Introduction to Computer Architecture. Meet your Colleagues. Course Theme CISC Michela Taufer September 4, 2008

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1 CISC Introduction to Computer Architecture Michela Taufer September 4, 2008 Topics: Course policies and overview Theme Five great realities of computer systems Powerpoint Lecture Notes for Computer Systems: A Programmer's Perspective, R. Bryant and D. O'Hallaron, Prentice Hall, 2003 Meet your Colleagues Ask your classmate: His/Her name? What are his/her favorite topics in computer science? List up to three topics. What is he/she planning to do after his/her graduation? 2 Course Theme Abstraction is good, but donʼt forget reality! Courses to date emphasize abstraction Abstract data types Asymptotic analysis (big oh) These abstractions have limits Especially in the presence of bugs Need to understand underlying implementations Useful outcomes Useful outcomes Become more effective programmers Able to find and eliminate bugs efficiently Able to tune program performance Prepare for later systems classes in CS & ECE Compilers, Operating Systems, Networks, Embedded Systems 3

2 Teaching Staff Instructors Prof. Michela Taufer (2:30PM to 3:30PM or by appointment) TAʼs Yang Gang 4 Textbooks (Mandatory) Randal E. Bryant and David R. OʼHallaron, Computer Systems: A Programmerʼs Perspective, Prentice Hall csapp.cs.cmu.edu 5 Textbooks (Recommended) Brian Kernighan and Dennis Ritchie, The C Programming Language, Second Edition, Prentice Hall,

3 Course Components Lectures Higher level concepts Quizzes Applied concepts, important tools and skills for labs Projects Four lab assignments The heart of the course ~2 weeks Provide in-depth understanding of an aspect of systems Programming and measurement 7 Getting Help Course webpage at //cis.udel.edu/~taufer/coursesedu/~taufer/courses Copies of lectures and project assignments Clarifications to assignments, deadlines Syllabus and class schedule User: cisc360student Password: Learn4Fun! Discussions through mailing list Clarifications to assignments, general discussion Send to all with: cisc360010_fa08@gcl.cis.udel.edu Personal help Professor: lecture, exams, quizzes, grades TA: lab assignments 8 Policies: Quizzes Quizzes test your understanding of the text You are expected to do the reading assignment BEFORE the quiz There are NO make-up quizzes 9

4 Policies: Lab Assignments Submissions Assignments due at 11:59PM on specified due date Electronic submissions ONLY - procedure is explained in assignment Makeup exams and assignments OK, but must make PRIOR arrangements with Prof. Taufer. Appealing grades Within 7 days of due date or exam date 10 Cheating What is cheating? Sharing code: either by copying, retyping, looking at, or supplying a copy of a file. What is NOT cheating? Helping others use systems or tools. Helping others with high-level design issues. Helping others debug their code. Penalty for cheating: Removal from course with failing grade. 11 Policies: Grading Exams (38%) Two in class exams (10% each) Final (28%) All exams are open book Projects (40%) 4 project (10% each) Quizzes (12%) Grading Characteristics Lab scores tend to be high Serious handicap if you donʼt hand a lab in Tests typically have a wider range of scores 12

5 Facilities Assignments will use Linux OS machines McKinly Lab Lab Linux systems for CIS labs Remote SSH Alias: hplab.acad.cis.udel.edu 13 Schedule of the Next Two Weeks Class 01 - Introduction (Sep 4) o Course Overview o Course Organization o Reading chap 1 assigned Class 02 - Bits and Bytes (Sep 9) o Reading chap 2 assigned o Quiz chap 1 Class 03 - Integers (Sep 11) 14 Course Perspective Most Systems Courses are Builder-Centric Computer Architecture Design pipelined processor in Verilog Operating Systems Implement large portions of operating system Compilers Write compiler for simple language Networking Implement and simulate network protocols 15

6 Course Perspective (Cont.) This Course is Programmer-Centric Purpose is to show how by knowing more about the underlying system, one can be more effective as a programmer Enable you to Write programs that are more reliable and efficient Incorporate features that require hooks into OS» E.g., concurrency, signal handlers Not just a course for dedicated hackers We bring out the hidden hacker in everyone Cover material in this course that you wonʼt see elsewhere 16 Programs and Data (9) Topics Bits operations, arithmetic, assembly language programs, representation of C control and data structures Includes aspects of architecture and compilers Lab Assignments L1: Manipulating bits L2: Defusing a binary bomb 17 Computer Architecture (6) Topics Computer architecture and logic design,pipelined architecture Develop understanding of processor design and the close relationship between software and hardware Lab Assignments L3: Design and implementation of a pipelined Y86 processor 18

7 Performance (2) Topics High level processor models, code optimization (control and data) Includes aspects of architecture, compilers, and OS Lab Assignments L4: Optimizing Code Performance 19 The Memory Hierarchy (2) Topics Memory technology, memory hierarchy, caches, disks, locality Includes aspects of architecture and OS. Assignments L4: Optimizing Code Performance 20 Virtual memory (4) Topics Virtual memory, address translation, dynamic storage allocation Includes aspects of architecture and OS 21

