c++ vector example - STL Alternative

4 Answers

My experience is that well designed STL code runs slowly in debug builds because the optimizer is turned off. STL containers emit a lot of calls to constructors and operator= which (if they are light weight) gets inlined/removed in release builds.

Also, Visual C++ 2005 and up has checking enabled for STL in both release and debug builds. It is a huge performance hog for STL-heavy software. It can be disabled by defining _SECURE_SCL=0 for all your compilation units. Please note that having different _SECURE_SCL status in different compilation units will almost certainly lead to disaster.

You could create a third build configuration with checking turned off and use that to debug with performance. I recommend you to keep a debug configuration with checking on though, since it's very helpful to catch erroneous array indices and stuff like that.


arduino c++ stl

I really hate using STL containers because they make the debug version of my code run really slowly. What do other people use instead of STL that has reasonable performance for debug builds?

I'm a game programmer and this has been a problem on many of the projects I've worked on. It's pretty hard to get 60 fps when you use STL container for everything.

I use MSVC for most of my work.

Why does a C/C++ program often have optimization turned off in debug mode?

Without any optimization on, the flow through your code is linear. If you are on line 5 and single step, you step to line 6. With optimization on, you can get instruction re-ordering, loop unrolling and all sorts of optimizations.
For example:

void foo() {
1:  int i;
2:  for(i = 0; i < 2; )
3:    i++;
4:  return;

In this example, without optimization, you could single step through the code and hit lines 1, 2, 3, 2, 3, 2, 4

With optimization on, you might get an execution path that looks like: 2, 3, 3, 4 or even just 4! (The function does nothing after all...)

Bottom line, debugging code with optimization enabled can be a royal pain! Especially if you have large functions.

Note that turning on optimization changes the code! In certain environment (safety critical systems), this is unacceptable and the code being debugged has to be the code shipped. Gotta debug with optimization on in that case.

While the optimized and non-optimized code should be "functionally" equivalent, under certain circumstances, the behavior will change.
Here is a simplistic example:

    int* ptr = 0xdeadbeef;  // some address to memory-mapped I/O device
    *ptr = 0;   // setup hardware device
    while(*ptr == 1) {    // loop until hardware device is done
       // do something

With optimization off, this is straightforward, and you kinda know what to expect. However, if you turn optimization on, a couple of things might happen:

  • The compiler might optimize the while block away (we init to 0, it'll never be 1)
  • Instead of accessing memory, pointer access might be moved to a register->No I/O Update
  • memory access might be cached (not necessarily compiler optimization related)

In all these cases, the behavior would be drastically different and most likely wrong.

Optimizing code is an automated process that improves the runtime performance of the code while preserving semantics. This process can remove intermediate results which are unncessary to complete an expression or function evaluation, but may be of interest to you when debugging. Similarly, optimizations can alter the apparent control flow so that things may happen in a slightly different order than what appears in the source code. This is done to skip unnecessary or redundant calculations. This rejiggering of code can mess with the mapping between source code line numbers and object code addresses making it hard for a debugger to follow the flow of control as you wrote it.

Debugging in unoptimized mode allows you to see everything you've written as you've written it without the optimizer removing or reordering things.

Once you are happy that your program is working correctly you can turn on optimizations to get improved performance. Even though optimizers are pretty trustworthy these days, it's still a good idea to build a good quality test suite to ensure that your program runs identically (from a functional point of view, not considering performance) in both optimized and unoptimized mode.

If your vector will be reallocated many times then yes, it can cause memory fragmentation. The simplest way to avoid that would be using std::vector::reserve() if you more or less know how big your array can grow.

You can also consider using std::deque instead of vector, so you won't have problem with memory fragmentation at all.

Here is topic on which can be interesting for you: what-is-memory-fragmentation.