Implementing the `EngineBufferManager` the desired way,
with the ability to post allocation requests asynchronously,
raises the difficult question of who will ultimately perform
the allocation / deallocation and further management work.
The point is that this management effort takes up capacity
originally assigned for the render workers themselves, either
by implicitly pushing aside those threads, or as a dedicated
processing assigned to some worker.
In the current stage of development it seems impossible to decide
upon the proper mechanism to schedule this excess work explicitly.
The solution proposed hereby however circumvents this dilemma,
insofar it allows to implement the synchronous, fallback processing
in terms of the asynchronous processing, just performed exclusively
within the current thread. Unless some processing will be scheduled
explicitly (which can be added as performance optimisation later on),
the handling of a direct allocation request will ''fold down'' into
the current worker eventually, thereby using it's processing capability
without the need of any explicit scheduling.
While all of this aggregate can be considered ''deep implementation'',
the structure of dependencies bears danger to get confusing. Even more so,
since an elaborate pooling memory allocator will be added to and interconnected
with this structure.
Now considering the following route:
- `engine-buffer-allocator.hpp` has elements of a common service / interface
- but `engine-buffer-allocator.cpp `is also the most deeply nested implementation backend
- `local-buffer-store.hpp` is a junction point
- `local-mem-pool.hpp` is considered an insolated implementation detail
- ultimately, this will be included and wired in `render-enviroment.cpp`
This implementation and the accompanying test might seem pointless,
yet the point is that the interface is aligned to the emerging
concepts for memory allocators in Lumiera, while also directly
delegating to the std::allocator for the time being.
Before we're able to observe the actual allocator trend and behaviour,
it is pretty much moot to engage into any kind of optimisation;
the generic heap allocator performs quite well on recent C++ runtimes,
and, furthermore, the most important performance tweak is to use
a thread-local pool of recent allocations, which should allow
our jobs to run without impeding each other.
