2007-03-22 03:00:33 +00:00
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<HTML>
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<HEAD>
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<title>Google CPU Profiler</title>
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</HEAD>
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<BODY>
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This is the CPU profiler we use at Google. There are three parts to
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using it: linking the library into an application, running the code,
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and analyzing the output.
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<H1>Linking in the Library</H1>
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<p>To install the CPU profiler into your executable, add -lprofiler to
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the link-time step for your executable. (It's also probably possible
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to add in the profiler at run-time using LD_PRELOAD, but this isn't
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necessarily recommended.)</p>
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<p>This does <i>not</i> turn on CPU profiling; it just inserts the code.
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For that reason, it's practical to just always link -lprofiler into a
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binary while developing; that's what we do at Google. (However, since
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any user can turn on the profiler by setting an environment variable,
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it's not necessarily recommended to install profiler-linked binaries
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into a production, running system.)</p>
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<H1>Running the Code</H1>
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<p>There are two alternatives to actually turn on CPU profiling for a
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given run of an executable:</p>
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<ol>
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<li> Define the environment variable CPUPROFILE to the filename to dump the
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profile to. For instance, to profile /usr/local/netscape:
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<pre>
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$ CPUPROFILE=/tmp/profile /usr/local/netscape # sh
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% setenv CPUPROFILE /tmp/profile; /usr/local/netscape # csh
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</pre>
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OR
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<li> In your code, bracket the code you want profiled in calls to
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ProfilerStart() and ProfilerStop(). ProfilerStart() will take the
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profile-filename as an argument.
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</ol>
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2007-03-22 04:44:18 +00:00
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<p>In Linux 2.6 and above, profiling works correctly with threads,
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automatically profiling all threads. In Linux 2.4, profiling only
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profiles the main thread (due to a kernel bug involving itimers and
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threads). Profiling works correctly with sub-processes: each child
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2007-03-22 03:28:56 +00:00
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process gets its own profile with its own name (generated by combining
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CPUPROFILE with the child's process id).</p>
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2007-03-22 03:00:33 +00:00
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2007-03-22 03:28:56 +00:00
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<p>For security reasons, CPU profiling will not write to a file -- and
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is thus not usable -- for setuid programs.</p>
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<H2>Controlling Behavior via the Environment</H2>
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<p>In addition to the environment variable <code>CPUPROFILE</code>,
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which determines where profiles are written, there are several
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environment variables which control the performance of the CPU
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profile.</p>
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<table frame=box rules=sides cellpadding=5 width=100%>
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<tr>
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<td><code>PROFILEFREQUENCY=<i>x</i></code></td>
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<td>How many interrupts/second the cpu-profiler samples.
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</td>
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</tr>
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</table>
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2007-03-22 03:00:33 +00:00
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<H1>Analyzing the Output</H1>
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<p>pprof is the script used to analyze a profile. It has many output
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modes, both textual and graphical. Some give just raw numbers, much
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like the -pg output of gcc, and others show the data in the form of a
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dependency graph.</p>
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<p>pprof <b>requires</b> perl5 to be installed to run. It also
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requires dot to be installed for any of the graphical output routines,
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and gv to be installed for --gv mode (described below).</p>
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<p>Here are some ways to call pprof. These are described in more
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detail below.</p>
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<pre>
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% pprof "program" "profile"
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Generates one line per procedure
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% pprof --gv "program" "profile"
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Generates annotated call-graph and displays via "gv"
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% pprof --gv --focus=Mutex "program" "profile"
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Restrict to code paths that involve an entry that matches "Mutex"
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% pprof --gv --focus=Mutex --ignore=string "program" "profile"
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Restrict to code paths that involve an entry that matches "Mutex"
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and does not match "string"
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% pprof --list=IBF_CheckDocid "program" "profile"
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Generates disassembly listing of all routines with at least one
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sample that match the --list=<regexp> pattern. The listing is
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annotated with the flat and cumulative sample counts at each line.
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% pprof --disasm=IBF_CheckDocid "program" "profile"
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Generates disassembly listing of all routines with at least one
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sample that match the --disasm=<regexp> pattern. The listing is
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annotated with the flat and cumulative sample counts at each PC value.
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</pre>
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<h3>Node Information</h3>
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<p>In the various graphical modes of pprof, the output is a call graph
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annotated with timing information, like so:</p>
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<A HREF="pprof-test-big.gif">
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<center><table><tr><td>
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<img src="pprof-test.gif">
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</td></tr></table></center>
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</A>
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<p>Each node represents a procedure.
