![Example (1)
Public static void main(String[] args) {
int n = Integer. parseInt(args[0]);
long[] sums = new long[n]
long overallSum = 0;
for (int i = 0; i < n; ++i) {
sums[i] = sumTo(i);
}
for (int i = 0; i < n; ++i) {
overallSum += sums[i];
}
}
private static long sumTo(int n) {
return n == 0 ? 0 : n + sumTo(n – 1);
}](https://image.slidesharecdn.com/profilejavaprograms-120608062659-phpapp02/85/Profiling-Java-Programs-for-Parallelism-11-320.jpg)
Profiling Java Programs for Parallelism
- 1. Profiling Java Programs for Parallelism Authors: Clemens Hammacher, Kevin Streit, Sebastian Hack and Andreas Zeller Presented by: Anisimov Dmitry (Theoretical part) Igdalov Dimitri (Demo)
- 2. Challenge How to leverage the computer power of multicore architectures for systems that were not built with parallelism in mind?
- 3. The idea of article To try to measure the potential for parallel execution in recent object-oriented programs.
- 4. Approach of authors Three main steps: Tracing dynamic dependencies Detecting parallelism Suggesting parallelization candidates
- 5. Tracing dynamic dependences (1) Trace is a program P(D) obtained by running a program P on some input D. The basis of parallelism-detection algorithm is the execution trace of a program run on a specific input.
- 6. Tracing dynamic dependences (2) During tracing we define dynamic dependencies: If instruction B of program consumes values computed by A then B is data dependent on A and must be executed after A.
- 7. Detecting parallelism (1) The dynamic dependencies form a dynamic dependence graph. This graph describes how the individual instructions transitively depend on and influence each other.
- 8. Detecting parallelism (2) In the dynamic dependence graph we can identify parallel as well as serial computation paths. The main serial path is critical path H. Critical path H is longest path whose instructions must be executed sequentially.
- 9. Detecting parallelism (3) Ideal speed-up factor of parallelization is n/k where n is the length of program P and k is the length of critical path H.
- 10. Suggesting parallelization candidates Loops placed on critical path H are the most interesting portion of P w.r.t. parallelization. Loops are ranked w.r.t. the potential gain on the execution of program P.
- 11. Example (1) Public static void main(String[] args) { int n = Integer. parseInt(args[0]); long[] sums = new long[n] long overallSum = 0; for (int i = 0; i < n; ++i) { sums[i] = sumTo(i); } for (int i = 0; i < n; ++i) { overallSum += sums[i]; } } private static long sumTo(int n) { return n == 0 ? 0 : n + sumTo(n – 1); }
- 12. Example (2)
- 13. Example (3)
- 14. Example (4)
- 15. Results for example We have 4 threads for parallel execution: Thread 0: 0 2 4 5 10 Thread 1: 1 3 Thread 2: 7 8 Thread 3: 6 9