'Arithmetic operation' presentation slideshows

comp.nus.sg/~cs2100/

http://www.comp.nus.edu.sg/~cs2100/. Lecture #7. MIPS Part I: Introduction. Lecture #7: MIPS Part 1: Introduction (1/2). Instruction Set Architecture Machine Code vs Assembly Language Walkthrough General Purpose Registers MIPS Assembly Language 5.1 General Instruction Syntax

458 views • 45 slides

1.03k views • 38 slides

522 views • 38 slides

ANALYSIS OF ALGORITHMS

550 views • 33 slides

Good Afternoon!

400 views • 30 slides

Good Afternoon!

401 views • 25 slides

Booth's Algorithm Example

Booth's Algorithm Example. Points to remember. When using Booth's Algorithm: You will need twice as many bits in your product as you have in your original two operands .

413 views • 23 slides

A Massively Parallel Architecture for Bioinformatics

A Massively Parallel Architecture for Bioinformatics. Presented by Md Jamiul Jahid. Introduction. Bioinformatics algorithms are demanding in scientific computing In general most of the bioinformatics algorithms are fairly simple Dealing with huge amount of data

342 views • 17 slides

Digital Logic Design (CSNB163)

Digital Logic Design (CSNB163). Module 1. Number Systems. {0,1,2,3,4,5,6,7,8,9}. {0,1}. {0,1,2,3,4,5,6,7}. {0,1,2,3,4,5,6,7,8,9,A,B,C,D,E,F}. Number system consists of an ordered set of symbols called digit. The radix (r) or base is the total number of digits allowed in the system.

305 views • 17 slides

Chapter 11

Chapter 11. Data Validation. Question. Should your program assume the data is correct, or should your program edit the data to ensure it is correct?. Why Input Must Be Validated. Risk of data entry errors is high Large volume of data entered Human error keying in data

298 views • 16 slides

String Matching

COMP171 Fall 2005. String Matching. Pattern Matching. Given a text string T[0..n-1] and a pattern P[0..m-1], find all occurrences of the pattern within the text. Example: T = 000010001010001 and P = 0001, the occurrences are: first occurrence starts at T[1]

515 views • 15 slides

DSP Processors

DSP. y. x. ALU with ADD, MULT, etc. bus. memory. registers. PC. a. b. XTAL. t. c. d. DSP Processors. We have seen that the Multiply and Accumulate (MAC) operation is very prevalent in DSP computation computation of energy MA filters AR filters correlation of two signals FFT

307 views • 9 slides