Current default value for rows_per_chunk parameter of the CSV writer is 8, which means that the input table is by default broken into many small slices that are written out sequentially. This reduces the performance by an order on magnitude in some cases.

In Python layer, the default is the number of rows (i.e. write table out in a single pass). We can follow this by setting rows_per_chunk

The version of device_copy_n which takes a CUDA stream argument
https://github.com/clara-parabricks/GenomeWorks/blob/74e6424c156a7ee15b4137d4788a4257ee6482c4/common/base/include/claraparabricks/genomeworks/utils/cudautils.hpp#L138
should be renamed to device_copy_n_async to make the non-blocking behavior more obvious.

The blocking three-argument version of device_copy_n should remain

When running the regression, the resulting logs seem to end up in third_party/tests/$TEST/.... This of course is not unnoticed by git, so a git status shows a ton of non-added new files added.

To reproduce:

make
make regression
git status   # observe all the files

Build or test artifacts should never clutter the rest of the code-base (we should regard them as read-only in

Flags should be renamed to be positive statements rather than negative ones, if possible.