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mprof-report(1)        DragonFly General Commands Manual       mprof-report(1)

The Mono log profiler
       The Mono log profiler can be used to collect a lot of information about
       a program running in the Mono runtime.  This data can be used (both
       while the process is running and later) to do analyses of the program
       behaviour, determine resource usage, performance issues or even look
       for particular execution patterns.

       This is accomplished by logging the events provided by the Mono runtime
       through the profiling interface and periodically writing them to a file
       which can be later inspected with the command line mprof-report program
       or with a GUI (not developed yet).

       The events collected include (among others):

       o method enter and leave

       o object allocation

       o garbage collection

       o JIT compilation

       o metadata loading

       o lock contention

       o exceptions

       In addition, the profiler can periodically collect info about all the
       objects present in the heap at the end of a garbage collection (this is
       called heap shot and currently implemented only for the sgen garbage
       collector).  Another available profiler mode is the sampling or
       statistical mode: periodically the program is sampled and the
       information about what the program was busy with is saved.  This allows
       to get information about the program behaviour without degrading its
       performance too much (usually less than 10%).

   Basic profiler usage
       The simpler way to use the profiler is the following:

       mono --profile=log program.exe

       At the end of the execution the file output.mlpd will be found in the
       current directory.  A summary report of the data can be printed by

       mprof-report output.mlpd

       With this invocation a huge amount of data is collected about the
       program execution and collecting and saving this data can significantly
       slow down program execution.  If saving the profiling data is not
       needed, a report can be generated directly with:

       mono --profile=log:report program.exe

       If the information about allocations is not of interest, it can be

       mono --profile=log:noalloc program.exe

       On the other hand, if method call timing is not important, while
       allocations are, the needed info can be gathered with:

       mono --profile=log:nocalls program.exe

       You will still be able to inspect information about the sequence of
       calls that lead to each allocation because at each object allocation a
       stack trace is collected if full enter/leave information is not

       To periodically collect heap shots (and exclude method and allocation
       events) use the following options (making sure you run with the sgen
       garbage collector):

       mono --gc=sgen --profile=log:heapshot program.exe

       To perform a sampling profiler run, use the sample option:

       mono --profile=log:sample program.exe

   Profiler option documentation
       By default the log profiler will gather all the events provided by the
       Mono runtime and write them to a file named output.mlpd.  When no
       option is specified, it is equivalent to using:


       The following options can be used to modify this default behaviour.
       Each option is separated from the next by a , character, with no spaces
       and all the options are included after the log: profile module

       o help: display concise help info about each available option

       o [no]alloc: noalloc disables collecting object allocation info, alloc
         enables it if it was disabled by another option like heapshot.

       o [no]calls: nocalls disables collecting method enter and leave events.
         When this option is used at each object allocation and at some other
         events (like lock contentions and exception throws) a stack trace is
         collected by default.  See the maxframes option to control this
         behaviour.  calls enables method enter/leave events if they were
         disabled by another option like heapshot.

       o heapshot[=MODE]: collect heap shot data at each major collection.
         The frequency of the heap shots can be changed with the MODE
         parameter.  When this option is used allocation events and method
         enter/leave events are not recorded by default: if they are needed,
         they need to be enabled explicitly.  The optional parameter MODE can
         modify the default heap shot frequency.  heapshot can be used
         multiple times with different modes: in that case a heap shot is
         taken if either of the conditions are met.  MODE can be one of:

         o NUMms: perform a heap shot if at least NUM milliseconds passed
           since the last one.

         o NUMgc: perform a heap shot every NUM major garbage collections

         o ondemand: perform a heap shot when such a command is sent to the
           control port

       o sample[=TYPE[/FREQ]]: collect statistical samples of the program
         behaviour.  The default is to collect a 1000 times per second the
         instruction pointer.  This is equivalent to the value "cycles/1000"
         for TYPE.  On some systems, like with recent Linux kernels, it is
         possible to cause the sampling to happen for other events provided by
         the performance counters of the cpu.  In this case, TYPE can be one

         o cycles: processor cycles

         o instr: executed instructions

         o cacherefs: cache references

         o cachemiss: cache misses

         o branches: executed branches

         o branchmiss: mispredicted branches

       o time=TIMER: use the TIMER timestamp mode.  TIMER can have the
         following values:

         o fast: a usually faster but possibly more inaccurate timer

       o maxframes=NUM: when a stack trace needs to be performed, collect NUM
         frames at the most.  The default is 8.

       o calldepth=NUM: ignore method enter/leave events when the call chain
         depth is bigger than NUM.

       o zip: automatically compress the output data in gzip format.

