1. October 24, 2003 SEESCOASEESCOA STWW - Programma Debugging Components Koen De Bosschere RUG-ELIS

2. SEESCOASEESCOA Problem description  Components are loosely coupled and do not have a common notion of time  Components have contracts (e.g. timing contracts)  Components are activated asynchronously by the scheduler  Components can be replaced at run-time Traditional debugging techniques are not adequate

3. SEESCOASEESCOA Traditional debugging inadequate?  Execution is non-deterministic: no two runs can be guaranteed to be identical (scheduling, timing differences, replacing components,…): cyclic debugging not applicable  Timing is part of correctness: the intrusion caused by the debugger might violate the contracts  Input might not be repeatable if generated by an external device (e.g. camera or microphone) Debugging is often a matter of trial and error, and a good portion of luck and experience is needed; the use of multithreading only adds to that.

4. SEESCOASEESCOA Two approaches  On-chip debugging techniques  Software debugging techniques

5. SEESCOASEESCOA On-chip debugging techniques  Logic Analyser  ROM monitor  ROM emulator  In-Circuit Emulator  Background Debug Mode  JTAG These add-ons take up valuable chip area (up to 10%) Hardware manufacturers believe in design for debugability

6. SEESCOASEESCOA Software debugging techniques  Execution must be repeatable to allow for cyclic debugging wProgram flow must be identical wInput must be identical  Execution must be observable to allow for debugging wWe must be able to use breakpoints, watch points, etc. without altering the program flow Re-execution must be deterministic

7. SEESCOASEESCOA Example code class G { public static int global = 5; } class Thread1 extends Thread { public void run() { G.global += 2; } } class Thread2 extends Thread { public void run() { G.global *= 3; } } class Main { public static void main(String [] args) { Thread1 t1 = new Thread1(); Thread2 t2 = new Thread2(); G.global = 5; t1.start(); t2.start(); t1.join(); t2.join(); System.out.println(“global” + G.global); }

8. SEESCOASEESCOA Possible executions L(5) G.global=15 L(5) S(7) S(15) +2 *3 G.global=5 G.global=7 L(5) S(7) S(15) +2 *3 G.global=5 G.global=21 L(5) L(7) S(7) S(21) +2 *3 G.global=5 G.global=17 L(15) L(5) S(17) S(15) +2 *3 G.global=5

9. SEESCOASEESCOA Causes of non-determinism  Sequential programs: wInput wCertain system calls (time) w…  Parallel programs: wRace conditions on shared variables, wLoad balancing w…

10. SEESCOASEESCOA Execution Replay  Goal: make repeated equivalent re- executions possible  Method: two phases wRecord phase: record all non- deterministic events during an execution in a trace file wReplay phase: use trace file to produce the same execution  Question: what & where to trace? wSynchronization Replay wInput Replay wData race detection

11. SEESCOASEESCOA Requirements execution replay  Record must have low intrusion  Replay must be accurate  Record phase must be space efficient  Replay phase must be time efficient

12. SEESCOASEESCOA Synchronization Replay Execution 1Execution 2 Trace file record replay (happens before relation)

13. SEESCOASEESCOA Input replay application kernel IO-instructions System calls

14. SEESCOASEESCOA Example code class G { public static int global = 5; public static Object s = new Object(); } class Thread1 extends Thread { public void run() { synchronized(G.s){G.global += 2;}} } class Thread2 extends Thread { public void run() { synchronized(G.s){G.global *= 3;}} } class Main { public static void main(String [] args) { Thread1 t1 = new Thread1(); Thread2 t2 = new Thread2(); G.global = 5; t1.start(); t2.start(); t1.join(); t2.join(); }

15. SEESCOASEESCOA Possible executions G.global=21 L(5) L(7) S(7) S(21) +2 *3 G.global=5 G.global=7 L(5) S(7) S(15) +2 *3 G.global=5 L(5) G.global=15 L(5) S(7) S(15) +2 *3 G.global=5 G.global=17 L(15) L(5) S(17) S(15) +2 *3 G.global=5

