My main use case involved 2.5M words that were represented using 150K nodes. But other users might have < 32K nodes in which case they may benefit from a 2x memory footprint cut (as if we haven't done enough!) It might be worth taking this number up to 64K-1 as we only need one special value.
If we are doing this, we may also want to think of users who might have more than 2G nodes and add a ulong version. Unlikely, but future-ready. Add a long version of GetNodeCount ().
I.e. add another template parameter to YaleDawg<TPayload>, TIndex which can be byte, ushort, uint or ulong and instantiate the required specialization based on the total number of nodes.
My main use case involved 2.5M words that were represented using 150K nodes. But other users might have < 32K nodes in which case they may benefit from a 2x memory footprint cut (as if we haven't done enough!) It might be worth taking this number up to 64K-1 as we only need one special value.
If we are doing this, we may also want to think of users who might have more than 2G nodes and add a ulong version. Unlikely, but future-ready. Add a long version of GetNodeCount ().
I.e. add another template parameter to YaleDawg<TPayload>, TIndex which can be byte, ushort, uint or ulong and instantiate the required specialization based on the total number of nodes.