TAU

Description

Tau website  

• TAU Performance System® is a portable profiling and tracing toolkit for performance analysis of parallel programs written in Fortran, C, C++, Java, Python.
• TAU (Tuning and Analysis Utilities) is capable of gathering performance information through instrumentation of functions, methods, basic blocks, and statements. All C++ language features are supported including templates and namespaces. The API also provides selection of profiling groups for organizing and controlling instrumentation. The instrumentation can be inserted in the source code using an automatic instrumentor tool based on the Program Database Toolkit (PDT), dynamically using DyninstAPI, at runtime in the Java Virtual Machine, or manually using the instrumentation API.
• TAU's profile visualization tool, paraprof, provides graphical displays of all the performance analysis results, in aggregate and single node/context/thread forms. The user can quickly identify sources of performance bottlenecks in the application using the graphical interface. In addition, TAU can generate event traces that can be displayed with the Vampir, Paraver or JumpShot trace visualization tools.

Required Modules

Run module spider Tau to find out what environment modules are available for this application.

System Variables

• TAU - Tau library directory
• TAUROOT - installation directory
• TAU_MAKEFILE - default makefile
• TAU_METRICS = LINUXTIMERS:PAPI_FP_OPS:PAPI_L2_DCM
• TAU_PROFILE = 1
• TAU_TRACE = 0
• TAU_CALLPATH = 1

• HPC_TAU_DIR - installation directory
• HPC_TAU_BIN - executable directory
• HPC_TAU_LIB - library directory
• HPC_TAU_DOC - examples directory
• HPC_PDT_DIR - installation directory
• HPC_PDT_BIN - executable directory
• HPC_PDT_INC - includes directory
• PAPI_PERFMON_EVENT_FILE - default performance event log file.

Citation

If you publish research that uses {{{app}}} you have to cite it as follows:

• TAU: The TAU Parallel Performance System, by S. Shende and A. D. Malony. International Journal of High Performance Computing Applications, Volume 20 Number 2 Summer 2006. Pages 287-311.
• PDT: A Tool Framework for Static and Dynamic Analysis of Object-Oriented Software with Templates, by K. A. Lindlan, J. Cuny, A. D. Malony, S. Shende, B. Mohr, R. Rivenburgh, C. Rasmussen. Proceedings of SC2000: High Performance Networking and Computing Conference, Dallas, November 2000.
• CCA: Performance Technology for Parallel and Distributed Component Software, by A. Malony, S. Shende, N. Trebon, J. Ray, R. Armstrong, C. Rasmussen, and M. Sottile. Concurrency and Computation: Practice and Experience, Vol. 17, Issue 2-4, pp. 117-141, John Wiley & Sons, Ltd., Feb - Apr, 2005.