The Chained-group allocation pattern

Matt Bentley. Last updated: 21/08/2017


This document describes a pattern of memory expansion for data containers, namely doubly-linked chains of increasingly-large memory blocks with metadata attached to them, each of which doubles the number of elements capable of being stored within the container prior to it's instantiation (ie. a growth factor of 2).


This is a simple technique for allocating memory in a situation where the amount of memory needed is not known in advance, for example, for a dynamically-expanding data container such as a dynamic array or C++ vector. We can define a 'group' in this context as a struct containing both a memory block for storage as well as metadata necessary for utilizing the memory block. The metadata we store is both pointers to previous and next groups, and any other data necessary for the groups to be utilized by the container's iterators. This could include the number of elements able to be stored in the group, the number of elements currently stored in the group, the end element of the group, skipfields, and so on.

As mentioned above, the memory blocks in this pattern have a growth factor of 2, though this could be adjusted to preference. I will now illustrate this. To start with, you allocate a small block of memory of fixed size. As an example, let's hypothesize a C++ vector of 32-bit integers, using this memory pattern. We initialize the vector, and it creates a memory block large enough to hold 8 integers as it's initial memory block:

Memory block 1: 0 0 0 0 0 0 0 0

Once that block is full (ie. the container has had enough objects inserted into it to fill up the available space), we allocate another memory block large enough to double the number of objects that can be held within the container. Continuing the vector example above, let's say we've now filled the initial 8 spaces available:

Memory block 1: 1 5 6 2 7 1 5 2

and now wish to add another number to the vector. At this point we must double the space available, which means we need to adding another memory block large enough to hold 8 integers:

Memory block 1: 1 5 6 2 7 1 5 2
Memory block 2: 0 0 0 0 0 0 0 0

and insert into it:

Memory block 1: 1 5 6 2 7 1 0 2
Memory block 2: 4 0 0 0 0 0 0 0

Now we simply continue this pattern every time we run out of space. Continuing the vector example above, the next allocated memory block would be large enough to hold 16 integers:

Memory block 1: 1 5 6 2 7 1 5 2
Memory block 2: 4 3 1 3 4 1 6 4
Memory block 3: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

and the next memory block after that would be large enough to hold 32 integers, etcetera.


The most significant advantage of having a chain of separate memory blocks, over the reallocation of all elements to a single memory block (as is favoured by std::vector and many others), is the stability of pointers/iterators, which is unaffected by element insertion. No matter how many elements get added to a container using this pattern, adding elements never triggers pointer/iterator invalidation - which can be of great use for both modular and object-oriented programming architectures, as it decreases busywork/workarounds in terms of avoiding invalidation, and thus decreases development time.

By keeping metadata for each memory block attached to the memory block (in a 'group') rather than in some central repository of the container's, we reduce computational complexity if we decide to remove one of those memory blocks from the chain. In the case of a centralised repository and raw memory blocks, we would have to implement some sort of extensible container to keep track of the metadata and allow it to expand on-the-fly - a vector, list or deque of some description. By attaching the metadata to the memory block, we negate the need to have two separate storage/expansion mechanisms. In some cases, this will lead to performance gains, especially when new memory blocks are being created/erased in realtime.

Adding elements to a container using this chained-group pattern is typically much faster than adding to a container using a single memory block and reallocation due to the fact that no data needs to be reallocated upon expansion of the container. Freeing up unused memory also becomes a possibility, because when memory blocks become empty due to erasures, one can destruct the group and link the previous group and subsequent group to each other, thus removing the group from the chain as you would in a linked-list. In the case of a stack, you might remove trailing blocks from the chain once all their elements have been popped.

In addition, this pattern has an advantage over a vector of groups (pointer to memory block plus metadata), which is that no reallocation is required upon creation of a new group, which can dramatically increase insertion speed in some scenarios.


In terms of iteration over all container elements, an entirely-contiguous single memory block would result in faster iteration compared to a chained list of groups, due to the reduced complexity during this operation and increased cache performance. For a chained-group pattern, a check for end-of-block is required for each +1 forward-iteration through the elements, just as a check for beginning-of-block is required for each -1 reverse-iteration. This proves to be less-detrimental than might be expected in actual benchmarks, due to CPU branch-prediction which only fails in the least-common case of end-block/beginning-block; but this does reduces iteration performance by comparison.

Utilizing a growth factor of 2 for the memory blocks aids in reducing this performance loss as the end-block/beginning-block cases become statistically-smaller. As mentioned earlier, the multiple-memory block approach allows a container to remove groups containing memory blocks which have become empty due to erasures, without affecting pointer stability for other non-erased memory blocks. But having a memory block expand too much could lead to situations where you have a very large memory block with only one or two non-erased elements, so it may be necessary to limit the maximum size of memory blocks in these scenarios.

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