This is a fork of the O(1) heap library that has been modified for use in librecomp. It has been changed to use 32-bit offsets instead of pointers for the allocation metadata, which reduces their overhead and allows the heap to be dumped and reloaded at the cost of only being able to set up a 4GB region.
The original README is as follows:
O1heap is a highly deterministic constant-complexity memory allocator designed for hard real-time high-integrity embedded systems. The name stands for O(1) heap.
The allocator offers a constant worst-case execution time (WCET) and a well-characterized worst-case memory fragmentation (consumption) (WCMC). The allocator allows the designer to statically prove its temporal and spatial properties for a given application, which makes it suitable for use in high-integrity embedded systems.
The codebase is implemented in C99/C11 following MISRA C:2012, with several intended deviations which are unavoidable due to the fact that a memory allocator has to rely on inherently unsafe operations to fulfill its purpose. The codebase is extremely compact (<500 LoC) and is therefore trivial to validate.
The allocator is designed to be portable across all conventional architectures, from 8-bit to 64-bit systems.
The core objective of this library is to provide a dynamic memory allocator that meets the following requirements:
-
Memory allocation and deallocation routines are constant-time.
-
For a given peak memory requirement
$M$ , the worst-case memory consumption$H$ is predictable (i.e., the worst-case heap fragmentation is well-characterized). The application designer shall be able to easily predict the amount of memory that needs to be provided to the memory allocator to ensure that out-of-memory (OOM) failures provably cannot occur at runtime under any circumstances. -
The implementation shall be simple and conform to relevant high-integrity coding guidelines.
This implementation derives from or is based on the ideas presented in:
- "Timing-Predictable Memory Allocation In Hard Real-Time Systems" -- J. Herter, 2014.
- "An algorithm with constant execution time for dynamic storage allocation" -- T. Ogasawara, 1995.
- "Worst case fragmentation of first fit and best fit storage allocation strategies" -- J. M. Robson, 1975.
This implementation does not make any non-trivial assumptions about the behavioral properties of the application. Per Herter [2014], it can be described as a predictably bad allocator:
An allocator that provably performs close to its worst-case memory behavior which, in turn, is better than the worst-case behavior of the allocators discussed [in Herter 2014], but much worse than the memory consumption of these for normal programs without (mostly theoretical) bad (de-)allocation sequences.
While it has been shown to be possible to construct a constant-complexity allocator which demonstrates better worst-case and average-case memory requirements by making assumptions about the memory (de-)allocation patterns and/or by relying on more sophisticated algorithms, this implementation chooses a conservative approach where no assumptions are made about the application and the codebase is kept simple to facilitate its integration into verified and validated high-integrity software.
The library implements a modified half-fit algorithm -- a constant-complexity strategy originally proposed by Ogasawara.
In this implementation, memory is allocated in fragments whose size is rounded up to the next integer power of two.
The worst-case memory consumption (WCMC)
Where
Memory allocators used in general-purpose (non-real-time and/or non-high-integrity) applications often leverage a different class of algorithms which may feature poorer worst-case performance metrics but perform (much) better on average. For a hard real-time system, the average case performance is generally less relevant, so it can be excluded from analysis.
The two-level segregated fit (TLSF) algorithm is a more complex
| Allocation strategy | WCMC |
|---|---|
| First-fit | |
| Half-fit | |
| Best-fit | |
| TLSF | (see best-fit) |
The state of catastrophic fragmentation is a state where the allocator is unable to serve
a memory allocation request even if there is enough free memory due to its suboptimal arrangement.
By definition, if the amount of memory available to the allocator is not less than
The above-defined theoretical worst-case upper bound H may be prohibitively high for some
memory-constrained applications.
It has been shown [Robson 1975] that under a typical workload,
for a sufficiently high amount of memory available to the allocator which is less than
Following some of the ideas from [Herter 2014], this implementation takes caching-related issues into consideration by choosing the most recently used memory fragments to minimize cache misses in the application.
The implemented variant of half-fit allocates memory in fragments of size:
Where O1HEAP_ALIGNMENT,
because it also dictates the allocated memory pointer alignment.
Due to the overhead, the maximum amount of memory available to the application per allocation is
From the above follows that malloc(..),
the allocator returns a null pointer if a zero-sized allocation is requested.
It has been mentioned that the abstract definition of
Where
The above equation should be used for sizing the heap space.
Observe that the case of
The following illustration shows the worst-case memory consumption (WCMC) for some common memory sizes;
as explained above, O1HEAP_ALIGNMENT which is platform-dependent:
Copy the files o1heap.c and o1heap.h (find them under o1heap/) into your project tree.
