Add a benchmark/example for numexpr usage under free-threading conditions

[andfoy]

Fixes #503

[andfoy]

@FrancescAlted, it seems that this lock is a performance bottleneck when multiple threads are ran in parallel, is it necessary?

[andfoy]

With the lock:

Benchmarking Expression 1:
NumPy time (threaded over 32 chunks with 16 threads): 3.276298 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 9.975059 seconds
numexpr speedup: 0.33x
----------------------------------------
Benchmarking Expression 2:
NumPy time (threaded over 32 chunks with 16 threads): 18.981946 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 50.327974 seconds
numexpr speedup: 0.38x
----------------------------------------
Benchmarking Expression 3:
NumPy time (threaded over 32 chunks with 16 threads): 20.414158 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 70.900648 seconds
numexpr speedup: 0.29x
----------------------------------------
Benchmarking Expression 4:
NumPy time (threaded over 32 chunks with 16 threads): 38.012808 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 160.476216 seconds
numexpr speedup: 0.24x
----------------------------------------

[andfoy]

Without locking:

Benchmarking Expression 1:
NumPy time (threaded over 32 chunks with 16 threads): 3.415349 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 2.618876 seconds
numexpr speedup: 1.30x
----------------------------------------
Benchmarking Expression 2:
NumPy time (threaded over 32 chunks with 16 threads): 19.005238 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 12.611407 seconds
numexpr speedup: 1.51x
----------------------------------------
Benchmarking Expression 3:
NumPy time (threaded over 32 chunks with 16 threads): 20.555149 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 17.690749 seconds
numexpr speedup: 1.16x
----------------------------------------
Benchmarking Expression 4:
NumPy time (threaded over 32 chunks with 16 threads): 38.338372 seconds
numexpr time (threaded with re_evaluate over 32 chunks with 16 threads): 35.074684 seconds
numexpr speedup: 1.09x
----------------------------------------