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<!DOCTYPE chapter PUBLIC "-//OASIS//DTD DocBook XML V4.2//EN"
"http://www.oasis-open.org/docbook/xml/4.2/docbookx.dtd"
[<!ENTITY % poky SYSTEM "../poky.ent"> %poky; ] >

<chapter id='profile-manual-usage'>

<title>Basic Usage (with examples) for each of the Yocto Tracing Tools</title>

<para>
    This chapter presents basic usage examples for each of the tracing
    tools.
</para>

<section id='profile-manual-perf'>
    <title>perf</title>

    <para>
        The 'perf' tool is the profiling and tracing tool that comes
        bundled with the Linux kernel.
    </para>

    <para>
        Don't let the fact that it's part of the kernel fool you into thinking
        that it's only for tracing and profiling the kernel - you can indeed
        use it to trace and profile just the kernel , but you can also use it
        to profile specific applications separately (with or without kernel
        context), and you can also use it to trace and profile the kernel
        and all applications on the system simultaneously to gain a system-wide
        view of what's going on.
    </para>

    <para>
        In many ways, it aims to be a superset of all the tracing and profiling
        tools available in Linux today, including all the other tools covered
        in this HOWTO. The past couple of years have seen perf subsume a lot
        of the functionality of those other tools, and at the same time those
        other tools have removed large portions of their previous functionality
        and replaced it with calls to the equivalent functionality now
        implemented by the perf subsystem. Extrapolation suggests that at
        some point those other tools will simply become completely redundant
        and go away; until then, we'll cover those other tools in these pages
        and in many cases show how the same things can be accomplished in
        perf and the other tools when it seems useful to do so.
    </para>

    <para>
        The coverage below details some of the most common ways you'll likely
        want to apply the tool; full documentation can be found either within
        the tool itself or in the man pages at
        <ulink url='http://linux.die.net/man/1/perf'>perf(1)</ulink>.
    </para>

    <section id='perf-setup'>
        <title>Setup</title>

        <para>
            For this section, we'll assume you've already performed the basic
            setup outlined in the General Setup section.
        </para>

        <para>
            In particular, you'll get the most mileage out of perf if you
            profile an image built with INHIBIT_PACKAGE_STRIP = "1" in your
            local.conf.
        </para>

        <para>
            perf runs on the target system for the most part. You can archive
            profile data and copy it to the host for analysis, but for the
            rest of this document we assume you've ssh'ed to the host and
            will be running the perf commands on the target.
        </para>
    </section>

    <section id='perf-basic-usage'>
        <title>Basic Usage</title>

        <para>
            The perf tool is pretty much self-documenting. To remind yourself
            of the available commands, simply type 'perf', which will show you
            basic usage along with the available perf subcommands:
            <literallayout class='monospaced'>
     root@crownbay:~# perf

     usage: perf [--version] [--help] COMMAND [ARGS]

     The most commonly used perf commands are:
       annotate        Read perf.data (created by perf record) and display annotated code
       archive         Create archive with object files with build-ids found in perf.data file
       bench           General framework for benchmark suites
       buildid-cache   Manage build-id cache.
       buildid-list    List the buildids in a perf.data file
       diff            Read two perf.data files and display the differential profile
       evlist          List the event names in a perf.data file
       inject          Filter to augment the events stream with additional information
       kmem            Tool to trace/measure kernel memory(slab) properties
       kvm             Tool to trace/measure kvm guest os
       list            List all symbolic event types
       lock            Analyze lock events
       probe           Define new dynamic tracepoints
       record          Run a command and record its profile into perf.data
       report          Read perf.data (created by perf record) and display the profile
       sched           Tool to trace/measure scheduler properties (latencies)
       script          Read perf.data (created by perf record) and display trace output
       stat            Run a command and gather performance counter statistics
       test            Runs sanity tests.
       timechart       Tool to visualize total system behavior during a workload
       top             System profiling tool.

