MPI-Profiler ·

A C++ static library for fine-grain profiling MPI programs. Measure each MPI routines & CPU time for each process with better visualization.

📚 Table of contents

• Technical stack
• Features
• Installation
• Usage
• Contributors
• License

⚙ Technical stack

• C++
• MPI

🚀 Features

• Time MPI routines used in linked programs
• Render timed result in mpi_record.<process_id>

⬇ Installation

• In order to run MPI, you should have GNU C++ compiler (g++).
  • For Windows users, you should start by installing MinGW Package Installer
  • For Mac users, XCode has already (most of the time) had g++ pre-installed to you
  • For Ubuntu users, you can download Homebrew and use the following command brew install gcc
• MPICC/C++ is included with GNU package.

📋 Usage

• To compile and get the static library mpi_timer.a, run make
• To profile your program, compile & run it together with the generated .a file and supply number of threads:
  • For example, to profile mpi_test.cpp running with 4 tasks (processes), either way works:
    make all SRC=mpi_test.cpp NP=4
    or
    mpic++ mpi_timer.a mpi_test.cpp -o run && mpirun ./run -np 4
• After compile & run, each timing result for each process p will be in mpi_record.p file
• To clean object files, run make clean
• To clean processes' records, run make clean_all

👨‍💻 Contributors

• Dung Tuan Le
  Computer Science major.
  University of Rochester '21.

📄 License

Kronos is MIT licensed.