Compiling using optimizing compiler options

This tutorial is done on Puhti, which requires that:

Overview

💭 Without any optimization options, a compiler tries to reduce the computational cost of compiling and to make debugging produce the expected results. Turning on optimization flags makes the compiler attempt to improve the performance and/or code size at the expense of compilation time and possibly the ability to debug the program.

☝🏻 It is recommended to start with safe (basic) optimization, and then move up to intermediate, or even aggressive, while ensuring that results produced by the program remain correct and that the performance actually improves.

Compare different optimization flags

💬 This tutorial examines a simple C++ code that computes the Laplacian for a two-dimensional field. We’ll use gcc to compile the code with different optimization options and observe how they affect performance. Understanding the details of the program is not important for completing this tutorial, just consider it an illustrative example.

  1. Create and enter a suitable scratch directory on Puhti (replace <project> with your CSC project, e.g. project_2001234):

    mkdir -p /scratch/<project>/$USER/laplacian
cd /scratch/<project>/$USER/laplacian

    ☝🏻 Own software should normally be installed under /projappl, but for the sake of this exercise it is sufficient to use /scratch.

  2. Download the source code from Allas:

    wget https://a3s.fi/CSC_training/laplacian.cpp

  3. To avoid causing unnecessary load on the login node, launch an interactive session on a compute node:

    sinteractive --account <project> --time 00:15:00 --tmp 0  # replace <project> with your CSC project, e.g. project_2001234

  4. First, compile the code using gcc without optimizing compiler options:

    gcc -fopenmp -o laplacian laplacian.cpp
    • -o laplacian instructs the compiler to name the executable output as laplacian.
    • -fopenmp flag is needed for this code since it uses OpenMP directives.

  5. Run the code as (should take about two minutes):

    ./laplacian

  6. Recompile the code using safe (-O2), intermediate (-O3) and aggressive (-Ofast) optimization options. For example:

    gcc -O2 -fopenmp laplacian.cpp -o laplacian_O2

  7. Re-run the program for each optimization level.

    • How much does the performance improve in each case?
    • Do the results remain the same for all optimization levels?

💡 In this case -Ofast increases code size by roughly 10% compared to using no optimization flags. Although the absolute difference for such a small code is insignificant (only about 2 KB), it is good to keep in mind that optimization may affect output program size. Similarly, more aggressive optimization typically increases compilation time and may worsen debugging experience.

☝🏻 Aggressive optimization may result in programs producing less precise or even incorrect results. Please be aware of this and thoroughly benchmark your code when using aggressively optimizing compiler flags.

💡 As the example code here is so small, it is not necessary to compile on the fast local disk to move I/O load away from the shared file system. However, when building a larger, more realistic software package, please use $TMPDIR to avoid stressing Lustre.

Bonus: Fortran version

  1. Re-run the previous steps for a similar program written in Fortran instead of C++. You may download the source code from Allas:

    wget https://a3s.fi/CSC_training/laplacian.F90

  2. Use gfortran compiler instead of gcc. The previous options are the same for both compilers.

💭 How does the performance and results compare with the C++ code? Does gfortran deliver similar improvements as gcc?

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