[PATCH v3] acl: support custom memory allocator

[Stephen Hemminger]

On Tue, 25 Nov 2025 12:14:46 +0000
"mannywang(王永峰)" <mannywang at tencent.com> wrote:

> Reduce memory fragmentation caused by dynamic memory allocations
> by allowing users to provide custom memory allocator.
> 
> Add new members to struct rte_acl_config to allow passing custom
> allocator callbacks to rte_acl_build:
> 
> - running_alloc: allocator callback for run-time internal memory
> - running_free: free callback for run-time internal memory
> - running_ctx: user-defined context passed to running_alloc/free
> 
> - temp_alloc: allocator callback for temporary memory during ACL build
> - temp_reset: reset callback for temporary allocator
> - temp_ctx: user-defined context passed to temp_alloc/reset
> 
> These callbacks allow users to provide their own memory pools or
> allocators for both persistent runtime structures and temporary
> build-time data.
> 
> A typical approach is to pre-allocate a static memory region
> for rte_acl_ctx, and to provide a global temporary memory manager
> that supports multipleallocations and a single reset during ACL build.
> 
> Since tb_mem_pool handles allocation failures using siglongjmp,
> temp_alloc follows the same approach for failure handling.
> 
> Signed-off-by: YongFeng Wang <mannywang at tencent.com>
> ---

Rather than custom allocators, I did a couple of quick AI queries about
alternatives. It looks like there are some big global gains possible
here:

Summary of Recommendations
Improvement	Benefit	Complexity	Priority
ACL Object Pooling	Eliminates ACL-specific fragmentation	Medium	High
Size-Class Segregation	Reduces general fragmentation	High	High
Slab Allocator for Build	Better hugepage utilization	Medium	Medium
Deferred Coalescing	Reduces fragmentation from churn	Medium	Medium
Thread-Local Caching	Reduces contention, improves locality	Medium	Medium

Also adding some malloc_trim() would help.

https://claude.ai/share/75fcf73c-17e3-4f41-8590-f2ab640f9512