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