136 lines
7.4 KiB
Markdown
136 lines
7.4 KiB
Markdown
Notes on `sharded-slab`'s implementation and design.
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# Design
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The sharded slab's design is strongly inspired by the ideas presented by
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Leijen, Zorn, and de Moura in [Mimalloc: Free List Sharding in
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Action][mimalloc]. In this report, the authors present a novel design for a
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memory allocator based on a concept of _free list sharding_.
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Memory allocators must keep track of what memory regions are not currently
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allocated ("free") in order to provide them to future allocation requests.
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The term [_free list_][freelist] refers to a technique for performing this
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bookkeeping, where each free block stores a pointer to the next free block,
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forming a linked list. The memory allocator keeps a pointer to the most
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recently freed block, the _head_ of the free list. To allocate more memory,
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the allocator pops from the free list by setting the head pointer to the
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next free block of the current head block, and returning the previous head.
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To deallocate a block, the block is pushed to the free list by setting its
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first word to the current head pointer, and the head pointer is set to point
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to the deallocated block. Most implementations of slab allocators backed by
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arrays or vectors use a similar technique, where pointers are replaced by
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indices into the backing array.
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When allocations and deallocations can occur concurrently across threads,
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they must synchronize accesses to the free list; either by putting the
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entire allocator state inside of a lock, or by using atomic operations to
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treat the free list as a lock-free structure (such as a [Treiber stack]). In
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both cases, there is a significant performance cost — even when the free
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list is lock-free, it is likely that a noticeable amount of time will be
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spent in compare-and-swap loops. Ideally, the global synchronzation point
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created by the single global free list could be avoided as much as possible.
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The approach presented by Leijen, Zorn, and de Moura is to introduce
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sharding and thus increase the granularity of synchronization significantly.
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In mimalloc, the heap is _sharded_ so that each thread has its own
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thread-local heap. Objects are always allocated from the local heap of the
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thread where the allocation is performed. Because allocations are always
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done from a thread's local heap, they need not be synchronized.
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However, since objects can move between threads before being deallocated,
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_deallocations_ may still occur concurrently. Therefore, Leijen et al.
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introduce a concept of _local_ and _global_ free lists. When an object is
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deallocated on the same thread it was originally allocated on, it is placed
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on the local free list; if it is deallocated on another thread, it goes on
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the global free list for the heap of the thread from which it originated. To
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allocate, the local free list is used first; if it is empty, the entire
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global free list is popped onto the local free list. Since the local free
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list is only ever accessed by the thread it belongs to, it does not require
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synchronization at all, and because the global free list is popped from
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infrequently, the cost of synchronization has a reduced impact. A majority
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of allocations can occur without any synchronization at all; and
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deallocations only require synchronization when an object has left its
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parent thread (a relatively uncommon case).
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[mimalloc]: https://www.microsoft.com/en-us/research/uploads/prod/2019/06/mimalloc-tr-v1.pdf
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[freelist]: https://en.wikipedia.org/wiki/Free_list
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[Treiber stack]: https://en.wikipedia.org/wiki/Treiber_stack
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# Implementation
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A slab is represented as an array of [`MAX_THREADS`] _shards_. A shard
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consists of a vector of one or more _pages_ plus associated metadata.
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Finally, a page consists of an array of _slots_, head indices for the local
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and remote free lists.
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```text
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┌─────────────┐
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│ shard 1 │
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│ │ ┌─────────────┐ ┌────────┐
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│ pages───────┼───▶│ page 1 │ │ │
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├─────────────┤ ├─────────────┤ ┌────▶│ next──┼─┐
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│ shard 2 │ │ page 2 │ │ ├────────┤ │
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├─────────────┤ │ │ │ │XXXXXXXX│ │
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│ shard 3 │ │ local_head──┼──┘ ├────────┤ │
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└─────────────┘ │ remote_head─┼──┐ │ │◀┘
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... ├─────────────┤ │ │ next──┼─┐
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┌─────────────┐ │ page 3 │ │ ├────────┤ │
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│ shard n │ └─────────────┘ │ │XXXXXXXX│ │
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└─────────────┘ ... │ ├────────┤ │
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┌─────────────┐ │ │XXXXXXXX│ │
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│ page n │ │ ├────────┤ │
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└─────────────┘ │ │ │◀┘
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└────▶│ next──┼───▶ ...
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├────────┤
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│XXXXXXXX│
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└────────┘
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```
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The size of the first page in a shard is always a power of two, and every
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subsequent page added after the first is twice as large as the page that
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preceeds it.
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```text
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pg.
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┌───┐ ┌─┬─┐
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│ 0 │───▶ │ │
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├───┤ ├─┼─┼─┬─┐
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│ 1 │───▶ │ │ │ │
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├───┤ ├─┼─┼─┼─┼─┬─┬─┬─┐
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│ 2 │───▶ │ │ │ │ │ │ │ │
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├───┤ ├─┼─┼─┼─┼─┼─┼─┼─┼─┬─┬─┬─┬─┬─┬─┬─┐
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│ 3 │───▶ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │
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└───┘ └─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┘
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```
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When searching for a free slot, the smallest page is searched first, and if
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it is full, the search proceeds to the next page until either a free slot is
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found or all available pages have been searched. If all available pages have
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been searched and the maximum number of pages has not yet been reached, a
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new page is then allocated.
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Since every page is twice as large as the previous page, and all page sizes
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are powers of two, we can determine the page index that contains a given
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address by shifting the address down by the smallest page size and
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looking at how many twos places necessary to represent that number,
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telling us what power of two page size it fits inside of. We can
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determine the number of twos places by counting the number of leading
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zeros (unused twos places) in the number's binary representation, and
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subtracting that count from the total number of bits in a word.
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The formula for determining the page number that contains an offset is thus:
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```rust,ignore
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WIDTH - ((offset + INITIAL_PAGE_SIZE) >> INDEX_SHIFT).leading_zeros()
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```
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where `WIDTH` is the number of bits in a `usize`, and `INDEX_SHIFT` is
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```rust,ignore
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INITIAL_PAGE_SIZE.trailing_zeros() + 1;
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```
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[`MAX_THREADS`]: https://docs.rs/sharded-slab/latest/sharded_slab/trait.Config.html#associatedconstant.MAX_THREADS
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