       o output=OUTSPEC: instead of writing the profiling data to the
         output.mlpd file, substitute %p in OUTSPEC with the current process
         id and %t with the current date and time, then do according to

         o if OUTSPEC begins with a | character, execute the rest as a program
           and feed the data to its standard input

         o if OUTSPEC begins with a - character, use the rest of OUTSPEC as
           the filename, but force overwrite any existing file by that name

         o otherwise write the data the the named file: note that is a file by
           that name already exists, a warning is issued and profiling is

       o report: the profiling data is sent to mprof-report, which will print
         a summary report.  This is equivalent to the option: output=mprof-
         report -.  If the output option is specified as well, the report will
         be written to the output file instead of the console.

       o port=PORT: specify the tcp/ip port to use for the listening command
         server.  Currently not available for windows.  This server is started
         for example when heapshot=ondemand is used: it will read commands
         line by line.  The following commands are available:

         o heapshot: perform a heapshot as soon as possible

       o counters: sample counters values every 1 second. This allow a really
         lightweight way to have insight in some of the runtime key metrics.
         Counters displayed in non verbose mode are : Methods from AOT,
         Methods JITted using mono JIT, Methods JITted using LLVM, Total time
         spent JITting (sec), User Time, System Time, Total Time, Working Set,
         Private Bytes, Virtual Bytes, Page Faults and CPU Load Average (1min,
         5min and 15min).

   Analyzing the profile data
       Currently there is a command line program (mprof-report) to analyze the
       data produced by the profiler.  This is ran automatically when the
       report profiler option is used.  Simply run:

       mprof-report output.mlpd

       to see a summary report of the data included in the file.

   Trace information for events
       Often it is important for some events, like allocations, lock
       contention and exception throws to know where they happened.  Or we may
       want to see what sequence of calls leads to a particular method
       invocation.  To see this info invoke mprof-report as follows:

       mprof-report --traces output.mlpd

       The maximum number of methods in each stack trace can be specified with
       the --maxframes=NUM option:

       mprof-report --traces --maxframes=4 output.mlpd

       The stack trace info will be available if method enter/leave events
       have been recorded or if stack trace collection wasn't explicitly
       disabled with the maxframes=0 profiler option.  Note that the profiler
       will collect up to 8 frames by default at specific events when the
       nocalls option is used, so in that case, if more stack frames are
       required in mprof-report, a bigger value for maxframes when profiling
       must be used, too.

       The --traces option also controls the reverse reference feature in the
       heapshot report: for each class it reports how many references to
       objects of that class come from other classes.

   Sort order for methods and allocations
       When a list of methods is printed the default sort order is based on
       the total time spent in the method.  This time is wall clock time (that
       is, it includes the time spent, for example, in a sleep call, even if
       actual cpu time would be basically 0).  Also, if the method has been
       ran on different threads, the time will be a sum of the time used in
       each thread.

       To change the sort order, use the option:


       where MODE can be:

       o self: amount of time spent in the method itself and not in its

       o calls: the number of method invocations

       o total: the total time spent in the method.

       Object allocation lists are sorted by default depending on the total
       amount of bytes used by each type.

       To change the sort order of object allocations, use the option:


       where MODE can be:

       o count: the number of allocated objects of the given type

       o bytes: the total number of bytes used by objects of the given type

       To change the sort order of counters, use the option:


       where MODE can be:

       o time: sort values by time then category

       o category: sort values by category then time

   Selecting what data to report
       The profiler by default collects data about many runtime subsystems and
       mprof-report prints a summary of all the subsystems that are found in
       the data file.  It is possible to tell mprof-report to only show
       information about some of them with the following option:


       where the report names R1, R2 etc.  can be:

       o header: information about program startup and profiler version

       o jit: JIT compiler information

       o sample: statistical sampling information

       o gc: garbage collection information

       o alloc: object allocation information

       o call: method profiling information

       o metadata: metadata events like image loads

       o exception: exception throw and handling information

       o monitor: lock contention information

       o thread: thread information

       o heapshot: live heap usage at heap shots

       o counters: counters samples

       It is possible to limit some of the data displayed to a timeframe of
       the program execution with the option:


       where FROM and TO are seconds since application startup (they can be
       floating point numbers).

       Another interesting option is to consider only events happening on a
       particular thread with the following option:


       where THREADID is one of the numbers listed in the thread summary
       report (or a thread name when present).

       By default long lists of methods or other information like object
       allocations are limited to the most important data.  To increase the
       amount of information printed you can use the option:


   Track individual objects
       Instead of printing the usual reports from the profiler data, it is
       possible to track some interesting information about some specific
       object addresses.  The objects are selected based on their address with
       the --track option as follows:


       The reported info (if available in the data file), will be class name,
       size, creation time, stack trace of creation (with the --traces
       option), etc.  If heapshot data is available it will be possible to
       also track what other objects reference one of the listed addresses.

