How do I diagnose long link times with GCC for C++?

Long link times when compiling C++ programs with GCC can be a frustrating experience for developers. Diagnosing the root cause of these delays is essential for improving build efficiency and productivity. Below are some common factors that can contribute to long link times, along with solutions to help you identify and reduce them.

GCC, C++, long link times, diagnosing linker issues, compile time optimization, build efficiency, reduce link time

Learn how to diagnose and fix long link times when using GCC for C++ compilation. Discover strategies to optimize build processes and improve development workflow.

Here’s an example of how to investigate long linking times using the GCC toolchain:

// Check for unnecessary dependencies gcc -o my_program main.o utils.o -Wl,--print-map > link.map // Analyze the generated map file for large object files less link.map // Use separate translation units to minimize linker load g++ -o my_program main.cpp utils.cpp

To further diagnose linking issues:

  • Use --verbose or -v flags to get detailed output from the linker.
  • Check for circular dependencies between object files.
  • Use tools like size and nm to inspect object file sizes and symbols.
  • Consider using link-time optimization (LTO) to optimize across translation units.

GCC C++ long link times diagnosing linker issues compile time optimization build efficiency reduce link time

Related Questions

How do I avoid rehashing overhead with std::set in multithreaded code?

How do I find elements with custom comparators with std::set for embedded targets?

How do I erase elements while iterating with std::set for embedded targets?

How do I provide stable iteration order with std::unordered_map for large datasets?

How do I reserve capacity ahead of time with std::unordered_map for large datasets?

How do I erase elements while iterating with std::unordered_map in multithreaded code?

How do I provide stable iteration order with std::map for embedded targets?

How do I provide stable iteration order with std::map in multithreaded code?

How do I avoid rehashing overhead with std::map in performance-sensitive code?

How do I merge two containers efficiently with std::map for embedded targets?