Wrap use of CUDA mutex in where reductions

[ianthomas23]

This PR implements the use of CUDA mutexes in a where reduction by wrapping the use of where and its selector in the same mutex lock region. Previously the two were separate, which can lead to some hard to track down variations in results as multiple CUDA threads could potentially try to alter the same data at the same time. The wrapping occurs in the compiler.py make_append function, which is where the existing special handling of where reductions takes place.

Whilst doing this I have chosen to move all use of a CUDA mutex from reductions.py to compiler.py so that it is all in one place. This benefits us in that it reduces the future proliferation of reduction._append_cuda functions which might have otherwise needed versions both with and without mutex locking.

I have also rewritten the handling of return values from reduction._append_cuda functions to explicitly check if the function call has changed the data stored in the agg or not, as this wasn't always correct before when handling NaNs.

This work is a necessary precursor to completing the CUDA support for where(max_n) and similar (issues #1182 and #1207) which will follow shortly.

[codecov]

Codecov Report

Merging #1217 (c6ad0e4) into main (8092f4d) will increase coverage by 0.09%.
The diff coverage is 84.72%.

@@            Coverage Diff             @@
##             main    #1217      +/-   ##
==========================================
+ Coverage   84.52%   84.62%   +0.09%     
==========================================
  Files          35       35              
  Lines        8369     8591     +222     
==========================================
+ Hits         7074     7270     +196     
- Misses       1295     1321      +26     

Impacted Files	Coverage Δ
datashader/data_libraries/pandas.py	100.00% <ø> (ø)
datashader/reductions.py	83.58% <81.49%> (+0.47%)	⬆️
datashader/compiler.py	87.91% <83.33%> (-2.66%)	⬇️
datashader/data_libraries/dask.py	95.23% <100.00%> (+0.07%)	⬆️
datashader/data_libraries/dask_xarray.py	98.95% <100.00%> (ø)
datashader/utils.py	81.86% <100.00%> (+2.61%)	⬆️

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