Bibliography

1

Bailey, D., Harris, T., Saphir, W., van der Wijngaart, R., Woo, A. and Yarrow, M., 1995.
The nas parallel benchmarks 2.0.
Technical Report Technical Report NAS-95-020, NASA Ames Research Center.

2

Bronevetsky, G., Marques, D., Pingali, K. and Stodghill, P., 2003a.
Automated application-level checkpointing of mpi programs.
In Principles and Practice of Parallel Programming (PPoPP).

3

Bronevetsky, G., Marques, D., Pingali, K. and Stodghill, P., 2003b.
Collective operations in an application-level fault tolerant mpi system.
In International Conference on Supercomputing (ICS).

4

Browne, S., Dongarra, J., Garner, N., Ho, G. and Mucci, P., 2000.
A portable programming interface for performance evaluation on modern processors.
International Journal of High Performance Computing Applications 14(3):189-204.

5

Fahringer, T. and Seragiotto, C., 2002.
Experience with aksum: A semi-automatic multi-experiment performance analysis tool for parallel and distributed applications.
In Workshop on Performance Analysis and Distributed Computing.

6

Graham, S., Kessler, P. and McKusick, M., 1982.
gprof: A call graph execution profiler.
In SIGPLAN Symposium on Compiler Construction, pp. 120-126.

7

IBM.
Profiling parallel programs with xprofiler.
In IBM Parallel Environment for AIX: Operation and Use, volume Volume 2.

8

Janssen, C.
The visual profiler.
URL http://aros.ca.sandia.gov/ cljanss/perf/vprof/.

9

Knuth, D., 1971.
An empirical study of fortran programs.
Software Practice and Experience 1:105-133.

10

Kranzlmüller, D., 2000.
Event Graph Analysis for Debugging Massively Parallel Programs.
Ph.d., Johanne Kepler Universität Linz.

11

Laboratories, B., 1979.
prof command.
In Unix Programmer's Manual, volume Section 1. Murray Hill, NJ.

12

Malony, A., 1991a.
Event based performance perturbation: A case study.
In Principles and Practices of Parallel Programming (PPoPP), pp. 201-212.

13

Malony, A., 1991b.
Performance Observability.
Ph.d., University of Illinois at Urbana-Champaign.

14

Malony, A. and Reed, D., 1991.
Models for performance perturbation analysis.
In ACM/ONR Workshop on Parallel and Distributed Debugging, pp. 1-12.

15

Malony, A., Reed, D. and Wijshoff, H., 1992.
Performance measurement intrusion and perturbation analysis.
IEEE Transactions on Parallel and Distributed Systems 3(4):433-450.

16

Malony, A. and Shende, S., 2004.
Overhead compensation in performance profiling.
In Euro-Par Conference, volume LNCS 3149, pp. 119-132. Springer.

17

Malony, A. and Shende, S., 2005.
Models for on-the-fly compensation of measurement overhead in parallel performance profiling.
In Euro-Par Conference, volume LNCS 3648, pp. 72-82. Springer.

18

Mellor-Crummey, J., Fowler, R. and Marin, G., 2002.
Hpcview: A tool for top-down analysis of node performance.
Journal of Supercomputing 23:81-104.

19

Mucci, P.
Dynaprof.
URL http://www.cs.utk.edu/ mucci/dynaprof.

20

Reed, D., Rose, L. D. and Zhang, Y., 1998.
Svpablo: A multi-language performance analysis system.
In International Conference on Performance Tools, pp. 352-355.

21

Rose, L. D., 2001.
The hardware performance monitor toolkit.
In Euro-Par Conference, volume LNCS 2150, pp. 122-131. Springer.

22

Sarukkai, S. and Malony, A., 1993.
Perturbation analysis of high-level instrumentation for spmd programs.
In Principles and Practices of Parallel Programming (PPoPP), pp. 44-53.

23

Shende, S. and Malony, A., 2006.
The tau parallel performance system.
International Journal of High Performance Computing Applications 20(2):287-331.

24

Vetter, J., 2002.
Dynamic statistical profiling of communication activity in distributed applications.
In ACM SIGMETRICS Joint International Conference on Measurement and Modeling of Computer Systems.

25

Williams, W., Hoel, T. and Pase, D., 1994.
The mpp apprentice performance tool: Delivering the performance of the cray t3d.
In Programming Environments for Massively Parallel Distributed Systems. North-Holland.

Table 1: A comparison of parallel overhead compensation scheme in Monte-carlo integrator

Task	No instrumentation	No compensation	Local compensation	Parallel compensation
Master	73.926	128.179	139.56	73.926
Worker	73.834	128.173	73.212	73.909