Instructors: Randy H. Katz David A. PaHerson hhp://inst.eecs.berkeley.edu/~cs61c/fa10. Fall Lecture #1. Agenda

Transcription

1 CS 61C: Great Ideas in Computer Architecture (Machine Structures) Instructors: Randy H. Katz David A. PaHerson hhp://inst.eecs.berkeley.edu/~cs61c/fa10 1 Agenda Great Ideas in Computer Architecture Administrivia Technology Break How to Talk to a Computer 2 1

2 Agenda Great Ideas in Computer Architecture Administrivia Technology Break How to Talk to a Computer 3 Old School CS61c 4 2

3 New School CS61c Fall Lecture #1 5 Fall Lecture #1 6 3

4 Machine Structures SoHware Hardware Applica6on (ex: browser) Compiler Assembler Processor Memory Datapath & Control Digital Design Circuit Design transistors Opera6ng System (Mac OSX) I/O system CS61C Instruc6on Set Architecture 7 Great Ideas in Computer Architecture Layers of Representa[on/Interpreta[on Moore s Law Principle of Locality/Memory Hierarchy Parallelism Performance Improvement 8 4

5 Machine Interpreta4on Levels of Representa[on/ Interpreta[on High Level Language Program (e.g., C) Compiler Assembly Language Program (e.g., MIPS) Assembler Machine Language Program (MIPS) Hardware Architecture Descrip6on (e.g., block diagrams) Architecture Implementa4on Logic Circuit Descrip6on (Circuit Schema6c Diagrams) temp = v[k]; v[k] = v[k+1]; v[k+1] = temp; lw $t0, 0($2) lw $t1, 4($2) sw $t1, 0($2) sw $t0, 4($2) Anything can be represented as a number, i.e., data or instruc[ons ! Predicts: 2X Transistors / chip every 2 years Moore s Law # of transistors on an integrated circuit (IC) Gordon Moore Intel Cofounder B.S. Cal 1950! Year 10 5

6 Principle of Locality/ Memory Hierarchy 11 Parallelism 12 6

7 Performance Improvement Matching applica[on to underlying hardware to exploit: Locality Parallelism Special hardware features, like specialized instruc[ons (e.g., matrix manipula[on) Latency How long to set the problem up How much faster does it execute once it gets going It is all about 'me to finish 13 Agenda Great Ideas in Computer Architecture Administrivia Technology Break How to Talk to a Computer 14 7

8 15 Course Informa[on Instructors: Randy Katz, Dave PaHerson Teaching Assistants: Andrew Gearhart, Michael Greenbaum, Conor Hughes, Charles Reiss Textbooks: PaHerson, Hennessey, Computer Organiza'on and Design, 4 th Edi[on Kernighan, Ritchie, The C Programming Language, 2 nd Edi[on Course Web: hhp://inst.eecs.berkeley.edu/~cs61c/fa10 Google Group: 61CFall2010UCB 16 8

9 Course Organiza[on Grading Class Par[cipa[on (5%) Homework (5%) Labs (20%) Projects (40%) Computer Instruc[on Set Simulator Data Parallelism (Map- Reduce on EC2) Computer Processor Design (Logisim) Effort Par'cipa'on Altruism Performance Tuning of a Parallel Applica[on (partnered) Midterm (10%) Final (20%)

10 The Rules (and we really mean it!) 19 Agenda Great Ideas in Computer Architecture Administrivia Technology Break How to Talk to a Computer 20 10

11 Agenda Great Ideas in Computer Architecture Administrivia Technology Break How to Talk to a Computer 21 Speaking to a Computer A word a computer understands called an instruc'on Vocabulary of all words a computer understands are called an instruc'on set Different computers may have different vocabularies (instruc[on sets) Computer vocabulary used in iphone is not same as computer vocabulary used in Macbook laptop Or the same vocabulary iphone and ipad computers have same instruc[on set Why not all the same? Why not all different? What might be pros and cons? 22 11

12 Instruc[on Set in this Class MIPS Invented by my co- author John Hennessy Standard instruc[on set for networking gear Elegant example of instruc[on sets called Reduced Instruc[on Set Computer (RISC) RISC: Limited vocabulary in number of words and in complexity of those words Most popular RISC is ARM (Advanced RISC Machine) 5 billion in 2010, in every cell phone (iphone, ipad, ipod, ) Another popular Instruc[on Set is used in Macbook and in PCs: Intel 80x86 in Core i3, Core i5, Core i7 1/20th as 80x86s made in 2010 (0.3 billion) 23 Example MIPS Instruc[ons Every computer does arithme[c Tell a computer to do addi[on? add a, b, c Add b to c and put sum into a Needs 3 operands: 2 sources + 1 des[na[on for sum Always just 1 opera[on per MIPS instruc[on How write same opera[on in Java? 24 12

13 Guess the other MIPS instruc[ons Subtract c from b and put difference in a? Mul[ply b by c and put product in a? Divide b by c and put quo[ent in a? 25 Guess the other MIPS instruc[ons Java operator &: c & b and put result in a? Java operator : c b and put result in a? Java operator <<: c << b and put result in a? Java operator >>: c >> b and put result in a? 26 13

14 Example Instruc[ons MIPS instruc[ons are inflexible, rigid: Just 1 arithme[c opera[on per instruc[on, Always with 3 operands How write this Java opera[on in MIPS? a = b + c + d + e 27 Comments in MIPS Can add comments to MIPS instruc[on by putng # that con[nues to end of line of text add a, b, c # b + c is placed in a. add a, a, d # b + c + d is now in a. add a, a, e # b + c + d + e is in a

15 Java to MIPS Operators almost iden[cal What is MIPS code that performs same as? a = b + c; d = a e; What is MIPS code that performs same as? f = (g + h) (i + j); 29 Peer Instruc[on For a given func[on, which programming language likely takes the most lines of code? I. Scheme II. Java III. MIPS instruc[ons Put the three representa[ons in order A. Most to least: I, II, III B. I, III, II C. II, III, I D. II, I, III E. III, II, I F. III, I, II 30 15

16 Summary Computer words called instruc[ons Computer vocabulary is instruc[on set MIPS is example instruc[on set in this class Rigid format: 1 opera[on, 2 source operands, 1 des[na[on add, sub, mult, div, and, or, shl, shr Like other programming languages, has comments to help programmer Simple mapping from arithme[c expression in Java to MIPS instru[ons 31 16