Thanks for additional information. Seems that the take home message is
that I should look at other ways to set up the calculations. I just
picked up an old cfile, used that as a starting point and did not even
consider alternatives to use ReadHITRAN.
On 2021-09-20 09:05, Richard Larsson wrote:
We can of course optimize the reading routine but there's no point in
doing that. The methods that read external catalogs should only ever be
used once per update of the external catalog, so it's fine if they are
slow but not too slow.
New memory is allocated for every absorption line always. This is
because we keep line data local, and the model for the line shape and
the local quantum numbers don't have to be known at compile-time.
Additionally, the line data is pushed into arrays, so they will double
in size every time you reach the current size.
If we knew the number of lines and broadening species and local quantum
numbers, then these allocations happen once for the entire band, but we
don't in ReadHITRAN or any of the external reading routines. So you
will have many-many system calls asking for more memory. This of course
also means that you are over-allocating memory since that's how Arrays
work in ARTS (because that's standard C++). Again, this is also fine
since the external catalog when read again will allocate only exactly
what is required.
Den mån 20 sep. 2021 kl 08:09 skrev Patrick Eriksson
Thanks for the clarification.
Is the allocation of more memory done in fixed chunks? Or something
"smart" in the process? If the former and the chunks are too small,
maybe I am doing a lot of reallocations. My impression was that memory
usage increased quite monotonically, not in noticeable steps.
If the lines have to be sorted into bands, then the complexity of the
reading will increase in line with what I have noticed. And likely not
much to do about it.
> There are two possible slowdowns there could be still. One is
> hit some line count where you need to reallocate the array of lines
> because you have too many. The other is that the search for
> line in the correct band is slow when there are more bands to
> The former would be just pure bad luck, so there's nothing to do
> I would suspect the latter is your problem. You need to search
> the existing bands for every new line to find where it belongs.
> bands are often clustered closely together in frequency, this
> down the reading as you get more and more bands. A smaller frequency
> range means fewer bands to look through.
> On Sun, Sep 19, 2021, 22:39 Patrick Eriksson
> > It's expected to take a somewhat arbitrary time. It reads
> I have tried multiple times and the pattern is not changing.
> > The start-up time is going to be large because of having
to find the
> > first frequency, which means you have to parse the text
> Understood. But that overhead seems to be relatively small.
In my test,
> it seemed to take 4-7 s to reach the first frequency. Anyhow,
> in the other direction. To minimise the parsing to reach the
> frequency, it should be better to read all in one go, and not
> (which is the case for me).