What is the performance cost of having a virtual method in a C++ class?

by

I ran some timings on a 3ghz in-order PowerPC processor. On that architecture, a virtual function call costs 7 nanoseconds longer than a direct (non-virtual) function call.

So, not really worth worrying about the cost unless the function is something like a trivial Get()/Set() accessor, in which anything other than inline is kind of wasteful. A 7ns overhead on a function that inlines to 0.5ns is severe; a 7ns overhead on a function that takes 500ms to execute is meaningless.

The big cost of virtual functions isn’t really the lookup of a function pointer in the vtable (that’s usually just a single cycle), but that the indirect jump usually cannot be branch-predicted. This can cause a large pipeline bubble as the processor cannot fetch any instructions until the indirect jump (the call through the function pointer) has retired and a new instruction pointer computed. So, the cost of a virtual function call is much bigger than it might seem from looking at the assembly… but still only 7 nanoseconds.

Edit: Andrew, Not Sure, and others also raise the very good point that a virtual function call may cause an instruction cache miss: if you jump to a code address that is not in cache then the whole program comes to a dead halt while the instructions are fetched from main memory. This is always a significant stall: on Xenon, about 650 cycles (by my tests).

However this isn’t a problem specific to virtual functions because even a direct function call will cause a miss if you jump to instructions that aren’t in cache. What matters is whether the function has been run before recently (making it more likely to be in cache), and whether your architecture can predict static (not virtual) branches and fetch those instructions into cache ahead of time. My PPC does not, but maybe Intel’s most recent hardware does.

My timings control for the influence of icache misses on execution (deliberately, since I was trying to examine the CPU pipeline in isolation), so they discount that cost.

More Related Contents:

  1. Virtual functions and performance – C++
  2. Performance penalty for working with interfaces in C++?
  3. Which yields faster code?
  4. How to get the CPU cycle count in x86_64 from C++?
  5. How to overload std::swap()
  6. Why is my program slow when looping over exactly 8192 elements?
  7. Why does C++ compilation take so long?
  8. What is the efficient way to count set bits at a position or lower?
  9. Fastest way to determine if an integer is between two integers (inclusive) with known sets of values
  10. virtual assignment operator C++
  11. How can I measure CPU time and wall clock time on both Linux/Windows?
  12. Efficient way of storing Huffman tree
  13. How do exceptions work (behind the scenes) in c++
  14. Why are Python Programs often slower than the Equivalent Program Written in C or C++?
  15. Is there any guarantee of alignment of address return by C++’s new operation?
  16. Getting an accurate execution time in C++ (micro seconds)
  17. Does a C++11 range-based for loop condition get evaluated every cycle?
  18. Can the use of C++11’s ‘auto’ improve performance?
  19. A fast method to round a double to a 32-bit int explained
  20. linux perf: how to interpret and find hotspots
  21. Is there a 128 bit integer in C++?
  22. Calling a virtual function from the constructor
  23. What is the Fastest Method for High Performance Sequential File I/O in C++?
  24. Return Type Covariance with Smart Pointers
  25. Fastest way to get a positive modulo in C/C++
  26. Do c++ templates make programs slow?
  27. Performance Tradeoff – When is MATLAB better/slower than C/C++
  28. Memory-efficient C++ strings (interning, ropes, copy-on-write, etc) [closed]
  29. Fastest way to get the integer part of sqrt(n)?
  30. Why is this SIMD multiplication not faster than non-SIMD multiplication?

Leave a Comment