See if we can speedup postclassical in case of tiling

[micheles]

It is quite slow for the USA model, see calculation #108 on the spot machine:

| calc_108, maxmem=345.0 GB  | time_sec  | memory_mb | counts      |
| total postclassical        | 434_923   | 1_318     | 192         |
| read PoEs                  | 426_713   | 1_318     | 192         |

Received 192 * 1.77 MB {'hcurves-stats': '313.55 MB', 'hmaps-stats': '25.96 MB'} in 4120 seconds from postclassical

[#108 USA INFO] Stored 212.86 GB of rates
[#108 USA INFO] Producing 192 postclassical tasks
[#108 USA INFO] There are 414_311 slices of poes [2157.9 per task]

All process are waiting (in "D" state) while reading the data. A strategy could be to store a tile column and a dataset slice_by_tile rather than slice_by_sid.

[micheles]

Solved by gzipping the datasets.