  A parallel, blocked, one-sided Hari--Zimmermann algorithm for the generalized
singular value decomposition (GSVD) of a real or a complex matrix pair $(F,G)$
is here proposed, where $F$ and $G$ have the same number of columns, and are
both of the full column rank. The algorithm targets either a single graphics
processing unit (GPU), or a cluster of those, performs all non-trivial
computation exclusively on the GPUs, requires the minimal amount of memory to
be reasonably expected, scales acceptably with the increase of the number of
GPUs available, and guarantees the reproducible, bitwise identical output of
the runs repeated over the same input and with the same number of GPUs.
