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?
Chris White02/03/2020, 4:22 PM
, 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!