16. SEESCOASEESCOA Record phase G.global=21 L(5) L(7) S(7) S(21) +2 *3 G.global=5 1 2 3 4 3 7 9 6 8 6 4 5 7 10 1,2,3,7,9,10 3,4,5,6 4,6,7,8 G.global=17 L(15) S(17) +2 G.global=5 L(5) S(15) *3 1 2 3 10 11 12 3 4 5 6 7 8 9 7 1,2,3,10,11,1 2 3,7,8,9 4,5,6,7

17. SEESCOASEESCOA 1 2 3 4 5 6 7 8 9 10 11 12 Replay phase G.global=21 L(5) L(7) S(7) S(21) +2 *3 G.global=5 1 2 3 4 3 7 9 6 8 6 4 5 7 10 G.global=17 L(15) S(17) +2 G.global=5 L(5) S(15) *3 1 2 3 10 11 12 3 4 5 6 7 8 9 7

18. SEESCOASEESCOA Execution Replay in Java  Requires to record the choices made by synchronization constructs like synchronized, wait, signal, etc.  During replay, the synchronization operations are replaced by operations waitforlogicaltime(t). component system T

19. SEESCOASEESCOA Input Replay  Execution will only yield the same results if the input is repeatable too  Solution: recording input by capturing all I/O events and regenerating them during replay  Input replay generates a huge amount of data…

20. SEESCOASEESCOA Data race detection  Data race occurs if a store/store, load/store or store/load occurs between two threads in parallel on the same location.  Automatic data race detection: check data race condition on all load/store pairs that are not ordered. L(5) G.global=15 L(5) S(7) S(15) +2 *3 G.global=5 G.global=7 L(5) S(7) S(15) +2 *3 G.global=5

21. SEESCOASEESCOA Implementation  RecPlay for Solaris (SPARC) and Linux (x86) wUses JiTI for dynamic instrumentation wRecord overhead: 1.6%  JaReC for Java (on top of the JVM) wUses JVMPI for dynamic instrumentation wRecord overhead: 25% on average  Input-Replay for Linux (Tornado) wUses ptrace

22. SEESCOASEESCOA Performance modeling JVM  Java workload separable in different components wVirtual Machine (SUN, IBM, JikesRVM, JRockit, …) wJava application (SPECjvm98, SPECjbb2000, …) wInput to the application  Measure execution characteristics (AMD Duron) wIPC, branch & cache behavior, …  Statistical analysis wPrincipal Components Analysis wCluster Analysis  Quantify difference SPECcpu2000 and Java workloads

23. SEESCOASEESCOA JVM Results  Java workloads mostly clustered by wbenchmark for large workloads wVM for small workloads  SPECjvm98: small input set not significant for large input set execution behavior  Comparing Java vs. C: wNo significant difference IPC, amount of branches, data TLB wSignificant difference data cache behaviour, instruction TLB, return stack usage

24. SEESCOASEESCOA PCA for SPECjvm98 – s1 input set

25. SEESCOASEESCOA PCA for SPECjvm98 – s100 input set

26. SEESCOASEESCOA PCA for SPECcpu vs. Java

27. SEESCOASEESCOA Conclusions  Debugging multithreaded/distributed systems is not an easy task  Faithful record/replay requires extra resources (time + space)  Record/replay enables the developer the effectively debug a complex multithreaded program  The choice of Java VM has an impact on the low-level behavior of the processor. Java benchmarks should be large enough to be realistic.

28. SEESCOASEESCOA Output  14 refereed conference papers (OOPSLA, ParCo, WBT,…)  12 workshop papers  5 journal publications (FGCS, CACM, Parallel Computing,…)  1 PhD  12 master theses  Java and Embedded Systems Symposium Nov 2002 [150 people]  AADEBUG 2003 workshop, Sept 2003 [60 people]