What is your basis for this claim? C and C++ are both built on essentially the same memory and execution model. There is a significant set of programs that are valid C and C++ both -- surely you're not suggesting that merely compiling them as C++ will make them faster?
There's basically no performance technique available in C++ that is not also available in C. I don't think it's meaningful to call one faster than the other.
Yes, you can write most things in modern C++ in roughly equivalent C with enough code, complexity, and effort. However, the disparate economics are so lopsided that almost no one ever writes the equivalent C in complex systems. At some point, the development cost is too high due to the limitations of the expressiveness and abstractions. Everyone has a finite budget.
I’ve written the same kinds of systems I write now in both C and modern C++. The C equivalent versions require several times the code of C++, are less safe, and are more difficult to maintain. I like C and wrote it for a long time but the demands of modern systems software are a beyond what it can efficiently express. Trying to make it work requires cutting a lot of corners in the implementation in practice. It is still suited to more classically simple systems software, though I really like what Zig is doing in that space.
I used to have a lot of nostalgia for working in C99 but C++ improved so rapidly that around C++17 I kind of lost interest in it.
You can argue that C takes more effort to write, but if you write equivalent programs in both (ie. that use comparable data structures and algorithms) they are going to have comparable performance.
In practice, many best-in-class projects are written in C (Lua, LuaJIT, SQLite, LMDB). To be fair, most of these projects inhabit a design space where it's worth spending years or decades refining the implementation, but the combination of performance and code size you can get from these C projects is something that few C++ projects I have seen can match.
For code size in particular, the use of templates makes typical C++ code many times larger than equivalent C. While a careful C++ programmer could avoid this (ie. by making templated types fall back to type-generic algorithms to save on code size), few programmers actually do this, and in practice you end up with N copies of std::vector, std::map, etc. in your program (even the slow fallback paths that get little benefit from type specialization).
Great question! Here's one answer:
Having written a great deal of C code, I made a discovery about it. The first algorithm and data structure selected for a C program, stayed there. It survives all the optimizations, refactorings and improvements. But everyone knows that finding a better algorithm and data structure is where the big wins are.
Why doesn't that happen with C code?
C code is not plastic. It is brittle. It does not bend, it breaks.
This is because C is a low level language that lacks higher level constructs and metaprogramming. (Yes, you can metaprogram with the C preprocessor, a technique right out of hell.) The implementation details of the algorithm and data structure are distributed throughout the code, and restructuring that is just too hard. So it doesn't happen.
A simple example:
Change a value to a pointer to a value. Now you have to go through your entire program changing dots to arrows, and sprinkle stars everywhere. Ick.
Or let's change a linked list to an array. Aarrgghh again.
Higher level features, like what C++ and D have, make this sort of thing vastly simpler. (D does it better than C++, as a dot serves both value and pointer uses.) And so algorithms and data structures can be quickly modified and tried out, resulting in faster code. A traversal of an array can be changed to a traversal of a linked list, a hash table, a binary tree, all without changing the traversal code at all.
When people claim C++ to be faster than C, that is usually understood as C++ provides tools that makes writing fast code easier than C, not that the fastest possible implementation in C++ is faster than the fastest possible implementation in C, which is trivially false as in both cases the fastest possible implementation is the same unmaintainable soup of inline assembly.
The typical example used to claim C++ is faster than C is sorting, where C due to its lack of templates and overloading needs `qsort` to work with void pointers and a pointer to function, making it very hard on the optimiser, when C++'s `std::sort` gets the actual types it works on and can directly inline the comparator, making the optimiser work easier.
That said, external comparators are a weakness of generic C library functions. I once manually inlined them in some performance critical code using the C preprocessor:
https://github.com/openzfs/zfs/commit/677c6f8457943fe5b56d7a...
One of the strengths of C++ is that it is well-suited to compile-time codegen of hyper-optimized data structures. In fact, that is one of the features that makes it much better than C for performance engineering work.
But if you look beyond, you can find a whole world that extend the stl. If you are not happy, say, with unordered_map, you can find more or less drop in replacements that use the same iterator based interface, preserve value semantics and use the a common language to describe iterator and reference invalidation.
Regarding your specific use case, if you want intrusive lists you can use boost.intrusive which provides containers with STL semantics except it leaves ownership of the nodes to the user. The containers do not even need to be lists: you can put the same node in multiple lists linked list, binary trees (multiple flavors), and hash maps (although this is not fully intrusive) at the same time.
These days I don't generally need boost much, but I still reach for boost.intrusive quite often.
https://github.com/openzfs/zfs/commit/677c6f8457943fe5b56d7a...
The performance gain comes not from eliminating the function overhead, but enabling conditional move instructions to be used in the comparator, which eliminates a pipeline hazard on each loop iteration. There is some gain from eliminating the function overhead, but it is tiny in comparison to eliminating the pipeline hazard.
That said, C++ has its weaknesses too, particularly in its typical data structures, its excessive use of dynamic memory allocation and its exception handling. I gave an example here:
https://news.ycombinator.com/item?id=43827857
Honestly, I think these weaknesses are more severe than qsort being unable to inline the comparator.
Does not work if the compiler can not look into the function, but the same is true in C++.
