Add large page support for NNUE weights and simplify TT mem management

Use TT memory functions to allocate memory for the NNUE weights. This
should provide a small speed-up on systems where large pages are not
automatically used, including Windows and some Linux distributions.

Further, since we now have a wrapper for std::aligned_alloc(), we can
simplify the TT memory management a bit:

- We no longer need to store separate pointers to the hash table and
  its underlying memory allocation.
- We also get to merge the Linux-specific and default implementations
  of aligned_ttmem_alloc().

Finally, we'll enable the VirtualAlloc code path with large page
support also for Win32.

STC: https://tests.stockfishchess.org/tests/view/5f66595823a84a47b9036fba
LLR: 2.94 (-2.94,2.94) {-0.25,1.25}
Total: 14896 W: 1854 L: 1686 D: 11356
Ptnml(0-2): 65, 1224, 4742, 1312, 105

closes https://github.com/official-stockfish/Stockfish/pull/3081

No functional change.

README.md

@@ -152,7 +152,7 @@ to find the best move. The classical evaluation computes this value as a functio
 of various chess concepts, handcrafted by experts, tested and tuned using fishtest.
 The NNUE evaluation computes this value with a neural network based on basic
 inputs (e.g. piece positions only). The network is optimized and trained
-on the evalutions of millions of positions at moderate search depth.
+on the evaluations of millions of positions at moderate search depth.
 
 The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward.
 It can be evaluated efficiently on CPUs, and exploits the fact that only parts