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The directed edges indicate caller to callee relations. Each node is
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formatted as follows:</p>
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<center><pre>
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Class Name
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Method Name
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local (percentage)
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<b>of</b> cumulative (percentage)
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</pre></center>
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<p>The last one or two lines contains the timing information. (The
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profiling is done via a sampling method, where by default we take 100
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samples a second. Therefor one unit of time in the output corresponds
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to about 10 milliseconds of execution time.) The "local" time is the
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time spent executing the instructions directly contained in the
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procedure (and in any other procedures that were inlined into the
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procedure). The "cumulative" time is the sum of the "local" time and
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the time spent in any callees. If the cumulative time is the same as
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the local time, it is not printed.
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<p>For instance, the timing information for test_main_thread()
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indicates that 155 units (about 1.55 seconds) were spent executing the
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code in test_main_thread() and 200 units were spent while executing
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test_main_thread() and its callees such as snprintf().</p>
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<p>The size of the node is proportional to the local count. The
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percentage displayed in the node corresponds to the count divided by
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the total run time of the program (that is, the cumulative count for
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main()).</p>
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<h3>Edge Information</h3>
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<p>An edge from one node to another indicates a caller to callee
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relationship. Each edge is labelled with the time spent by the callee
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on behalf of the caller. E.g, the edge from test_main_thread() to
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snprintf() indicates that of the 200 samples in
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test_main_thread(), 37 are because of calls to snprintf().</p>
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<p>Note that test_main_thread() has an edge to vsnprintf(), even
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though test_main_thread() doesn't call that function directly. This
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is because the code was compiled with -O2; the profile reflects the
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optimized control flow.</p>
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<h3>Meta Information</h3>
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The top of the display should contain some meta information like:
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<pre>
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/tmp/profiler2_unittest
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Total samples: 202
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Focusing on: 202
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Dropped nodes with <= 1 abs(samples)
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Dropped edges with <= 0 samples
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</pre>
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This section contains the name of the program, and the total samples
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collected during the profiling run. If the --focus option is on (see
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the <a href="#focus">Focus</a> section below), the legend also
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contains the number of samples being shown in the focused display.
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Furthermore, some unimportant nodes and edges are dropped to reduce
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clutter. The characteristics of the dropped nodes and edges are also
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displayed in the legend.
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<h3><a name=focus>Focus and Ignore</a></h3>
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<p>You can ask pprof to generate a display focused on a particular
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piece of the program. You specify a regular expression. Any portion
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of the call-graph that is on a path which contains at least one node
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matching the regular expression is preserved. The rest of the
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call-graph is dropped on the floor. For example, you can focus on the
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vsnprintf() libc call in profiler2_unittest as follows:</p>
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<pre>
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% pprof --gv --focus=vsnprintf /tmp/profiler2_unittest test.prof
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</pre>
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<A HREF="pprof-vsnprintf-big.gif">
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<center><table><tr><td>
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<img src="pprof-vsnprintf.gif">
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</td></tr></table></center>
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</A>
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<p>
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Similarly, you can supply the --ignore option to ignore
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samples that match a specified regular expression. E.g.,
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if you are interested in everything except calls to snprintf(),
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you can say:
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<pre>
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% pprof --gv --ignore=snprintf /tmp/profiler2_unittest test.prof
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</pre>
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<h3><a name=options>pprof Options</a></h3>
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<h4>Output Type</h4>
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<p>
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<center>
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<table frame=box rules=sides cellpadding=5 width=100%>
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<tr valign=top>
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<td><code>--text</code></td>
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<td>
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Produces a textual listing. This is currently the default
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since it does not need to access to an X display, or
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dot or gv. However if you
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have these programs installed, you will probably be
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happier with the --gv output.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--gv</code></td>
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<td>
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Generates annotated call-graph, converts to postscript, and
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displays via gv.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--dot</code></td>
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<td>
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Generates the annotated call-graph in dot format and
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emits to stdout.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--ps</code></td>
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<td>
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Generates the annotated call-graph in Postscript format and
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emits to stdout.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--gif</code></td>
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<td>
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Generates the annotated call-graph in GIF format and
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emits to stdout.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--list=<<i>regexp</i>></code></td>
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<td>
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<p>Outputs source-code listing of routines whose
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name matches <regexp>. Each line
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in the listing is annotated with flat and cumulative
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sample counts.</p>
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<p>In the presence of inlined calls, the samples
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associated with inlined code tend to get assigned
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to a line that follows the location of the
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inlined call. A more precise accounting can be
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obtained by disassembling the routine using the
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--disasm flag.</p>
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</td>
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</tr>
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<tr valign=top>
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<td><code>--disasm=<<i>regexp</i>></code></td>
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<td>
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Generates disassembly of routines that match
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<regexp>, annotated with flat and
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cumulative sample counts and emits to stdout.
