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235 lines
9.4 KiB
Perl
235 lines
9.4 KiB
Perl
.\" Copyright (c) 1984 M. K. McKusick
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.\" Copyright (c) 1984 The Regents of the University of California.
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.\" All rights reserved.
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.\"
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.\" Redistribution and use in source and binary forms, with or without
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.\" modification, are permitted provided that the following conditions
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.\" are met:
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.\" 1. Redistributions of source code must retain the above copyright
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.\" notice, this list of conditions and the following disclaimer.
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.\" 2. Redistributions in binary form must reproduce the above copyright
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.\" notice, this list of conditions and the following disclaimer in the
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.\" documentation and/or other materials provided with the distribution.
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.\" 3. All advertising materials mentioning features or use of this software
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.\" must display the following acknowledgement:
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.\" This product includes software developed by the University of
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.\" California, Berkeley and its contributors.
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.\" 4. Neither the name of the University nor the names of its contributors
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.\" may be used to endorse or promote products derived from this software
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.\" without specific prior written permission.
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.\"
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.\" THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND
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.\" ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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.\" IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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.\" ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE
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.\" FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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.\" DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
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.\" OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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.\" HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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.\" LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
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.\" OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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.\" SUCH DAMAGE.
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.\"
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.\" @(#)2.t 1.3 (Berkeley) 11/8/90
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.\"
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.ds RH The \fIgprof\fP Profiler
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.NH 1
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The \fIgprof\fP Profiler
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.PP
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The purpose of the \fIgprof\fP profiling tool is to
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help the user evaluate alternative implementations
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of abstractions.
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The \fIgprof\fP design takes advantage of the fact that the kernel
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though large, is structured and hierarchical.
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We provide a profile in which the execution time
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for a set of routines that implement an
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abstraction is collected and charged
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to that abstraction.
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The profile can be used to compare and assess the costs of
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various implementations [Graham82] [Graham83].
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.NH 2
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Data presentation
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.PP
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The data is presented to the user in two different formats.
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The first presentation simply lists the routines
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without regard to the amount of time their descendants use.
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The second presentation incorporates the call graph of the
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kernel.
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.NH 3
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The Flat Profile
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.PP
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The flat profile consists of a list of all the routines
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that are called during execution of the kernel,
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with the count of the number of times they are called
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and the number of seconds of execution time for which they
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are themselves accountable.
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The routines are listed in decreasing order of execution time.
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A list of the routines that are never called during execution of
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the kernel is also available
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to verify that nothing important is omitted by
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this profiling run.
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The flat profile gives a quick overview of the routines that are used,
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and shows the routines that are themselves responsible
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for large fractions of the execution time.
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In practice,
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this profile usually shows that no single function
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is overwhelmingly responsible for
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the total time of the kernel.
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Notice that for this profile,
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the individual times sum to the total execution time.
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.NH 3
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The Call Graph Profile
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.PP
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Ideally, we would like to print the call graph of the kernel,
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but we are limited by the two-dimensional nature of our output
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devices.
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We cannot assume that a call graph is planar,
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and even if it is, that we can print a planar version of it.
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Instead, we choose to list each routine,
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together with information about
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the routines that are its direct parents and children.
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This listing presents a window into the call graph.
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Based on our experience,
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both parent information and child information
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is important,
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and should be available without searching
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through the output.
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Figure 1 shows a sample \fIgprof\fP entry.
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.KF
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.DS L
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.TS
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box center;
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c c c c c l l
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c c c c c l l
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c c c c c l l
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l n n n c l l.
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called/total \ \ parents
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index %time self descendants called+self name index
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called/total \ \ children
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_
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0.20 1.20 4/10 \ \ \s-1CALLER1\s+1 [7]
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0.30 1.80 6/10 \ \ \s-1CALLER2\s+1 [1]
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[2] 41.5 0.50 3.00 10+4 \s-1EXAMPLE\s+1 [2]
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1.50 1.00 20/40 \ \ \s-1SUB1\s+1 <cycle1> [4]
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0.00 0.50 1/5 \ \ \s-1SUB2\s+1 [9]
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0.00 0.00 0/5 \ \ \s-1SUB3\s+1 [11]
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.TE
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.ce
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Figure 1. Profile entry for \s-1EXAMPLE\s+1.
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.DE
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.KE
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.PP
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The major entries of the call graph profile are the entries from the
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flat profile, augmented by the time propagated to each
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routine from its descendants.
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This profile is sorted by the sum of the time for the routine
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itself plus the time inherited from its descendants.
