Now all the fine-tuning is happening using parallel range settings structure,
which avoid passing long lists of arguments, allows extend fine-tuning further,
avoid having lots of various functions which basically does the same thing.
Based on usages so far:
- Split callback worker func in two, 'basic' and 'extended' versions. The former goes back
to the simplest verion, while the later keeps the 'userdata_chunk', and gets the thread_id too.
- Add use_threading to simple BLI_task_parallel_range(), turns out we need this pretty much systematically,
and allows to get rid of most usages of BLI_task_parallel_range_ex().
- Now BLI_task_parallel_range() expects 'basic' version of callback, while BLI_task_parallel_range_ex()
expectes 'extended' version of the callback.
All in all, this should make common usage of BLI_task_parallel_range simpler (less verbose), and add
access to advanced callback to thread id, which is mandatory in some (future) cases.
This time, with have over 300% speedup!
But no, this is not due to switch to BLI_task (which 'only' gives usal 15% speedup),
but to enhancement of the algorithm, flatten loop over covariance matrix items now allows
to compute (usually) all items in parallel, instead of having at most 3 or 4 working threads
(with unbalanced load even)...