8 Project Rationale Each project should have a well-defined goal such as solving a puzzle or winning a contest. Defusing a binary bomb. Doing a project should result in new skills and concepts Data Lab: computer arithmetic, digital logic. Bomb Lab: assembly language, using a debugger, understanding the stack Arch Lab: learn about the design and implementation of a pipelined Y86 processor, optimizing its performance on a benchmark Y86 array copy program called ncopy.ys Perf Lab: profiling, measurement, performance debugging. 22 Great Reality #1 Intʼs are not Integers, Floatʼs s are not Reals Examples Is x 2 0? Floatʼs: Intʼs: Yes!» * > » 200 * 300 * 400 * >?? Is (x + y) + z = x + (y + z)? Unsigned & Signed Intʼs: Yes! Floatʼs:» (1e e20) > 3.14» 1e20 + (-1e ) -->?? 23 Computer Arithmetic Does not generate random values Arithmetic operations have important mathematical properties Cannot assume usual properties Due to finiteness of representations Integer operations satisfy ring properties Commutativity, associativity, distributivity Floating point operations satisfy ordering properties Monotonicity, values of signs Observation Need to understand which abstractions apply in which contexts Important issues for compiler writers and serious application programmers 24

9 Great Reality #2 Youʼve got to know assembly Chances are, youʼll never write program in assembly Compilers are much better & more patient than you are Understanding assembly key to machine-level execution model Tuning program performance Understanding sources of program inefficiency Behavior of programs in presence of bugs High-level language model breaks down Implementing system software Compiler has machine code as target Operating systems must manage process state 25 Assembly Code Example Time Stamp Counter Special 64-bit register in Intel-compatible machines Incremented every clock cycle Read with rdtsc instruction Application Measure time required by procedure In units of clock cycles double t; start_counter(); P(); t = get_counter(); printf("p required %f clock cycles\n", t); 26 Code to Read Counter Write small amount of assembly code using GCCʼs asm facility Inserts assembly code into machine code generated by compiler static unsigned cyc_hi = 0; static unsigned cyc_lo = 0; /* Set *hi and *lo to the high and low order bits of the cycle counter. */ void access_counter(unsigned *hi, unsigned *lo) { asm("rdtsc; movl %%edx,%0; movl %%eax,%1" : "=r" (*hi), "=r" (*lo) : : "%edx", "%eax"); 27

10 Code to Read Counter /* Record the current value of the cycle counter. */ void start_counter() { access_counter(&cyc_hi, &cyc_lo); /* Number of cycles since the last call to start_counter. */ double get_counter() { unsigned ncyc_hi, ncyc_lo; unsigned hi, lo, borrow; /* Get cycle counter */ access_counter(&ncyc_hi, &ncyc_lo); /* Do double precision subtraction */ lo = ncyc_lo - cyc_lo; borrow = lo > ncyc_lo; hi = ncyc_hi - cyc_hi - borrow; return (double) hi * (1 << 30) * 4 + lo; 28 Measuring Time Trickier than it Might Look Many sources of variation Example Sum integers from 1 to n n Cycles Cycles/n ,000 8, ,000 8, ,000 82, ,000 82, ,000,000 8,419, ,000,000 8,425, ,000,000,000 8,371,2305, Great Reality #3 Memory Matters Memory is not unbounded It must be allocated and managed Many applications are memory dominated Memory referencing bugs especially pernicious Effects are distant in both time and space Memory performance is not uniform Cache and virtual memory effects can greatly affect program performance Adapting program to characteristics of memory system can lead to major speed improvements 30

11 Memory Referencing Bug Example main () { long int a[2]; double d = 3.14; a[2] = ; /* Out of bounds reference */ printf("d = %.15g\n", d); exit(0); Alpha MIPS Linux -g e O (Linux version gives correct result, but implementing as separate function gives segmentation fault.) Memory Referencing Errors C and C++ do not provide any memory protection Out of bounds array references 32 Invalid pointer values Abuses of malloc/free Can lead to nasty bugs Whether or not bug has any effect depends on system and compiler Action at a distance Corrupted object logically unrelated to one being accessed Effect of bug may be first observed long after it is generated How can I deal with this? Program in Java, Lisp, or ML Understand what possible interactions may occur Use or develop tools to detect referencing errors Memory Performance Example Implementations of Matrix Multiplication Multiple ways to nest loops /* ijk */ for (i=0; i<n; i++) { for (j=0; j<n; j++) { sum = 0.0; for (k=0; k<n; k++) sum += a[i][k] * b[k][j]; c[i][j] = sum; /* jik */ for (j=0; j<n; j++) { for (i=0; i<n; i++) { sum = 0.0; for (k=0; k<n; k++) sum += a[i][k] * b[k][j]; c[i][j] = sum 33

12 Matmult Performance (Alpha 21164) Too big for L1 Cache Too big for L2 Cache ijk ikj jik jki kij kji matrix size (n) 34 Blocked matmult perf (Alpha 21164) bijk bikj ijk ikj matrix size (n) 35 Great Reality #4 Thereʼs s more to performance than asymptotic complexity Constant factors matter too! Easily see 10:1 performance range depending on how code written Must optimize at multiple levels: algorithm, data representations, procedures, and loops Must understand system to optimize performance Must understand system to optimize performance How programs compiled and executed How to measure program performance and identify bottlenecks How to improve performance without destroying code modularity and generality 36

13 Great Reality #5 Computers do more than execute programs They need to get data in and out I/O system critical to program reliability and performance They communicate with each other over networks Many system-level issues arise in presence of network Concurrent operations by autonomous processes Coping with unreliable media Cross platform compatibility Complex performance issues 37 Good Luck! 38