     See 'perf help COMMAND' for more information on a specific command.
        </literallayout>
    </para>

    <section id='using-perf-to-do-basic-profiling'>
        <title>Using perf to do Basic Profiling</title>

        <para>
            As a simple test case, we'll profile the 'wget' of a fairly large
            file, which is a minimally interesting case because it has both
            file and network I/O aspects, and at least in the case of standard
            Yocto images, it's implemented as part of busybox, so the methods
            we use to analyze it can be used in a very similar way to the whole
            host of supported busybox applets in Yocto.
            <literallayout class='monospaced'>
     root@crownbay:~# rm linux-2.6.19.2.tar.bz2; \
     wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
            </literallayout>
            The quickest and easiest way to get some basic overall data about
            what's going on for a particular workload it to profile it using
            'perf stat'. 'perf stat' basically profiles using a few default
            counters and displays the summed counts at the end of the run:
            <literallayout class='monospaced'>
     root@crownbay:~# perf stat wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
     Connecting to downloads.yoctoproject.org (140.211.169.59:80)
     linux-2.6.19.2.tar.b 100% |***************************************************| 41727k  0:00:00 ETA

     Performance counter stats for 'wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2':

           4597.223902 task-clock                #    0.077 CPUs utilized
                 23568 context-switches          #    0.005 M/sec
                    68 CPU-migrations            #    0.015 K/sec
                   241 page-faults               #    0.052 K/sec
            3045817293 cycles                    #    0.663 GHz
       &lt;not supported&gt; stalled-cycles-frontend
       &lt;not supported&gt; stalled-cycles-backend
             858909167 instructions              #    0.28  insns per cycle
             165441165 branches                  #   35.987 M/sec
              19550329 branch-misses             #   11.82% of all branches

          59.836627620 seconds time elapsed
            </literallayout>
            Many times such a simple-minded test doesn't yield much of
            interest, but sometimes it does (see Real-world Yocto bug
            (slow loop-mounted write speed)).
        </para>

        <para>
            Also, note that 'perf stat' isn't restricted to a fixed set of
            counters - basically any event listed in the output of 'perf list'
            can be tallied by 'perf stat'. For example, suppose we wanted to
            see a summary of all the events related to kernel memory
            allocation/freeing along with cache hits and misses:
            <literallayout class='monospaced'>
     root@crownbay:~# perf stat -e kmem:* -e cache-references -e cache-misses wget http://    downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
     Connecting to downloads.yoctoproject.org (140.211.169.59:80)
     linux-2.6.19.2.tar.b 100% |***************************************************| 41727k  0:00:00 ETA

     Performance counter stats for 'wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2':

                  5566 kmem:kmalloc
                125517 kmem:kmem_cache_alloc
                     0 kmem:kmalloc_node
                     0 kmem:kmem_cache_alloc_node
                 34401 kmem:kfree
                 69920 kmem:kmem_cache_free
                   133 kmem:mm_page_free
                    41 kmem:mm_page_free_batched
                 11502 kmem:mm_page_alloc
                 11375 kmem:mm_page_alloc_zone_locked
                     0 kmem:mm_page_pcpu_drain
                     0 kmem:mm_page_alloc_extfrag
              66848602 cache-references
               2917740 cache-misses              #    4.365 % of all cache refs

          44.831023415 seconds time elapsed
            </literallayout>
            So 'perf stat' gives us a nice easy way to get a quick overview of
            what might be happening for a set of events, but normally we'd
            need a little more detail in order to understand what's going on
            in a way that we can act on in a useful way.
        </para>

        <para>
            To dive down into a next level of detail, we can use 'perf
            record'/'perf report' which will collect profiling data and
            present it to use using an interactive text-based UI (or
            simply as text if we specify --stdio to 'perf report').
        </para>

        <para>
            As our first attempt at profiling this workload, we'll simply
            run 'perf record', handing it the workload we want to profile
            (everything after 'perf record' and any perf options we hand
            it - here none - will be executedin a new shell). perf collects
            samples until the process exits and records them in a file named
            'perf.data' in the current working directory.
            <literallayout class='monospaced'>
     root@crownbay:~# perf record wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2

     Connecting to downloads.yoctoproject.org (140.211.169.59:80)
     linux-2.6.19.2.tar.b 100% |************************************************| 41727k  0:00:00 ETA
     [ perf record: Woken up 1 times to write data ]
     [ perf record: Captured and wrote 0.176 MB perf.data (~7700 samples) ]
            </literallayout>
            To see the results in a 'text-based UI' (tui), simply run
            'perf report', which will read the perf.data file in the current
            working directory and display the results in an interactive UI:
            <literallayout class='monospaced'>
     root@crownbay:~# perf report
            </literallayout>
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-flat-stripped.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            The above screenshot displays a 'flat' profile, one entry for
            each 'bucket' corresponding to the functions that were profiled
            during the profiling run, ordered from the most popular to the
            least (perf has options to sort in various orders and keys as
            well as display entries only above a certain threshold and so
            on - see the perf documentation for details). Note that this
            includes both userspace functions (entries containing a [.]) and
            kernel functions accounted to the process (entries containing
            a [k]). (perf has command-line modifiers that can be used to
            restrict the profiling to kernel or userspace, among others).
        </para>

