pector: a C++11 std::vector-compliant implementation with a customizable size type and growing algorithm

pector is a portable C++11 implementation of std::vector with a compatible interface. It aims at fixing issues that can be encountered with the well-known implementations of std::vector (like GNU's and LLVM's) in some corner cases.

For now, it is known to be compatible with these compilers:

GCC 4.8.x and 4.9.x (in C++11 mode)
Clang 3.4, 3.5, 3.6 (in C++11 mode)
Clang under OSX (in C++11 mode)
Microsoft Visual Studio 2015

No C++98-only compiler is supported at this moment. This will be planned for future releases.

Contents

Installation instructions
- Installation with CMake
- Installation by manual copy
Quick usage
Why another vector implementation ?
Features
Advanced usages
Performance of pushing values
TODO
Contribute!
Acknoweldgments
Contacts

Installation instructions

This is a header only library. There are two ways to install it: by using CMake or manual copy.

Installation with CMake

CMake will allow two things: installing the pector headers at the right place in your system and build the tests suite.

Here are the steps:

$ git clone https://github.com/aguinet/pector
$ cd pector
$ mkdir build
$ cmake -DCMAKE_BUILD_TYPE=relwithdebinfo ..
$ make
$ make test
$ sudo make install

It is generally a good idea to run the tests suite to ensure there is no issue with your particular system (especially compiler).

Installation by manual copy

You can manually copy the include/pector directory in your project. You need to set an include path so that

#include <pector/pector.h>

will be valid.

Quick usage

After installation, you just need to include one header file in your project:

#include <pector/pector.h>

Then, you can simply replace std::vector by pt::pector in your code. By default, the same choices as the one done in standard implementations are done, apart from the growing strategy that multiply the size of the vector by 3/2 (instead of 2). With this configuration, you shouldn't see any performance degradations and even some improvements in some cases (see section Advanced usages).

See the Advanced usages section for possible optimisations and improvements for your cases!

Why another vector implementation ?

std::vector does a great job for most use cases, but there are some limitations, due to implementation choices or what the standard actually allows.

Growing strategy

The first limitation is the growth strategy chosen by the implementation. Many of them made one choice that can't be changed by the user. For instance, LLVM's std::vector implementation (as of January 2015) will multiply by 2 the vector capacity if room is needed. You might want to choose a smaller factor, or simply not to do this if for instance your vector already takes 2GB of memory.

sizeof(std::vector)

The second one is the size of an std::vector object. Most implementations uses three pointers to store the beginning, the end (of objects) and the end of storage of the container. This leads to a 24 bytes object on 64-bit systems. If your container as less than ~2**32 objects (which might be often the case ;)), it can be interesting to use two 32-bits unsigned integers to store the number of objects and the capacity of the container.

realloc support

The third one is the lack of support for realloc. The realloc might allow "in-place" reallocation as there are already room available at the end of the actual buffer, thus removing the need for a copy of the previous buffer into the new allocated one. Note that this can only be used for POD objects as this copy is implicitly done by realloc if needed. POD type would need a kind of realloc_no_copy interface to be efficient (a proposal was done for this (http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2013/n3495.txt), but never accepted :/)

We might consider using it for non-POD types, but benchmarking must be done to see if this useless copy is generally negligible versus the potential "in-place reallocation" gain.

"resize but do not construct"

The fourth one is the lack of a "resize but do not construct" operation. This can lead to performance gain in loops like this one:

std::vector<float> f(const size_t n, float const* a, float const* b)
{
    std::pector<float> ret;
    ret.resize(n);
    for (size_t i = 0; i < n; i++) {
      ret[i] = a[i] + b[i];
    }
    return ret;
}

Indeed, in this scenario, the resize method will call the constructor of the "int" object, which will basically set the whole container to 0. This operation is useless as we set the whole container to other values beyond. We could use reserve to avoid this, but we would end up with a code that has to use emplace_back (because with reserve, the size of the container would remain to zero), giving this:

std::vector<float> f(const size_t n, float const* a, float const* b)
{
    std::pector<float> ret;
    ret.reserve(n);
    for (size_t i = 0; i < n; i++) {
      ret.emplace_back(a[i] + b[i]);
    }
    return ret;
}

The issue here is that we have just lost the vectorization that the compiler was able to do (with modern CPUs) with the original code (and some other various optimisations, like the ability to use OpenMP on this loop). So, to have both word, we provide a resize_no_construct API that will actually resize the container without creating the underlying objects. It is the responsability of the caller to do such a thing. The code ends up like this:

std::vector<float> f(const size_t n, float const* a, float const* b)
{
    std::pector<float> ret;
    ret.resize_no_construct(n);
    for (size_t i = 0; i < n; i++) {
      ret[i] = a[i] + b[i];
    }
    return ret;
}

Here, we end-up with a container with the good size, without a useless write of zeros and with a potentially vectorized and/or OpenMP code! This API can be dangerous with non-POD types, see the Advanced usages section for more informations.

