text: Title: parallel batching for `find()`
  Body: In `docarray/utils/find.py` we have a helper function `find_batched()` that performs exact kNN search on multiple input queries.
  The current implementation treats all queries as one big batch; It calculates all distances for all queries in one go.
  
  In some scenarios this is not idea: If CPU is used to perform the vector similarity computation (instead of GPU), and the number of input queries is large, it would be nice to be able to split the workload across multiple threads and/or processes.
  
  Possibly an implementation of this could leverage our `map_doc()` or `map_docs_batch()` functions to achieve this.