COSC 3406: Computer Organization - Laurentian

COSC 3406: Computer Organization - Laurentian

COSC 3406: Computer Organization Kalpdrum Passi ( www.cs.laurentian.ca/kpassi/cosc3406.html ) Chapter 1 Computer Abstractions and Technology The Computer Revolution Progress in computer technology

Underpinned by Moores Law Makes novel applications feasible Computers in automobiles Cell phones Human genome project World Wide Web Search Engines Computers are pervasive Classes of Computers

Personal computers General purpose, variety of software Subject to cost/performance tradeoff Server computers Network based High capacity, performance, reliability Range from small servers to building sized Classes of Computers Personal computers General purpose, variety of software

Subject to cost/performance tradeoff Server computers Network based High capacity, performance, reliability Range from small servers to building sized Classes of Computers Supercomputers High-end scientific and engineering calculations Highest capability but represent a small

fraction of the overall computer market Embedded computers Hidden as components of systems Stringent power/performance/cost constraints Terabyte (TB) Originally 1,099,511,627,776 (240) bytes Although communications and secondary storage systems developers started using the term to mean 1,000,000,000,000 (1012) bytes.

To reduce confusion, we now use the term tebibyte (TiB) for 240 bytes, defining terabyte (TB) to mean 1012 bytes The PostPC Era The PostPC Era Personal Mobile Device (PMD)

Battery operated Connects to the Internet Hundreds of dollars Smart phones, tablets, electronic glasses Cloud computing

Warehouse Scale Computers (WSC) Software as a Service (SaaS) Portion of software run on a PMD and a portion run in the Cloud Amazon and Google What You Will Learn

How programs are translated into the machine language And how the hardware executes them The hardware/software interface What determines program performance And how it can be improved How hardware designers improve performance What is parallel processing

Understanding Performance Algorithm Determines number of operations executed Programming language, compiler, architecture Determine number of machine instructions executed per operation Processor and memory system Determine how fast instructions are executed I/O system (including OS)

Determines how fast I/O operations are executed Eight Great Ideas Design for Moores Law Use abstraction to simplify design Make the common case fast Performance via parallelism Performance via pipelining Performance via prediction Hierarchy of memories Dependability via redundancy

Moores Law Predicts: 2X Transistors / chip every 2 years Gordon Moore Intel Cofounder B.S. Cal 1950! End of Moores Law?

Cost per transistor is rising as transistor size continues to shrink COSC 3406: So what's in it for me? Learn some of the big ideas in CS & engineering: 5 Classic components of a Computer

Data can be anything (integers, floating point, characters): a program determines what it is Stored program concept: instructions just data Principle of Locality, exploited via a memory hierarchy (cache) Greater performance by exploiting parallelism Principle of abstraction, used to build systems as layers Compilation v. interpretation thru system layers Principles/Pitfalls of Performance Measurement Texts

Required: Computer Organization and Design: The Hardware/Software Interface, ARM Edition, Patterson and Hennessy (COD). Green card summarizes MIPS Reading assignments on web page Gradin g Grade breakdown Midterm exam: Assignments (individual): Project (group):

Final Exam: 30% 20% 20% 30% Course Problems Cheating What is cheating?

Studying together in groups is encouraged. Turned-in work must be completely your own. Common examples of cheating: running out of time on a assignment and then person asks to borrow solution just to take a look, copying an exam question, Both giver and receiver are equally culpable Cheating on homeworks: negative points for that assignment (e.g., if its worth 10 pts, you get -10)

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