11Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyCEG 320/520 CEG 320/520 –– Computer OrganizationComputer OrganizationInstructor: Travis Doom, Ph.D.331 Russ Engineering [email protected] slides created by Drs. Travis Doom and Michael Raymer for use in WSU’s CEG320. Some images, examples, and ideas courtesy of texbooks by Drs. Patt, Wakerly, Mano, Bryant, and others.2Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyWhat What isis a computer?a computer? What is computation? There are many sorts of computing devices, they fall into two categories:– Analog: machines that produce an answer that measures some continuous physical property such as distance, light intensity, or voltage. Examples?– Digital: machines that perform computations by manipulating a fixed finite set of elements. Examples?– The difficulty with analog devices is that it is very hard to increase their accuracy. Before modern digital computers, the most common digital machines were adding machines.– Adding machines perform exactly one sort of operation. Modern general-purpose digital computers also perform one operation… but their operation is to accept a set of instructions that tell it how to do any sort of computation.3Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyHow How dodo we get the electrons to do the work?we get the electrons to do the work? We describe our problems in English or some other natural language. Computer problems are solved by electrons flowing around inside the computer.  It is necessary to transform our problem from a natural language to the voltages that influence the flow of electrons. This transformation is really a sequence of systematic transformations, developed and improved over the last 50 years, which combine to give the computer the ability to carry out what may appear to be very complicated tasks. In reality, these tasks must be simple and straightforward.4Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyThe principle of design abstractionThe principle of design abstraction General model for Engineering (Byrne, 1992)Existing System Target SystemImplementationDesignRequirements RequirementsCon-ceptualCon-ceptualDesignImplementationre-thinkre-specifyre-designre-buildAlterationReverseEngineeringAbstractionForwardEngineeringRefinement5Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyLevels of abstraction in digital computationLevels of abstraction in digital computation Design ProcessAlgorithm & LanguageThe ProblemISA & MicroarchitectureCircuits & DevicesSoftware levelHardware levelLogic levelComputer ScienceComputer EngineeringComputer/Elect. EngineeringCS 24x, 4xxCEG 320CEG 260/3606Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyBlack BoxesBlack Boxes Every level of this hierarchy that you don’t understand is a black box– It might as well be magic– “Debugging by superstition” You are already familiar with the high-level language level of abstraction and above. The objective of this course is to move the black-box boundary down to Microarchitecture!– ISA: Essentially, the low-level tasks that a particular computer can perform. A sequence of such tasks may perform a high-level task.– Microarchitecture: Implementation of the ISA This course will largely treat circuits & devices as “magic” black boxes (refer to future coursework!)Algorithm & LanguageThe ProblemISA & MicroarchitectureCircuits & Devices27Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyThe instruction setThe instruction set High-Level Language – C, C++, or Java A = B + C;  ISA Level– Memory-Transfer Equivalent Mem[A]  Mem[B] + Mem[C]  Mem[EA00]  Mem[EA08] + Mem[EA10]– Low-level language equivalent– Assembly (human readable) ex: Machine (for a simple architecture) Load R2, B E2EA08 Load R3, C E3EA10 R2  R2 + R3 0223 Store A, R2 F2EA00 Executed as one step in an overall algorithm to solve a problem on a general-purpose digital computer8Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyUniversal computing devicesUniversal computing devices Turing’s Thesis: Computer scientists believe that ANYTHING that can be computed, can be computed by a computer (provided that it has enough time and enough memory). What does this imply?– All computers (from the least expensive to the most expensive) are capable of computing EXACTLY the same things IF they are given enough time and enough memory.– Some computers can do things faster, but none can do more than any other computer.– All computers can do exactly the same things! Thus, any given problem is either computable or it is not computable– Problems may be computable, but still not feasible (NPC) This course focuses on one computer (the LC-3), but the concepts apply to all computers!9Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyExponential growthExponential growth 101 102 103Number of students in the college of engineering 104Number of students enrolled at Wright State University 106Number of people in Dayton 108Number of people in Ohio 1010Number of stars in the galaxy 1020Total number of all stars in the universe 1080Total number of particles in the universe 10100<< Number of possible solutions to traveling salesman (100) Traveling salesman (100) is computable but it is NOT feasible.10Wright State Univ ersity, College of EngineeringDr. Doom, Computer Science & EngineeringCEG 320/520Comp. Org . & Assemb lyCS Realities: Why study Computer Org?CS Realities: Why study Computer Org? You’ve got to understand the limitations of binary encodings– Integers, floating point numbers (rounding, range, precision), strings of characters, instructions You’ve got to understand how a machine processes instructions– The