1 689, High-Performance Computing with Java Technology

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1 1 689, High-Performance Computing with Java Technology

2 High-Performance Computing With Java Technology Stefan Nilsson Assistant Professor Royal Institute of Technology 2 689, High-Performance Computing with Java Technology

3 Rules for Optimization (Trad.) Don t Use the right algorithms and data structures 90/10-rule Use a profiler Measure before and after (Don t optimize as you go) 3 689, High Performance Computing with Java Technology

4 Optimization Algorithms and data structures Code tuning 4 689, High Performance Computing with Java Technology

5 Code Lives Longer Than Hardware TeX Y2K Genetic programs 5 689, High Performance Computing with Java Technology

6 A Changing World Processors get faster Memory gets larger Problems grow larger Programs either improve or degrade 6 689, High Performance Computing with Java Technology

7 Program Degradation Due to Quadratic Growth T(n) = n², where n is size and T(n) time T(n) 600, , , n 7 689, High Performance Computing with Java Technology

8 Spot the Square String str = ""; for (int i = 0; i < 10000; i++) { str += i; } System.out.println(str); 8 689, High Performance Computing with Java Technology

9 Remove the Square StringBuffer strbuf = new StringBuffer(); for (int i = 0; i < 10000; i++) { strbuf.append(i); } System.out.println(strBuf); 9 689, High Performance Computing with Java Technology

10 What Really Happened? > javap -c MyClass... 8 new #3 <Class StringBuffer> 11 dup 12 invokespecial #4 <Method StringBuffer()> 15 aload_1 16 invokevirtual #5 <Method StringBuffer append(string)> 19 iload_2 20 invokevirtual #6 <Method StringBuffer append(int)> 23 invokevirtual #7 <Method String tostring()> 26 astore_1 27 iinc iload_2 31 sipush if_icmplt , High Performance Computing with Java Technology

11 Spot the Square (2) List mylist = new ArrayList(); Random rand = new Random(); for (int i = 1; i < 75000; i++) { int k = rand.nextint(i); mylist.add(k, new Object()); } , High Performance Computing with Java Technology

12 Remove the Square (2) List mylist = new IndexTreeList(); Random rand = new Random(); for (int i = 1; i < 75000; i++) { int k = rand.nextint(i); mylist.add(k, new Object()); } , High Performance Computing with Java Technology

13 List Operations Array Linked IndexTree add(i, x) n n log n remove(i) n n log n get(i) 1 n log n get(0) 1 1 log n , High Performance Computing with Java Technology

14 Logarithmic Growth log n n ,000 1,000, , High Performance Computing with Java Technology

15 Index Tree 0 N 1 I 2 L 3 S 4 S 5 O 6 N 1 N 4 I 7 S L 2 2 O 1 N 1 S , High Performance Computing with Java Technology

16 Object Pool class Node { private static Node[] pool = new Node[50]; private static int topofpool = 0;... public static Node create() { if (topofpool > 0) return pool[--topofpool]; else return new Node(); } } public static void destroy(node n) { } , High Performance Computing with Java Technology

17 Spot the Square (3) [Trick Question] StringBuffer strbuf = new StringBuffer(); BigInteger k; for (int i = 0; i < 25000; i++) strbuf.append("7"); k = new BigInteger(strBuf.toString()); k = k.multiply(k); System.out.println(k); , High Performance Computing with Java Technology

18 Use a Profiler > java -Xrunhprof ClassName TRACE 259: java.math.mutablebiginteger.divide(<unknown>:unknown line) java.math.biginteger.tostring(<unknown>:unknown line) java.math.biginteger.tostring(<unknown>:unknown line) java.lang.string.valueof(<unknown>:unknown line) , High Performance Computing with Java Technology

19 Alt: Perform Explicit Timings PrintStream o = System.out; o.print("multiply: "); long time = System.currentTimeMillis(); k = k.multiply(k); o.println(system.currenttimemillis()-time); o.print("tostring: "); time = System.currentTimeMillis(); String str = k.tostring(); o.println(system.currenttimemillis()-time); , High Performance Computing with Java Technology

20 Routing Table as Trie , High Performance Computing with Java Technology

21 Path Compression Skip= , High Performance Computing with Java Technology

22 Level Compression Skip= , High Performance Computing with Java Technology

23 Routing Table Lookup int node = trie[0]; int pos = getskip(node); int branch = getbranch(node); int adr = getadr(node); while (branch!= 0) { node = trie[adr + extract(pos, branch, s)]; pos += branch + getskip(node); branch = getbranch(node); adr = getadr(node); } , High Performance Computing with Java Technology

References http://www.research.ibm.com/journal/ sj39-1.html http://www.javagrande.

24 References sj39-1.html , High Performance Computing with Java Technology

25 25 689, High-Performance Computing with Java Technology

Code Profiling. CSE260, Computer Science B: Honors Stony Brook University

Code Profiling. CSE260, Computer Science B: Honors Stony Brook University Code Profiling CSE260, Computer Science B: Honors Stony Brook University http://www.cs.stonybrook.edu/~cse260 Performance Programs should: solve a problem correctly be readable be flexible (for future