Either keep them in the same directory, or make sure that the directory that contains the header
is added to the set of include look-up paths.
No special compiler options are needed to compile the source file (if you find this to be untrue, please open a ticket).
Dedicate a memory arena for the heap, and pass a pointer to it along with its size to the initialization function
o1heapInit(..).
Allocate and deallocate memory using o1heapAllocate(..) and o1heapFree(..).
Their semantics are compatible with malloc(..) and free(..) plus additional behavioral guarantees
(constant timing, bounded fragmentation).
If necessary, periodically invoke o1heapDoInvariantsHold(..) to ensure that the heap is functioning correctly
and its internal data structures are not damaged.
Avoid concurrent access to the heap. Use locking if necessary.
The preprocessor options given below can be overridden to fine-tune the implementation. None of them are mandatory to use.
Define this optional macro like O1HEAP_CONFIG_HEADER="path/to/my_o1heap_config.h" to pass build configuration macros.
This is useful because some build systems do not allow passing function-like macros via command line flags.
The macro O1HEAP_ASSERT(x) can be defined to customize the assertion handling or to disable it.
To disable assertion checks, the macro should expand to (void)(x).
If not specified, the macro expands to the standard assertion check macro assert(x) as defined in <assert.h>.
Some of the conditional branching statements are equipped with this annotation to hint the compiler that the generated code should be optimized for the case where the corresponding branch is taken. This is done to reduce the worst-case execution time.
The macro should expand to a compiler-specific branch weighting intrinsic,
or to the original expression (x) if no such hinting is desired.
If not specified, the macro expands as follows:
- For some well-known compilers the macro automatically expands to appropriate branch weighting intrinsics.
For example, for GCC, Clang, and ARM Compiler, it expands to
__builtin_expect((x), 1). - For other (unknown) compilers it expands to the original expression with no modifications:
(x).
The count leading zeros (CLZ) function is used for fast binary logarithm computation (which has to be done multiple times per allocation, so its performance is critical). Most of the modern processors implement dedicated hardware support for fast CLZ computation, which is available via compiler intrinsics.
If not overridden by the user, for some compilers O1HEAP_CLZ(x) will expand to the appropriate intrinsic
(e.g., __builtin_clzl(x) for GCC/Clang).
For other compilers it will default to a slow software implementation,
which is likely to significantly degrade the performance of the library.
The following tools should be available locally to conduct library development:
- Modern versions of CMake, GCC, Clang, and Clang-Tools.
- An AMD64 machine.
- (optional) Valgrind.
The codebase shall follow the Zubax C/C++ Coding Conventions. Compliance is enforced through the following means:
- Clang-Tidy -- invoked automatically while building the test suite.
- Clang-Format -- invoked manually as
make format; enforced in CI/CD automatically. - SonarCloud -- invoked by CI/CD automatically.
Please refer to the continuous integration configuration to see how to invoke the tests.
Update the version number macro in the header file and create a new git tag like 1.0.
MISRA compliance is enforced with the help of the following tools:
- Clang-Tidy -- invoked automatically during the normal build process.
- SonarCloud -- invoked as part of the continuous integration build.
Every intentional deviation shall be documented and justified in-place using the following notation, followed by the appropriate static analyser warning suppression statement:
// Intentional violation of MISRA: <valid reason here>
// NOSONAR
// NOLINTThe list of intentional deviations can be obtained by simply searching the codebase for the above comments.
Do not suppress compliance warnings using the means provided by static analysis tools because such deviations are impossible to track at the source code level. An exception applies for the case of false-positive (invalid) warnings -- those should not be mentioned in the codebase.
- Timing-Predictable Memory Allocation In Hard Real-Time Systems, J. Herter, 2014.
- Worst case fragmentation of first fit and best fit storage allocation strategies, J. M. Robson, 1975.
- Dynamic Memory Allocation In SQLite -- on Robson proof and deterministic fragmentation.
- [Russian] Динамическая память в системах жёсткого реального времени -- issues with dynamic memory allocation in modern embedded RTOS and related popular misconceptions.
- Significantly accelerate (de-)allocation by replacing the naïve log2 implementation with fast CLZ intrinsics;
see
O1HEAP_CLZ(x). - Do not require char to be 8-bit wide: replace
uint8_twithuint_fast8_t. This is to enhance compatibility with odd embedded platforms whereCHAR_BIT!=8(e.g., ADSP TS-201, TMS320C2804).
- Remove critical section hooks to enhance MISRA conformance #4
- Add support for config header via
O1HEAP_CONFIG_HEADER#5
The first release.
The library is available under the terms of the MIT License.
Please find it in the file LICENSE.