Size-aware allocator

Last but not least, std::vector does not leverage the possibility that an allocator might be able to know the amount of allocated memory of a given pointer. This allows two optimisations: being able not to store the capacity of the vector (thus gaining memory) and a better memory usage.

Not reinventing the wheel

Other implementations of std::vector exists (like https://github.com/facebook/folly/blob/master/folly/docs/FBVector.md), but none of them fixed all of these issues. So that's what we tried to achieve here.

We are now describing the various features of pector.

Features

The main features of pector are the following:

stores a pointer and two unsigned integers (for the size and the capacity), instead of three pointers as commonly done. The key feature is the ability to specify the size type:

pt::pector<int, std::allocator<int>> v;
// sizeof(v) == sizeof(int*) + 2*sizeof(size_t)

pt::pector<int, std::allocator<int>, uint32_t> v;
// sizeof(v) == sizeof(int*) + 2*sizeof(uint32_t)

This can save lots of memory in cases where you have a lot of relatively "small" vector objects in your software (especially in 64-bits).

POD-types optimisation: uses memcpy, memmove, memcmp and alike functions when possible with POD types
realloc-aware allocator: for instance, realloc can be used for POD types
size-aware allocator: do not store the capacity of the container if the allocator is capable of giving the allocated size associated with a pointer. For instance, malloc_usable_size can be used on GNU systems.

pt::pector<int, pt::malloc_allocator<int>> v;
// sizeof(v) == sizeof(int*) + sizeof(size_t)

This makes the object 16 bytes wide on 64-bit systems (where std::vector is generally 24 bytes).

configurable growing strategy:

The growing strategy is used when the vector needs to grow (when using emplace, emplace_back, push_back or insert). Most vector implementations do not allow the user to choose how to grow the vector capacity (linearly, exponentially, etc...). By default, pector multiply the capacity by 3/2, but you can implement you own strategy. See pector/recommended_size.h for examples.
resize_no_construct API: this gives the ability to resize a container without calling the default constructor of the underlying objects. For instance, for a vector of integers, this remove the first initialisation at zero, which can be costly in some situations.
if you know what you are doing, integer overflow checks can be disabled for performance reasons.

Advanced usages

Advanced usage are mainly done thanks to the template parameters provided by pector. The API then is the same than std::vector. We describe here how to use them with some examples.

The signature of the pector class is the following:

template <class T, class Alloc = std::allocator<T>, class SizeType = size_t, class RecommendedSize = default_recommended_size, bool check_size_overflow = true>
class pector;

We will explain each parameter and their interest.

Object size optimisation

As said previously, the size of an std::vector object is generally the size of 3 pointers. That is, on 64-bit systems, 24 bytes. As you may not have 2**64 objects in your container, you may want to use 32-bit (or even smaller) unsigned integers to store the size of the container, and thus gain memory.

pector allows this by storing a pointer and two integers whose type is user controllable:

// using uint32_t as size type
pt::pector<int, std::allocator<int>, uint32_t> v1;
std::cout << sizeof(v1) << std::endl;

With default packing, this code will output:

By default, integer overflow checks are performed when the size of the container grows. This can be disabled (see Disabling integer overflow checks).

POD-type detection and perfect forwarding

pector uses optimized functions of the C standard library for memory copying when using POD types.

This adds however an issue for perfect forwarded types. Indeed, it is possible to create an std::vector object for types that are perfectly forwarded (as you only need to store pointers to this type).

For pector to work with perfect forwarded types, you need to specialized std::is_pod for these given types. Here is an example (extracted from tests/forward_decl.cpp) that declares B has a non-POD type:

struct B;

namespace std {
template <>
struct is_pod<B>: public std::false_type { };
} // std

typedef pector<B> pector_b;

Warning

if you declare a non-POD type as a POD one, you will encounter all kinds of memory errors, as objects will never be constructed!

Enhanced malloc-based allocator

pector can use an enhanced interface based on std::allocator to provides more features. The two concepts introduced are:

size-aware allocator: given a pointer allocated by them, these allocators are able to give the real amount of memory reserved (one example is malloc_usable_size). The interface to implement is:

size_type usable_size(const_pointer p) const

reallocable allocator: support for a reallocate(pointer, size_type) function that can potentially reallocate "in place" a given buffer. The interface to implement is:

pointer realloc(pointer p, size_type const n)

In order to have pector still compatible with standard allocator, an "enhanced" allocator has to derive from empty structures in order to "announce" if it supports one of these interfaces. These structures are declared in pector/enhanced_allocators.h and simply are:

struct size_aware_allocator { };
struct reallocable_allocator { };

with the associated "traits":

template <class Alloc>
struct is_size_aware_allocator: public std::is_base_of<size_aware_allocator, Alloc>
{ };

template <class Alloc>
struct is_reallocable_allocator: public std::is_base_of<reallocable_allocator, Alloc>
{ };

One example of such allocator is the malloc_allocator defined in pector/malloc_allocator.h. It uses the C standard malloc,free,realloc to provide the "reallocable" idiom. If GNU extensions are available, it uses the malloc_usable_size function to provide the "size-aware" idiom.

