TauferLab / CSMPI

A PMPI module for tracing call-stacks

Summary:

CSMPI is a PMPI module for tracing call-stacks of MPI functions. You may want to know which chains of function calls in your application end in calls to certain MPI functions; CSMPI can help you find out.

Installation:

• Run one_step_build.sh

Usage:

• Link CSMPI with your MPI application explicitly, via LD_PRELOAD, or via a "tool-stacking" layer like PnMPI (https://github.com/LLNL/PnMPI).
• Pick a configuration file from the config subdirectory or create one using config/generate_config.py.
• Set CSMPI_CONFIG environment variable to the path of your configuration file.
• When the application CSMPI is linked to calls MPI_Finalize, CSMPI will write out one trace file per MPI rank.

Configuration:

• CSMPI supports tracing callstacks with:
  • libunwind
  • glibc backtrace.

By default, CSMPI is set to build using glibc. However, you can change CSMPI to build using libunwind by changing the following line in the file 'one_step_build.sh':

cmake -DUSE_LIBUNWIND=OFF ..

to instead use '-DUSE_LIBUNWIND=ON'. To use libunwind, the line should look like the following:

cmake -DUSE_LIBUNWIND=ON ..

Tracing Overhead:

Callstack tracing can impose large runtime overheads. Hence you should:

• Use the glibc backtrace configuration rather than libunwind if possible
• Do not do in-place address translation or name-demangling without a good reason
• Set your tracing frequency carefully
• Avoid tracing as many MPI functions as possible

Dependencies:

• CMake
• JSON for Modern C++ (https://github.com/nlohmann/json)
• Boost (Serialization, MPI)
• libunwind (Optional)

Copyright and License:

Copyright (c) 2021, Global Computing Lab

ANACIN-X is distributed under terms of the Apache License, Version 2.0 with LLVM Exceptions.

See LICENSE for more details.