Based on topic-available-chunks, see #802.
Based on #1043

Adds strategies for guiding applications to efficient parallel chunk loading patterns.
Idea: PR #802 lets reading applications inquire the chunks that are available for loading in the backend. This PR adds a function chunk_assignment::assignChunks, taking such a ChunkTable as well as a strategy as input and produces a further ChunkTable that may be used as a load pattern.

Implemented strategies:

• Round Robin: Assign chunks to reading processes in turn.
• by hostname: Assign chunks to processes on the same host. Parameterized by the interior distribution strategy.
• by cuboid slice: Assign chunks according to a slicing into n_ranks hyperslabs of the data space.
• by binpacking: Assign chunks in an approximatively balanced manner via an approximation algorithm for the NP complete binpacking problem.

Also, add an attribute to the global Series object (currently called rankMetaInfo, I'm sure we'll change this) that can be used to write string-formatted meta information for the single writing processes and assign meaning to them (e.g. hostnames). Used by the hostname-based strategy.

TODO:

• Python bindings
• Testing, mostly done manually so far
• Cleanup
• Documentation
• This PR adds many MPI-based methods to the Series class. It would probably be good to first separate MPI and non-MPI headers, and then to add this functionality to the MPI headers.