python: bind PixelHistogramCUDA

PixelHistogramCUDA_<input>_<storage> for uint16, float32 and float64
frames and the six storage types of PixelHistogram, behind an
aare.PixelHistogramCUDA() factory. Frames are never converted: a wrong
dtype raises TypeError, so a registered buffer is always the one copied.
The GIL is released during GPU work.

- C++: fill_histogram() and submit_batch() take const views, so
  read-only arrays (np.memmap mode="r") work; register_output_buffer()
  pins the destination of values(out).
- Python: register_input_buffer()/register_output_buffer() keep their
  array alive; values(out=...) writes into a given array. With a pinned
  out, reading back a 640 MB histogram takes 28 ms instead of 230 ms.
- Tests in test_PixelHistogramCUDA.py; PixelHistogramCUDA.ipynb compares
  CPU and GPU on 100k Moench frames (identical, ~13x faster on the GPU).

python/CMakeLists.txt

@@ -76,6 +76,7 @@ set(PYTHON_FILES
     aare/Cluster.py
     aare/FastPedestal.py
     aare/Pedestal.py
+    aare/PixelHistogramCUDA.py
     aare/calibration.py
     aare/factory.py
     aare/experimental.py