Moreover, the user can choose which idiom to "enable", using two boolean template parameters:

template <class T, bool make_reallocable = true, bool make_size_aware = false>
class malloc_allocator;

For instance, this pector object:

pt::pector<int, pt::malloc_allocator<int, true, false>> v;

will uses realloc for reallocations but won't do any size optimisation of the vector object (as described in Object size optimisation).

The growing strategy

When a pector object needs to grow (using emplace_back for instance), it has to decide about its new capacity size. The first solution would just be to add the necessary space, but this can lead to quadratic growth performance (see http://www.drdobbs.com/c-made-easier-how-vectors-grow/184401375 for a nice explanation of this phenomena).

What could be interesting though is to control the

The existing strategies are the following:

dummy (class recommended_size_dummy): just return the wanted capacity ;
multiply (class recommended_size_multiply_by): multiply the old capacity by a rational fraction. This is the one used by default with 3/2 ;
add (class recommended_size_add_by): just add a constant the old capacity.

To use a particular strategy, just specific it when instantiating the pector object:

// This will create a pector object with a growing strategy of multiplying the old capacity by 2
pt::pector<int, std::allocator<int>, size_t, pt::recommended_size_multiply_by<2,1>> v;

The default one is used with a factor of 1.5, which allows for a better memory usage with common allocators (see https://github.com/facebook/folly/blob/master/folly/docs/FBVector.md for an explanation).

To implement a new growing strategy (which might better fit a specific allocator, like what have been done with FBVector in the link above), just declare a structure with one interface:

struct my_recommended_size
{
      template <class SizeType>
      static inline SizeType recommended(SizeType const max_size, SizeType const old_cap, SizeType const new_cap);
};

The role of the recommended function is to return the new capacity of the vector given the old one, the new wanted one and the maximum number of objects that the container can hold.

"Resize but do not construct" idiom

See above for the explanation about the necessity of such idiom. The resize_no_construct function will change the actual size of the container to the user-supplied one without creating underlying objects.

Warning

when using this API with non-POD types, the user is responsible for the creation of the new objects! Maybe this feature will be only available for POD-types in the future.

Disabling integer overflow checks

Integer overflow checks are done in the function that needs to enlarge the size of the container (like emplace_back). If such overflow occurs, an std::length_error exception is thrown.

If you known what you are doing, and, for performance reasons, you want to disable this check, you can do so by using the last template parameter of a pector object. For instance:

pector<int, std::allocator<int>, size_t, pt::default_recommended_size, false> v;

will create an object that will not perform these checks.

Please note that they only occur at the level of the number of objects inside the container, not its capacity. This issue at the "capacity level" is handled by the growing strategy (see The growing strategy).

Performance of pushing values

Below is a graph of the performances of adding a given number of consecutive signed 32-bit integers, using different configurations. The code use is in the grow_perfs test case. This is a compared against GCC's libstdc++ std::vector implementation. These tests have been run on a Core i7 i7-3520M.

The first configuration is using pector with the standard allocator, and two growing strategies : one that multiples the allocated size by 1.5, and the other by 2. The results are show below:

Then, pector is used with the special malloc_allocator in reallocable mode (without the "size-aware" mode), still using the same two growing strategies. The results are shown below:

Finally, pector is used with the special malloc_allocator in reallocable and "size-aware" mode, using the same two growing strategies. The results are shown below:

What we can see is that using realloc implies a nice performance gain (~x3 against the standard std::vector class). We can also notice that pector is equivalent or better than the standard implementation in every case but when the allocator is "size-aware". This is due to the cost of the calls to malloc_usable_size (see TODO below).

Note also that the internal state of the standard allocator might influence the performances of such workloads, thus benchmarking your own code in "real-life situation" is still necessary to see the real benefits of pector.

TODO

TODO list:

use malloc_usable_size the get the real vector capacity when possible (and still store the allocation size for performance reasons, see Performance of pushing values).
be less strict between the types of the pector objects that can be swapped
C++98 only compiler support

headmyshoulder/pector

pector: a C++11 std::vector-compliant implementation with a customizable size type and growing algorithm