Lifting	[PDF]	[TeX]
Lecture 27	:	Bivariate Factorization	[PDF]	[TeX]

And a single file with all the above lectures: here

During our discussion on cyclotomic polynomials over Q, we talked about attempting to write a program to compute the n-th cyclotomic polynomial on input n. I took up the challenge and wrote a program in Haskell to do it. The source is available here.
The name of the function is cyclo. It took about an hour to write the program, and is around 80 lines. I've made the code quite readable and straightforward.

Piyush wrote a Haskell program for it as well. It is very well organized and faster than my program. The tar-zipped source is available here.
Another student Piyush Srivastava wrote a C++ code for the same. The gzipped source is available here.

As a part of the student talks in CMI, I had given a presentation on the AKS Primality test. The pdf of the presentation is available here.

Computational Investigations

Computational Investigations

Introduction to Epigenetics II / Epigenetics of human diseases and computational investigations

Syllabus

	Introduction; Databases Slides (pdf)
	Highthroughput technologies, genomewide DNA methylation profiling Slides (pdf)
	Exploratory analysis and Analysing multivariate genomic data Slides (pdf)
	DNA methylation prediction Slides 1 (pdf) Slides 2(pdf)
	Evolutionary aspects Slides (pdf)
	Prediction of imprinted genes Slides (ppt)
	Deamination followed by Substitution Slides (pdf)

Computational Geometry PDF

Computational Geometry

Course Description

Topics in surface modeling: b-splines, non-uniform rational b-splines, physically based deformable surfaces, sweeps and generalized cylinders, offsets, blending and filleting surfaces. Non-linear solvers and intersection problems. Solid modeling: constructive solid geometry, boundary representation, non-manifold and mixed-dimension boundary representation models, octrees. Robustness of geometric computations. Interval methods. Finite and boundary element discretization methods for continuum mechanics problems. Scientific visualization. Variational geometry. Tolerances. Inspection methods. Feature representation and recognition. Shape interrogation for design, analysis, and manufacturing. Involves analytical and programming assignments.

This course was originally offered in Course 13 (Department of Ocean Engineering) as 13.472J. In 2005, ocean engineering subjects became part of Course 2 (Department of Mechanical Engineering), and this course was renumbered 2.158J.

Lecture Notes

LECTURE NOTES
Lecture 1 (PDF)
Lecture 2 (PDF)
Lecture 3 (PDF)
Lecture 4 and 5 (PDF)
Lecture 6 (PDF)
Lecture 8 (PDF)
Lecture 9 (PDF)
Lecture 10-12 (PDF)
Lecture 13 (PDF)
Lecture 14 and 15 (PDF)
Lecture 19 (PDF)
Lecture 20 (PDF)
Lecture 21 (PDF)
Lecture 23 (PDF)