doc/guide/src/ProfilingAllocation.adoc

   1 ProfilingAllocation
   2 ===================
   3
   4 With MLton and `mlprof`, you can <:Profiling:profile> your program to
   5 find out how many bytes each function allocates.  To do so, compile
   6 your program with `-profile alloc`.  For example, suppose that
   7 `list-rev.sml` is the following.
   8
   9 [source,sml]
  10 ----
  11 sys::[./bin/InclGitFile.py mlton master doc/examples/profiling/list-rev.sml]
  12 ----
  13
  14 Compile and run `list-rev` as follows.
  15 ----
  16 % mlton -profile alloc list-rev.sml
  17 % ./list-rev
  18 % mlprof -show-line true list-rev mlmon.out
  19 6,030,136 bytes allocated (108,336 bytes by GC)
  20        function          cur
  21 ----------------------- -----
  22 append  list-rev.sml: 1 97.6%
  23 <gc>                     1.8%
  24 <main>                   0.4%
  25 rev  list-rev.sml: 6     0.2%
  26 ----
  27
  28 The data shows that most of the allocation is done by the `append`
  29 function defined on line 1 of `list-rev.sml`.  The table also shows
  30 how special functions like `gc` and `main` are handled: they are
  31 printed with surrounding brackets.  C functions are displayed
  32 similarly.  In this example, the allocation done by the garbage
  33 collector is due to stack growth, which is usually the case.
  34
  35 The run-time performance impact of allocation profiling is noticeable,
  36 because it inserts additional C calls for object allocation.
  37
  38 Compile with `-profile alloc -profile-branch true` to find out how
  39 much allocation is done in each branch of a function; see
  40 <:ProfilingCounts:> for more details on `-profile-branch`.