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The profile shows which of the higher level routines
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spend large portions of the total execution time
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in the routines that they call.
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For each routine, we show the amount of time passed by each child
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to the routine, which includes time for the child itself
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and for the descendants of the child
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(and thus the descendants of the routine).
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We also show the percentage these times represent of the total time
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accounted to the child.
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Similarly, the parents of each routine are listed,
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along with time,
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and percentage of total routine time,
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propagated to each one.
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.PP
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Cycles are handled as single entities.
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The cycle as a whole is shown as though it were a single routine,
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except that members of the cycle are listed in place of the children.
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Although the number of calls of each member
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from within the cycle are shown,
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they do not affect time propagation.
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When a child is a member of a cycle,
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the time shown is the appropriate fraction of the time
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for the whole cycle.
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Self-recursive routines have their calls broken
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down into calls from the outside and self-recursive calls.
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Only the outside calls affect the propagation of time.
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.PP
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The example shown in Figure 2 is the fragment of a call graph
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corresponding to the entry in the call graph profile listing
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shown in Figure 1.
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.KF
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.DS L
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.so fig2.pic
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.ce
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Figure 2. Example call graph fragment.
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.DE
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.KE
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.PP
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The entry is for routine \s-1EXAMPLE\s+1, which has
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the Caller routines as its parents,
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and the Sub routines as its children.
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The reader should keep in mind that all information
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is given \fIwith respect to \s-1EXAMPLE\s+1\fP.
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The index in the first column shows that \s-1EXAMPLE\s+1
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is the second entry in the profile listing.
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The \s-1EXAMPLE\s+1 routine is called ten times, four times by \s-1CALLER1\s+1,
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and six times by \s-1CALLER2\s+1.
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Consequently 40% of \s-1EXAMPLE\s+1's time is propagated to \s-1CALLER1\s+1,
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and 60% of \s-1EXAMPLE\s+1's time is propagated to \s-1CALLER2\s+1.
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The self and descendant fields of the parents
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show the amount of self and descendant time \s-1EXAMPLE\s+1
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propagates to them (but not the time used by
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the parents directly).
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Note that \s-1EXAMPLE\s+1 calls itself recursively four times.
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The routine \s-1EXAMPLE\s+1 calls routine \s-1SUB1\s+1 twenty times, \s-1SUB2\s+1 once,
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and never calls \s-1SUB3\s+1.
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Since \s-1SUB2\s+1 is called a total of five times,
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20% of its self and descendant time is propagated to \s-1EXAMPLE\s+1's
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descendant time field.
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Because \s-1SUB1\s+1 is a member of \fIcycle 1\fR,
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the self and descendant times
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and call count fraction
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are those for the cycle as a whole.
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Since cycle 1 is called a total of forty times
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(not counting calls among members of the cycle),
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it propagates 50% of the cycle's self and descendant
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time to \s-1EXAMPLE\s+1's descendant time field.
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Finally each name is followed by an index that shows
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where on the listing to find the entry for that routine.
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.NH 2
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Profiling the Kernel
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.PP
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It is simple to build a 4.2BSD kernel that will automatically
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collect profiling information as it operates simply by specifying the
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.B \-p
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option to \fIconfig\fP\|(8) when configuring a kernel.
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The program counter sampling can be driven by the system clock,
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or by an alternate real time clock.
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The latter is highly recommended as use of the system clock results
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in statistical anomalies in accounting for
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the time spent in the kernel clock routine.
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.PP
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Once a profiling system has been booted statistic gathering is
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handled by \fIkgmon\fP\|(8).
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\fIKgmon\fP allows profiling to be started and stopped
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and the internal state of the profiling buffers to be dumped.
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\fIKgmon\fP can also be used to reset the state of the internal
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buffers to allow multiple experiments to be run without
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rebooting the machine.
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The profiling data can then be processed with \fIgprof\fP\|(1)
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to obtain information regarding the system's operation.
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.PP
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A profiled system is about 5-10% larger in its text space because of
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the calls to count the subroutine invocations.
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When the system executes,
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the profiling data is stored in a buffer that is 1.2
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times the size of the text space.
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All the information is summarized in memory,
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it is not necessary to have a trace file
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being continuously dumped to disk.
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The overhead for running a profiled system varies;
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under normal load we see anywhere from 5-25%
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of the system time spent in the profiling code.
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Thus the system is noticeably slower than an unprofiled system,
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yet is not so bad that it cannot be used in a production environment.
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This is important since it allows us to gather data
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in a real environment rather than trying to
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devise synthetic work loads.
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