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<title>GNU gprof: How do I?</title>
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<a name="How-do-I_003f"></a>
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<p>
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Next: <a href="Incompatibilities.html#Incompatibilities" accesskey="n" rel="next">Incompatibilities</a>, Previous: <a href="Inaccuracy.html#Inaccuracy" accesskey="p" rel="previous">Inaccuracy</a>, Up: <a href="index.html#Top" accesskey="u" rel="up">Top</a> [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>]</p>
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<a name="Answers-to-Common-Questions"></a>
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<h2 class="chapter">7 Answers to Common Questions</h2>
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<dl compact="compact">
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<dt>How can I get more exact information about hot spots in my program?</dt>
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<dd>
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<p>Looking at the per-line call counts only tells part of the story.
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Because <code>gprof</code> can only report call times and counts by function,
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the best way to get finer-grained information on where the program
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is spending its time is to re-factor large functions into sequences
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of calls to smaller ones. Beware however that this can introduce
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artificial hot spots since compiling with ‘<samp>-pg</samp>’ adds a significant
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overhead to function calls. An alternative solution is to use a
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non-intrusive profiler, e.g. oprofile.
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</p>
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</dd>
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<dt>How do I find which lines in my program were executed the most times?</dt>
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<dd>
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<p>Use the <code>gcov</code> program.
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</p>
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</dd>
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<dt>How do I find which lines in my program called a particular function?</dt>
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<dd>
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<p>Use ‘<samp>gprof -l</samp>’ and lookup the function in the call graph.
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The callers will be broken down by function and line number.
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</p>
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</dd>
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<dt>How do I analyze a program that runs for less than a second?</dt>
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<dd>
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<p>Try using a shell script like this one:
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</p>
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<div class="example">
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<pre class="example">for i in `seq 1 100`; do
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fastprog
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mv gmon.out gmon.out.$i
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done
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gprof -s fastprog gmon.out.*
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gprof fastprog gmon.sum
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</pre></div>
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<p>If your program is completely deterministic, all the call counts
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will be simple multiples of 100 (i.e., a function called once in
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each run will appear with a call count of 100).
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</p>
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</dd>
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</dl>
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