       The object addresses can be gathered either from the profiler report in
       some cases (like in the monitor lock report), from the live application
       or they can be selected with the --find=FINDSPEC option.  FINDSPEC can
       be one of the following:

       o S:SIZE: where the object is selected if it's size is at least SIZE

       o T:NAME: where the object is selected if NAME partially matches its
         class name

       This option can be specified multiple times with one of the different
       kinds of FINDSPEC.  For example, the following:

       --find=S:10000 --find=T:Byte[]

       will find all the byte arrays that are at least 10000 bytes in size.

       Note that with a moving garbage collector the object address can
       change, so you may need to track the changed address manually.  It can
       also happen that multiple objects are allocated at the same address, so
       the output from this option can become large.

   Saving a profiler report
       By default mprof-report will print the summary data to the console.  To
       print it to a file, instead, use the option:


   Dealing with profiler slowness
       If the profiler needs to collect lots of data, the execution of the
       program will slow down significantly, usually 10 to 20 times slower.
       There are several ways to reduce the impact of the profiler on the
       program execution.

   Use the statistical sampling mode
       Statistical sampling allows executing a program under the profiler with
       minimal performance overhead (usually less than 10%).  This mode allows
       checking where the program is spending most of it's execution time
       without significantly perturbing its behaviour.

   Collect less data
       Collecting method enter/leave events can be very expensive, especially
       in programs that perform many millions of tiny calls.  The profiler
       option nocalls can be used to avoid collecting this data or it can be
       limited to only a few call levels with the calldepth option.

       Object allocation information is expensive as well, though much less
       than method enter/leave events.  If it's not needed, it can be skipped
       with the noalloc profiler option.  Note that when method enter/leave
       events are discarded, by default stack traces are collected at each
       allocation and this can be expensive as well.  The impact of stack
       trace information can be reduced by setting a low value with the
       maxframes option or by eliminating them completely, by setting it to 0.

       The other major source of data is the heapshot profiler option:
       especially if the managed heap is big, since every object needs to be
       inspected.  The MODE parameter of the heapshot option can be used to
       reduce the frequency of the heap shots.

   Reduce the timestamp overhead
       On many operating systems or architectures what actually slows down
       profiling is the function provided by the system to get timestamp
       information.  The time=fast profiler option can be usually used to
       speed up this operation, but, depending on the system, time accounting
       may have some level of approximation (though statistically the data
       should be still fairly valuable).

   Dealing with the size of the data files
       When collecting a lot of information about a profiled program, huge
       data files can be generated.  There are a few ways to minimize the
       amount of data, for example by not collecting some of the more space-
       consuming information or by compressing the information on the fly or
       by just generating a summary report.

   Reducing the amount of data
       Method enter/leave events can be excluded completely with the nocalls
       option or they can be limited to just a few levels of calls with the
       calldepth option.  For example, the option:


       will ignore the method events when there are more than 10 managed stack
       frames.  This is very useful for programs that have deep recursion or
       for programs that perform many millions of tiny calls deep enough in
       the call stack.  The optimal number for the calldepth option depends on
       the program and it needs to be balanced between providing enough
       profiling information and allowing fast execution speed.

       Note that by default, if method events are not recorded at all, the
       profiler will collect stack trace information at events like
       allocations.  To avoid gathering this data, use the maxframes=0
       profiler option.

       Allocation events can be eliminated with the noalloc option.

       Heap shot data can also be huge: by default it is collected at each
       major collection.  To reduce the frequency, you can specify a heapshot
       mode: for example to collect every 5 collections (including major and


       or when at least 5 seconds passed since the last heap shot:


   Compressing the data
       To reduce the amout of disk space used by the data, the data can be
       compressed either after it has been generated with the gzip command:

       gzip -9 output.mlpd

       or it can be compressed automatically by using the zip profiler option.
       Note that in this case there could be a significant slowdown of the
       profiled program.

       The mprof-report program will tranparently deal with either compressed
       or uncompressed data files.

   Generating only a summary report
       Often it's enough to look at the profiler summary report to diagnose an
       issue and in this case it's possible to avoid saving the profiler data
       file to disk.  This can be accomplished with the report profiler
       option, which will basically send the data to the mprof-report program
       for display.

       To have more control of what summary information is reported (or to use
       a completely different program to decode the profiler data), the output
       profiler option can be used, with | as the first character: the rest of
       the output name will be executed as a program with the data fed in on
       the standard input.

       For example, to print only the Monitor summary with stack trace
       information, you could use it like this:

       output=|mprof-report --reports=monitor --traces -






Paolo Molaro. mprof-report(1)

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