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<title>GNU gprof: Implementation</title>
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<a name="Implementation"></a>
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<div class="header">
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<p>
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Next: <a href="File-Format.html#File-Format" accesskey="n" rel="next">File Format</a>, Up: <a href="Details.html#Details" accesskey="u" rel="up">Details</a> [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>]</p>
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<a name="Implementation-of-Profiling"></a>
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<h3 class="section">9.1 Implementation of Profiling</h3>
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<p>Profiling works by changing how every function in your program is compiled
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so that when it is called, it will stash away some information about where
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it was called from. From this, the profiler can figure out what function
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called it, and can count how many times it was called. This change is made
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by the compiler when your program is compiled with the ‘<samp>-pg</samp>’ option,
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which causes every function to call <code>mcount</code>
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(or <code>_mcount</code>, or <code>__mcount</code>, depending on the OS and compiler)
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as one of its first operations.
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</p>
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<p>The <code>mcount</code> routine, included in the profiling library,
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is responsible for recording in an in-memory call graph table
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both its parent routine (the child) and its parent’s parent. This is
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typically done by examining the stack frame to find both
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the address of the child, and the return address in the original parent.
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Since this is a very machine-dependent operation, <code>mcount</code>
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itself is typically a short assembly-language stub routine
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that extracts the required
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information, and then calls <code>__mcount_internal</code>
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(a normal C function) with two arguments—<code>frompc</code> and <code>selfpc</code>.
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<code>__mcount_internal</code> is responsible for maintaining
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the in-memory call graph, which records <code>frompc</code>, <code>selfpc</code>,
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and the number of times each of these call arcs was traversed.
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</p>
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<p>GCC Version 2 provides a magical function (<code>__builtin_return_address</code>),
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which allows a generic <code>mcount</code> function to extract the
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required information from the stack frame. However, on some
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architectures, most notably the SPARC, using this builtin can be
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very computationally expensive, and an assembly language version
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of <code>mcount</code> is used for performance reasons.
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</p>
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<p>Number-of-calls information for library routines is collected by using a
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special version of the C library. The programs in it are the same as in
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the usual C library, but they were compiled with ‘<samp>-pg</samp>’. If you
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link your program with ‘<samp>gcc … -pg</samp>’, it automatically uses the
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profiling version of the library.
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</p>
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<p>Profiling also involves watching your program as it runs, and keeping a
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histogram of where the program counter happens to be every now and then.
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Typically the program counter is looked at around 100 times per second of
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run time, but the exact frequency may vary from system to system.
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</p>
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<p>This is done is one of two ways. Most UNIX-like operating systems
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provide a <code>profil()</code> system call, which registers a memory
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array with the kernel, along with a scale
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factor that determines how the program’s address space maps
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into the array.
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Typical scaling values cause every 2 to 8 bytes of address space
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to map into a single array slot.
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On every tick of the system clock
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(assuming the profiled program is running), the value of the
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program counter is examined and the corresponding slot in
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the memory array is incremented. Since this is done in the kernel,
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which had to interrupt the process anyway to handle the clock
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interrupt, very little additional system overhead is required.
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</p>
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<p>However, some operating systems, most notably Linux 2.0 (and earlier),
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do not provide a <code>profil()</code> system call. On such a system,
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arrangements are made for the kernel to periodically deliver
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a signal to the process (typically via <code>setitimer()</code>),
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which then performs the same operation of examining the
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program counter and incrementing a slot in the memory array.
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Since this method requires a signal to be delivered to
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user space every time a sample is taken, it uses considerably
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more overhead than kernel-based profiling. Also, due to the
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added delay required to deliver the signal, this method is
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less accurate as well.
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</p>
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<p>A special startup routine allocates memory for the histogram and
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either calls <code>profil()</code> or sets up
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a clock signal handler.
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This routine (<code>monstartup</code>) can be invoked in several ways.
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On Linux systems, a special profiling startup file <code>gcrt0.o</code>,
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which invokes <code>monstartup</code> before <code>main</code>,
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is used instead of the default <code>crt0.o</code>.
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Use of this special startup file is one of the effects
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of using ‘<samp>gcc … -pg</samp>’ to link.
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On SPARC systems, no special startup files are used.
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Rather, the <code>mcount</code> routine, when it is invoked for
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the first time (typically when <code>main</code> is called),
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calls <code>monstartup</code>.
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</p>
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<p>If the compiler’s ‘<samp>-a</samp>’ option was used, basic-block counting
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is also enabled. Each object file is then compiled with a static array
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of counts, initially zero.
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In the executable code, every time a new basic-block begins
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(i.e., when an <code>if</code> statement appears), an extra instruction
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is inserted to increment the corresponding count in the array.
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At compile time, a paired array was constructed that recorded
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the starting address of each basic-block. Taken together,
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the two arrays record the starting address of every basic-block,
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along with the number of times it was executed.
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</p>
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<p>The profiling library also includes a function (<code>mcleanup</code>) which is
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typically registered using <code>atexit()</code> to be called as the
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program exits, and is responsible for writing the file <samp>gmon.out</samp>.
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Profiling is turned off, various headers are output, and the histogram
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is written, followed by the call-graph arcs and the basic-block counts.
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</p>
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<p>The output from <code>gprof</code> gives no indication of parts of your program that
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are limited by I/O or swapping bandwidth. This is because samples of the
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program counter are taken at fixed intervals of the program’s run time.
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Therefore, the
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time measurements in <code>gprof</code> output say nothing about time that your
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program was not running. For example, a part of the program that creates
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so much data that it cannot all fit in physical memory at once may run very
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slowly due to thrashing, but <code>gprof</code> will say it uses little time. On
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the other hand, sampling by run time has the advantage that the amount of
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load due to other users won’t directly affect the output you get.
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</p>
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<hr>
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<p>
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Next: <a href="File-Format.html#File-Format" accesskey="n" rel="next">File Format</a>, Up: <a href="Details.html#Details" accesskey="u" rel="up">Details</a> [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>]</p>
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