15 213 The Class That Gives CMU Its Zip Introduction to Computer Systems Guy Blelloch January 18 2000 Topics Theme Five great realities of computer systems How this fits within CS curriculum class01a ppt CS 213 S 00 Course Theme Abstraction is good but don t forget reality Courses to date emphasize abstraction Abstract data types Asymptotic analysis These abstractions have limits Especially in the presence of bugs Need to understand underlying implementations Useful outcomes Become more effective programmers Able to find and eliminate bugs efficiently Able to tune program performance Prepare for later systems classes Compilers Operating Systems Networks Computer Architecture class01a ppt 2 CS 213 S 00 Great Reality 1 Int s are not Integers Float s are not Reals Examples Is x2 0 Float s Yes Int s 65535 65535 131071 On most machines 65535L 65535 4292836225 On Alpha Is x y z x y z Unsigned Int s Yes Float s 1e10 1e10 3 14 3 14 1e10 1e10 3 14 0 0 class01a ppt 3 CS 213 S 00 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 usually 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 class01a ppt 4 CS 213 S 00 Great Reality 2 You ve got to know assembly Chances are you ll never write program in assembly Compilers are much better at this than you are Understanding assembly key to machine level execution model Behavior of programs in presence of bugs High level language model breaks down Tuning program performance Understanding sources of program inefficiency Implementing system software Compiler has machine code as target Operating systems must manage process state class01a ppt 5 CS 213 S 00 Great Reality 3 Memory Matters Memory is not unbounded It must be allocated and managed Many applications are memory dominated The memory system can be the largest portion of a machine s cost 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 class01a ppt 6 CS 213 S 00 Memory Referencing Bug Example main main long long int int a 2 a 2 double double dd 3 14 3 14 a 2 1073741824 a 2 1073741824 Out Out of of bounds bounds reference reference printf d printf d 15g n 15g n d d exit 0 exit 0 Alpha MIPS Sun g 5 30498947741318e 315 3 1399998664856 3 14 O 3 14 3 14 class01a ppt 3 14 7 CS 213 S 00 Memory Referencing Errors C and C do not provide any memory protection Out of bounds array references Invalid pointer values Abuses of malloc free Can lead to nasty bugs Whether or not bug has any effect system and compiler dependent Action at a distance Corrupted object logically unrelated to one being accessed Effect of bug may occur long after it occurs 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 E g Purify class01a ppt 8 CS 213 S 00 Memory Performance Example Implementations of Matrix Multiplication Multiple ways to nest loops ijk ijk for for i 0 i 0 i n i n i i for for j 0 j 0 j n j n j j sum sum 0 0 0 0 for for k 0 k 0 k n k n k k sum sum a i k a i k b k j b k j c i j c i j sum sum class01a ppt 9 jik jik for for j 0 j 0 j n j n j j for for i 0 i 0 i n i n i i sum sum 0 0 0 0 for for k 0 k 0 k n k n k k sum sum a i k a i k b k j b k j c i j c i j sum sum CS 213 S 00 Matmult Performance Alpha 21164 Too big for L1 Cache Too big for L2 Cache 160 140 120 ijk 100 ikj jik 80 jki kij 60 kji 40 20 0 matrix size n class01a ppt 10 CS 213 S 00 Blocked matmult perf Alpha 21164 160 140 120 100 bijk bikj 80 ijk ikj 60 40 20 0 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 matrix size n class01a ppt 11 CS 213 S 00 Great Reality 4 There 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 How programs compiled and executed How to measure program performance and identify bottlenecks How to improve performance without destroying code modularity and generality class01a ppt 12 CS 213 S 00 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 class01a ppt 13 CS 213 S 00 Role within Curriculum CS 412 Operating Systems CS 441 Networks Network Protocols CS 212 Execution Models CS 411 Compilers ECE 347 Processes Machine Code Mem Mgmt Optimization Architecture CS 213 Systems Exec Model Memory System Transition from Abstract to Concrete Data Structures Applications C Programming From high level language model To underlying implementation CS 211 Fundamental Structures class01a ppt 14 CS 213 S 00
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