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</td>
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</tr>
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</table>
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</center>
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<h4>Reporting Granularity</h4>
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<p>By default, pprof produces one entry per procedure. However you can
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use one of the following options to change the granularity of the
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output. The --files option seems to be particularly useless, and may
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be removed eventually.</p>
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<center>
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<table frame=box rules=sides cellpadding=5 width=100%>
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<tr valign=top>
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<td><code>--addresses</code></td>
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<td>
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Produce one node per program address.
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</td>
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</tr>
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<td><code>--lines</code></td>
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<td>
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Produce one node per source line.
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</td>
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</tr>
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<td><code>--functions</code></td>
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<td>
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Produce one node per function (this is the default).
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</td>
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</tr>
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<td><code>--files</code></td>
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<td>
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Produce one node per source file.
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</td>
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</tr>
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</table>
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</center>
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<h4>Controlling the Call Graph Display</h4>
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<p>Some nodes and edges are dropped to reduce clutter in the output
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display. The following options control this effect:</p>
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<center>
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<table frame=box rules=sides cellpadding=5 width=100%>
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<tr valign=top>
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<td><code>--nodecount=<n></code></td>
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<td>
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This option controls the number of displayed nodes. The nodes
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are first sorted by decreasing cumulative count, and then only
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the top N nodes are kept. The default value is 80.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--nodefraction=<f></code></td>
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<td>
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This option provides another mechanism for discarding nodes
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from the display. If the cumulative count for a node is
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less than this option's value multiplied by the total count
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for the profile, the node is dropped. The default value
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is 0.005; i.e. nodes that account for less than
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half a percent of the total time are dropped. A node
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is dropped if either this condition is satisfied, or the
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--nodecount condition is satisfied.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--edgefraction=<f></code></td>
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<td>
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This option controls the number of displayed edges. First of all,
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an edge is dropped if either its source or destination node is
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dropped. Otherwise, the edge is dropped if the sample
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count along the edge is less than this option's value multiplied
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by the total count for the profile. The default value is
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0.001; i.e., edges that account for less than
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0.1% of the total time are dropped.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--focus=<re></code></td>
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<td>
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This option controls what region of the graph is displayed
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based on the regular expression supplied with the option.
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For any path in the callgraph, we check all nodes in the path
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against the supplied regular expression. If none of the nodes
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match, the path is dropped from the output.
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</td>
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</tr>
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<tr valign=top>
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<td><code>--ignore=<re></code></td>
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<td>
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This option controls what region of the graph is displayed
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based on the regular expression supplied with the option.
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For any path in the callgraph, we check all nodes in the path
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against the supplied regular expression. If any of the nodes
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match, the path is dropped from the output.
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</td>
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</tr>
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</table>
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</center>
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<p>The dropped edges and nodes account for some count mismatches in
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the display. For example, the cumulative count for
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snprintf() in the first diagram above was 41. However the local
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count (1) and the count along the outgoing edges (12+1+20+6) add up to
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only 40.</p>
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<h1>Caveats</h1>
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<ul>
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<li> If the program exits because of a signal, the generated profile
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will be <font color=red>incomplete, and may perhaps be
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completely empty.</font>
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<li> The displayed graph may have disconnected regions because
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of the edge-dropping heuristics described above.
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<li> If the program linked in a library that was not compiled
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with enough symbolic information, all samples associated
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with the library may be charged to the last symbol found
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in the program before the libary. This will artificially
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inflate the count for that symbol.
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<li> If you run the program on one machine, and profile it on another,
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and the shared libraries are different on the two machines, the
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profiling output may be confusing: samples that fall within
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the shared libaries may be assigned to arbitrary procedures.
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2007-03-22 03:28:56 +00:00
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<li> If your program forks, the children will also be profiled (since
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they inherit the same CPUPROFILE setting). Each process is
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profiled separately; to distinguish the child profiles from the
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parent profile and from each other, all children will have their
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process-id appended to the CPUPROFILE name.
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<li> Due to a hack we make to work around a possible gcc bug, your
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profiles may end up named strangely if the first character of
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your CPUPROFILE variable has ascii value greater than 127. This
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should be exceedingly rare, but if you need to use such a name,
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just set prepend <code>./</code> to your filename:
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<code>CPUPROFILE=./Ägypten</code>.
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2007-03-22 03:00:33 +00:00
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</ul>
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<hr>
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2007-03-22 03:28:56 +00:00
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Last modified: Wed Apr 20 04:54:23 PDT 2005
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2007-03-22 03:00:33 +00:00
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</body>
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</html>
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