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From: "tromey at sourceware dot org" <sourceware-bugzilla@sourceware.org>
To: gdb-prs@sourceware.org
Subject: [Bug symtab/29105] New: new DWARF reader still slow
Date: Fri, 29 Apr 2022 19:51:00 +0000
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https://sourceware.org/bugzilla/show_bug.cgi?id=3D29105

            Bug ID: 29105
           Summary: new DWARF reader still slow
           Product: gdb
           Version: HEAD
            Status: NEW
          Severity: normal
          Priority: P2
         Component: symtab
          Assignee: unassigned at sourceware dot org
          Reporter: tromey at sourceware dot org
  Target Milestone: ---

Pedro pointed out that using the index cache is still faster than
the new DWARF reader.  I think I found why:

What happens here is that gdb does the finalization step in the
background.  Interactively, this helps make it seem faster.  However,
it's not really faster, it is just deferring some work.

You can see it with an invocation like:

   gdb -q -batch -iex 'set debug timestamp 1' -iex 'set debug dwarf-read 1'=
 -ex
start ./gdb

Here for gdb-with-an-index I see:

    0.820423 [dwarf-read] dwarf2_initialize_objfile: found gdb index from f=
ile
    1.699175 [dwarf-read] process_queue: Expanding one or more symtabs of
objfile /tmp/gdb.idx ...

But for ordinary gdb:

    1.310033 [dwarf-read] dwarf2_build_psymtabs_hard: Done building psymtab=
s of
/tmp/gdb
    4.666649 [dwarf-read] process_queue: Expanding one or more symtabs of
objfile /tmp/gdb ...

This is disappointing of course.  It might be possible to reduce this
time at the cost of a bit more complexity in the lookup code and perhaps
a bit more memory use.  For example, right now finalization merges the
results from all the readers into a single entry table -- but maybe the
table could remain sharded instead.  Another possibility might be to do
the work in worker threads and, instead of sharding the result, pre-sort
the vectors and use a sorted merge operation to combine them.


See the last messages in this thread:

https://sourceware.org/pipermail/gdb-patches/2022-April/188194.html

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