Romain02/03/2020, 3:15 PM
While running such a flow on a dask cluster with 1 scheduler, and 1 worker (with
map_fn = FunctionTask(lambda x: x + 1, tags=["dask-resource:GPU=1"]) with Flow('test') as flow: list =  map_fn.map(list)
), it turns out that the flow is blocked because there are 2 tasks that "reserved" the gpu resources (see attached pics from the dask dashboard). It looks like the map itself reserved 1 GPU, and then the map_fn map on element from numbers cannot be processed because dask wait for the resource to be released. Is that the expected behavior of the mapping with dask resources?
, which results in 1 extra resource being used than you might otherwise expect. This is up for a refactor very very soon, in which case you will stop seeing this behavior!