For 10 Million cell problems my compute server (with 128 GB Ram)
starts to swap, when I use debugging tools in parallel runs. I assume
that this might get an issue for others, too.
Now we consistently use unordered_map for the mapping.
- the diffusion one is basically done on runtime anyways
- the energy one gives some small code elimination gains
however, it complicates the writing of downstream templates.
- The edit manipulations from EDITNNC have already been applied to the NNC data
from opm-common
- The NNC data structures are guaranteed to be ordered, both with cell1 <= cell2
and the NNCs are in ascending order
- The NNC output to EGRID / INIT files is based on std::vector<NNCdata>
For PINCH(5)==ALL, we take the minimum of MULTZ+ and ignore MULTZ-.
We also prepare for PINCH(5)==TOP taking only the toplevel MULTZ+
value.
For non-vertical directions we use both MULTZ+ and MULTZ-
This will process the same faces in serial and parallel.
Hence it make the silent assumption that we only process faces
from low cartesian index to high cartesian index hold again.
This should fix PINCH MULTZ ALL in parallel.
Up to now We always assumed that cardDims[i]>1 holds. which it does for most
of the cases. But when e.g. simulating a vertical stack of 5 cells
flow would report the transmissibilities in the Z direction in TRANX
and output TRANZ as zero. Similar problems should be there for 2D grids.
With this commit we actually check whether there can be neighbours in
the X and Z direction to prevent this behavior.
`NEW_PROP_TAG` is now a definition and not just a declaration.
Eliminate superfluous declarations, include headers with definitions.
Make one necessary forward declaration explicit.
this was actually broken by an upstream change from return-by-reference
to return-by-value, but we were lucky, the return value was
kept in memory until end of block it seems.
They are attached to the cells as well and are now distributed
during CpGrid::loadBalance. Due to this change we also rename
FieldPropsDataHandle to PropsCentroidsDataHandle.
It seems like eclipse ignores NNCs with small transmissibility.
Small means less than 1e-6 for Eclipse (Even if it says that it
is ignoring values below 1e-5 and/or zero values)!.
This commit now implements the same threshold during IO.
Also fixes a bug when applying EDITNNC, it needs to have cell1<=cell2 to work.
Unfortunately, we first created NNC with applied EDITNNC and then
still used the original NNC data to set the transmissibility. Thus
we were actually ignoring EDITNNC.
This commit fixes this by using the data structure that has EDITNNC
applied.
