Simple Chunk Allocator
A simple no_std
allocator written in Rust that manages memory in fixed-size chunks/blocks. Useful for basic no_std
binaries where you want to manage a heap of a few megabytes without complex features such as paging/page table management. Instead, this allocator gets a fixed/static memory region and allocates memory from there. This memory region can be contained inside the executable file that uses this allocator. See examples down below.
no_std
binaries and hopefully also for educational purposes. It helped me to understand a lot about allocators.
TL;DR
-
✅ no_std
allocator with test coverage -
✅ uses static memory as backing storage (no paging/page table manipulations) -
✅ allocation strategy is a combination of next-fit and best-fit -
✅ reasonable fast with low code complexity -
✅ const compatibility (no runtimeinit()
required) -
✅ efficient in scenarios where heap is a few dozens megabytes in size -
✅ user-friendly API
The inner and low-level ChunkAllocator
can be used as #[global_allocator]
with the synchronized wrapper type GlobalChunkAllocator
. Both can be used with the allocator_api
feature. The latter enables the usage in several types of the Rust standard library, such as Vec::new_in
or BTreeMap::new_in
. This is primarily interesting for testing but may also enable other interesting use-cases.
The focus is on const
compatibility. The allocator and the backing memory can get initialized during compile time and need no runtime init()
call or similar. This means that if the compiler accepts it then the allocation will also work during runtime. However, you can also create allocator objects during runtime.
The inner and low-level ChunkAllocator
is a chunk allocator or also called fixed-size block allocator. It uses a mixture of the strategies next-fit and a best-fit. It tries to use the smallest gap for an allocation request to prevent fragmentation but this is no guarantee. Each allocation is a trade-off between a low allocation time and preventing fragmentation. The default chunk size is 256 bytes
but this can be changed as compile time const generic. Having a fixed-size block allocator enables an easy bookkeeping algorithm through a bitmap but has as consequence that small allocations, such as 64 byte
will take at least one chunk/block of the chosen block size.
This project originates from my Diplom thesis project. Since I originally had lots of struggles to create this (my first ever allocator), I outsourced it for better testability and to share my knowledge and findings with others in the hope that someone can learn from it in any way.
Minimal Code Example
#![feature(const_mut_refs)]
#![feature(allocator_api)]
use simple_chunk_allocator::{heap, heap_bitmap, GlobalChunkAllocator, PageAligned};
// The macros help to get a correctly sized arrays types.
// I page-align them for better caching and to improve the availability of
// page-aligned addresses.
/// Backing storage for heap (1Mib). (read+write) static memory in final executable.
///
/// heap!: first argument is chunk amount, second argument is size of each chunk.
/// If no arguments are provided it falls back to defaults.
/// Example: `heap!(chunks=16, chunksize=256)`.
static mut HEAP: PageAligned<[u8; 1048576]> = heap!();
/// Backing storage for heap bookkeeping bitmap. (read+write) static memory in final executable.
///
/// heap_bitmap!: first argument is amount of chunks.
/// If no argument is provided it falls back to a default.
/// Example: `heap_bitmap!(chunks=16)`.
static mut HEAP_BITMAP: PageAligned<[u8; 512]> = heap_bitmap!();
// please make sure that the backing memory is at least CHUNK_SIZE aligned; better page-aligned
#[global_allocator]
static ALLOCATOR: GlobalChunkAllocator =
unsafe { GlobalChunkAllocator::new(HEAP.deref_mut_const(), HEAP_BITMAP.deref_mut_const()) };
fn main() {
// at this point, the allocator already got used a bit by the Rust runtime that executes
// before main() gets called. This is not the case if a `no_std` binary gets produced.
let old_usage = ALLOCATOR.usage();
let mut vec = Vec::new();
vec.push(1);
vec.push(2);
vec.push(3);
assert!(ALLOCATOR.usage() > old_usage);
// use "allocator_api"-feature. You can use this if "ALLOCATOR" is not registered as
// the global allocator. Otherwise, it is already the default.
let _boxed = Box::new_in([1, 2, 3], ALLOCATOR.allocator_api_glue());
}
Another Code Example (Free Standing Linux Binary)
This is an excerpt. The code can be found in the GitHub repository in freestanding-linux-example
.
static mut HEAP: PageAligned<[u8; 256]> = heap!(chunks = 16, chunksize = 16);
static mut HEAP_BITMAP: PageAligned<[u8; 2]> = heap_bitmap!(chunks = 16);
// please make sure that the backing memory is at least CHUNK_SIZE aligned; better page-aligned
#[global_allocator]
static ALLOCATOR: GlobalChunkAllocator<16> =
unsafe { GlobalChunkAllocator::<16>::new(HEAP.deref_mut_const(), HEAP_BITMAP.deref_mut_const()) };
/// Referenced as entry by linker argument. Entry into the code.
#[no_mangle]
fn start() -> ! {
write!(StdoutWriter, "Hello :)\n").unwrap();
let mut vec = Vec::new();
(0..10).for_each(|x| vec.push(x));
write!(StdoutWriter, "vec: {:#?}\n", vec).unwrap();
exit();
}
MSRV
This crate only builds with the nightly version of Rust because it uses many nightly-only features. I developed it with version 1.61.0-nightly
(2022-03-05). Older nightly versions might work. So far there is no stable Rust compiler version that compiles this.
Performance
The default CHUNK_SIZE is 256 bytes. It is a tradeoff between performance and efficient memory usage.
I executed my example bench
in release mode on an Intel i7-1165G7 CPU and a heap of 160MB
to get the results listed below. I used RUSTFLAGS="-C target-cpu=native" cargo run --release --example bench
to excute the benchmark with maximum performance. The benchmark simulates a heavy usage of the heap in a single-threaded program with many random allocations and deallocations. The benchmark stops when the heap is at 100%. The allocations vary in their alignment. The table below shows the results of this benchmark as number of clock cycles.
Chunk Size | # Chunks | # allocations | # deallocations | median | average | min | max |
---|---|---|---|---|---|---|---|
128 | 1310720 | 68148 | 47915 | 955 | 1001 | 126 | 57989 |
256 [DEFAULT] | 655360 | 71842 | 51744 | 592 | 619 | 121 | 53578 |
512 | 327680 | 66672 | 46858 | 373 | 401 | 111 | 54403 |
The results vary slightly because each run gets influenced by some randomness. One can see that the performance gets slower with a growing number of chunks. Increasing the chunk size reduces the size of the bookkeeping bitmap which accelerates the lookup. However, a smaller chunk size occupies less heap when only very small allocations are required.
Note that performance is better than listed above when the heap is used less frequently and does not run full.