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CSE 420 Computer Architecture 1 Today’s Lecture Course organization Computing environment Semester project Overview of course topics 2 1 Course Organization Course website http://www.cse.msu.edu/~cse420/ Syllabus and calendar Enrollment 3 Computing Environment Operating system: Linux Remote access: • • • arctic xserver2 cse410 Accounts 4 2 Semester Project Simulation of a 32-bit processor • • based on MIPS microprocessor subset of instructions Series of 10 milestones • • full credit if milestone completed by due date 10% deducted for each day late 5 The Information Revolution Computers have led to a third revolution for civilization, with the information revolution taking its place alongside the agricultural and industrial revolutions. This race to innovate has led to unprecedented progress since the inception of electronic computing in the late 1940s. Had the transportation industry kept pace with the computer industry, for example, today we could travel from New York to London in a second for a penny. (Patterson and Hennessy) 6 3 The Information Revolution Driven by rapid innovation in technology Complex applications now feasible • • • • Computers in automobiles Cell phones Human genome project World Wide Web 7 Classes of Computers Personal computers • • General purpose, variety of software Subject to cost/performance tradeoffs Server computers • • • Network based High capacity, performance, reliability Range of sizes 8 4 Classes of Computers Supercomputers • • High-end scientific applications Highest capability but represent a small fraction of the overall computer market Embedded computers • • Hidden as components of systems Stringent power/performance/cost constraints 9 The Post PC Era Personal Mobile Device (PMD) • • Smart phones, tablets (touch screen) Battery operated, wireless connection to net Cloud computing • • • Warehouse Scale Computers (WSC) Software as a Service (SaaS) Part of software runs on a PMD and part runs in the Cloud 10 5 The Post PC Era 11 Focus of the Course The interface between software and hardware: how programs are translated into machine language and how the hardware executes them What determines program performance What hardware designers can do to improve performance 12 6 Eight Great Ideas in Architecture Design for Moore’s Law Use abstraction to simplify design Make the common case fast Performance via parallelism 13 Eight Great Ideas in Architecture Performance via pipelining Performance via prediction Hierarchy of memories Dependability via redundancy 14 7 Moore’s Law Observation in 1965: number of transistors on an integrated circuit doubles every 18-24 months (exponential growth). A transistor’s dimensions are scaled by 30% every generation, so only 50% of the area is required (.7 x .7 = .49). In other words, transistor density doubles. 15 Moore’s Law Voltage used by a transistor is reduced by 30%, so power consumption is reduced by 50% (power based on voltage squared). Also, signals only have to travel 70% as far, so clock speeds can increase by 40%. Observation accurate for past 50 years. 16 8 Moore’s Law: Summary Every 18-24 months: Transistor density doubles (each transistor only requires half the area) Power consumption remains the same (twice as many transistors, each requires only half the power) Circuits 40% faster (shorter distances) 17 Abstraction Productivity technique used for hardware and software: use abstractions to represent the design at different levels Lower-level details hidden to offer a simpler model at higher levels 18 9 Make the Common Case Fast Improve overall performance by making the common case fast (rather than optimizing for rare special cases) Use experimentation and measurement to decide which cases are common and which are rare 19 Performance via Parallelism Accomplish more work in a given amount of time by doing tasks in parallel Instruction-level parallelism: overlap work at the level of individual instructions Processor-level parallelism: overlap work at the level of the processor 20 10 Performance via Pipelining Particular pattern of parallelism: subdivide task into smaller pieces, overlap steps 21 Performance via Prediction Faster (on average) to guess and start working immediately, rather than waiting until all of the information is available – as long as the mechanism to recover from a wrong guess isn't too expensive 22 11 Hierarchy of Memories Systems contain a hierarchy of different kinds of "memory" (storage) top: fast, expensive and small bottom: slow, inexpensive and large Provides the illusion that memory is nearly as fast as the top of the hierarchy and nearly as large (and cheap) as the bottom 23 Dependability via Redundancy Make systems more dependable by including redundant components used when failures occur help detect failures 24 12