An Assembly Language Introduction to Computer Architecture
An Assembly Language Introduction to Computer Architecture
An Assembly Language Introduction to Computer Architecture
This note describes the following topics: SASM - Simple Abstract
Language, Number Systems, Data Representation, Arithmetic and Logical
Operations, Floating Point Arithmetic, Data Structures, Using Regsiters for
Efficiency, The Pentium Architecture, Procedures,The Assembly Process, Input and
Output,Interrupts and Exception Handling, Features for Architectural
Performance, Architecture in Perspective, Memory Management and Virtual Memory
.
The purpose of
this book is to give the reader a better understanding of how computers really
work at a lower level than in programming languages like Pascal. By gaining a
deeper understanding of how computers work, the reader can often be much more
productive developing software in higher level languages such as C and C++.
Learning to program in assembly language is an excellent way to achieve this
goal.
This lecture note covers
essential topics such as system architecture, assembly processes, DOS file
operations, debugging, and Intel 8088 CPU registers, the course emphasizes
hands-on learning with practical assignments. The content explores addressing
modes, ASCII representation, system calls, segments, logical instructions, and
graphics programming. These notes serve as a valuable resource for students
seeking proficiency in low-level programming and hardware interfacing on the IBM
PC.
This PDF book covers
the following topics related to MIPS Assembly Language Programming : The MIPS
Architecture, Pseudocode, Number Systems, PCSpim The MIPS Simulator, Algorithm
Development, Reentrant Functions, Exception Processing, A Pipelined
Implementation, Embedded Processors.
Author(s): Computer Science
Department, California State University, Chico, California
This PDF covers the following topics related to Assembly Language
Programming : Fundamentals of assembly language, Introduction to assembly
language and ARMlite, Countdown, Matchsticks, Hangman, Indirect & Indexed
addressing, The System Stack, and Subroutines, Interrupts, Snake.
This lecture note
covers the following topics: Server Configuration, Python Overview, Pandas and
Numpy, Classifiers, Regression, Cross-Validation, Logistic Regression, Support
Vector Machines, Decision Trees, Ensemble Methods, Principal Component Analysis,
Embedding Methods, Clustering, Semi-Supervised Learning.