'Primitive operations' presentation slideshows

Assembly Languages & MIPS ISA

Assembly Languages & MIPS ISA. CS465 Lecture 2. Outline. Introduction to assembly languages MIPS instruction set architecture MIPS basic instructions Arithmetic instructions Data transfer instructions Control instructions Logical operations MIPS instruction format

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Computer Networks

??????? ??????????????. Computer Networks. Chapter 1: Introduction outlines:. Definition of Computer networks Uses of Computer Networks Network Hardware - Local Area Networks - Metropolitan Area Network - Wide Area Network

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Database Modelling

Database Modelling. Lecture 5: Data Manipulation 2 Nick Rossiter. Learning Objectives. To consider the algebraic Cartesian Product operator; To consider the algebraic Generalised Join operator; To consider the algebraic Natural Join operator.

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Chapter 2 The Algorithmic Foundations of Computer Science

Chapter 2 The Algorithmic Foundations of Computer Science. 1. Objectives. After studying this chapter, students will be able to: Explain the benefits of pseudocode over natural language or a programming language Represent algorithms using pseudocode

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Introduction

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Relativistic Red Black Trees

Relativistic Red Black Trees. Relativistic Programming. Concurrent reading and writing improves performance and scalability concurrent readers may disagree on the order of concurrent updates orders may be non- linearizable i s this OK ?

618 views • 51 slides

GPU Tutorial

GPU Tutorial. ??? Computer Game 2007 ?? 2007 ? 11 ? ??? ? , 12 ? ?? ?. Contents. Introduction to GPU High-level shading languages GPU applications. Introduction to GPU. ??? Computer Game 2007 ?? 2007 ? 11 ? 26 ?. Slide Credits. Marc Olano (UMBC) SIGGRAPH 2006 Course notes

568 views • 36 slides

Analyzing SET with Inductive Method

CS 395T. Analyzing SET with Inductive Method. Theorem Proving for Protocol Analysis. [Paulson]. Prove correctness instead of looking for bugs Use higher-order logic to reason about all possible protocol executions No finite bounds Any number of interleaved runs

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Algorithms Complexity and Data Structures Efficiency

Algorithms Complexity and Data Structures Efficiency. Computational Complexity, Choosing Data Structures. Svetlin Nakov. Telerik Corporation. www.telerik.com. Algorithms Complexity and Asymptotic Notation Time and Memory Complexity Mean, Average and Worst Case

613 views • 35 slides

Algorithms Complexity and Data Structures Efficiency

Algorithms Complexity and Data Structures Efficiency. Computational Complexity, Choosing Data Structures. Svetlin Nakov. Telerik Corporation. www.telerik.com. Algorithms Complexity and Asymptotic Notation Time and Memory Complexity Mean, Average and Worst Case

551 views • 35 slides

Programming Languages and Compilers (CS 421)

Programming Languages and Compilers (CS 421). Elsa L Gunter 2112 SC, UIUC http://www.cs.uiuc.edu/class/fa06/cs421/. Based in part on slides by Mattox Beckman, as updated by Vikram Adve and Gul Agha. Contact Information - Elsa L Gunter. Office: 2112 SC Office hours:

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Introduction to parallel algorithms

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Analysis of Algorithms

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Access Control Matrix

Access Control Matrix. Outline. Overview Access Control Matrix Model Boolean Expression Evaluation History Protection State Transitions Commands Conditional Commands Special Rights Principle of Attenuation of Privilege. Overview. State

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Template Method

Template Method. By: Mahmoodreza Jahanseir. Intent. Define the skeleton of an algorithm in an operation, deferring some steps to subclasses. Template Method lets subclasses redefine certain steps of an algorithm without changing the algorithm's structure.

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Execution plans

Execution plans. By Nimesh Shah , Amit Bhawnani. Outline. What is execution plan How are execution plans created How to get an execution plan Graphical Text. What is execution plan.

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Recursive Backtracking

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Reconfigurable Computing - Resolution Functions

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Algorithms: The recipe for computation

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