        <para>
            Notice also that the above report shows an entry for 'busybox',
            which is the executable that implements 'wget' in Yocto, but that
            instead of a useful function name in that entry, it displays
            an not-so-friendly hex value instead. The steps below will show
            how to fix that problem.
        </para>

        <para>
            Before we do that, however, let's try running a different profile,
            one which shows something a little more interesting. The only
            difference between the new profile and the previous one is that
            we'll add the -g option, which will record not just the address
            of a sampled function, but the entire callchain to the sampled
            function as well:
            <literallayout class='monospaced'>
     root@crownbay:~# perf record -g wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
     Connecting to downloads.yoctoproject.org (140.211.169.59:80)
     linux-2.6.19.2.tar.b 100% |************************************************| 41727k  0:00:00 ETA
     [ perf record: Woken up 3 times to write data ]
     [ perf record: Captured and wrote 0.652 MB perf.data (~28476 samples) ]


     root@crownbay:~# perf report
            </literallayout>
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-g-copy-to-user-expanded-stripped.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            Using the callgraph view, we can actually see not only which
            functions took the most time, but we can also see a summary of
            how those functions were called and learn something about how the
            program interacts with the kernel in the process.
        </para>

        <para>
            Notice that each entry in the above screenshot now contains a '+'
            on the left-hand side. This means that we can expand the entry and
            drill down into the callchains that feed into that entry.
            Pressing 'enter' on any one of them will expand the callchain
            (you can also press 'E' to expand them all at the same time or 'C'
            to collapse them all).
        </para>

        <para>
            In the screenshot above, we've toggled the __copy_to_user_ll()
            entry and several subnodes all the way down. This lets us see
            which callchains contributed to the profiled __copy_to_user_ll()
            function which contributed 1.77% to the total profile.
        </para>

        <para>
            As a bit of background explanation for these callchains, think
            about what happens at a high level when you run wget to get a file
            out on the network. Basically what happens is that the data comes
            into the kernel via the network connection (socket) and is passed
            to the userspace program 'wget' (which is actually a part of
            busybox, but that's not important for now), which takes the buffers
            the kernel passes to it and writes it to a disk file to save it.
        </para>

        <para>
            The part of this process that we're looking at in the above call
            stacks is the part where the kernel passes the data it's read from
            the socket down to wget i.e. a copy-to-user.
        </para>

        <para>
            Notice also that here there's also a case where the a hex value
            is displayed in the callstack, here in the expanded
            sys_clock_gettime() function. Later we'll see it resolve to a
            userspace function call in busybox.
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-g-copy-from-user-expanded-stripped.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            The above screenshot shows the other half of the journey for the
            data - from the wget program's userspace buffers to disk. To get
            the buffers to disk, the wget program issues a write(2), which
            does a copy-from-user to the kernel, which then takes care via
            some circuitous path (probably also present somewhere in the
            profile data), to get it safely to disk.
        </para>

        <para>
            Now that we've seen the basic layout of the profile data and the
            basics of how to extract useful information out of it, let's get
            back to the task at hand and see if we can get some basic idea
            about where the time is spent in the program we're profiling,
            wget. Remember that wget is actually implemented as an applet
            in busybox, so while the process name is 'wget', the executable
            we're actually interested in is busybox. So let's expand the
            first entry containing busybox:
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-busybox-expanded-stripped.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            Again, before we expanded we saw that the function was labeled
            with a hex value instead of a symbol as with most of the kernel
            entries. Expanding the busybox entry doesn't make it any better.
        </para>

        <para>
            The problem is that perf can't find the symbol information for the
            busybox binary, which is actually stripped out by the Yocto build
            system.
        </para>

        <para>
            One way around that is to put the following in your local.conf
            when you build the image:
            <literallayout class='monospaced'>
     INHIBIT_PACKAGE_STRIP = "1"
            </literallayout>
            However, we already have an image with the binaries stripped,
            so what can we do to get perf to resolve the symbols? Basically
            we need to install the debuginfo for the busybox package.
        </para>

        <para>
            To generate the debug info for the packages in the image, we can
            to add dbg-pkgs to EXTRA_IMAGE_FEATURES in local.conf. For example:
            <literallayout class='monospaced'>
     EXTRA_IMAGE_FEATURES = "debug-tweaks tools-profile dbg-pkgs"
            </literallayout>
            Additionally, in order to generate the type of debuginfo that
            perf understands, we also need to add the following to local.conf:
            <literallayout class='monospaced'>
     PACKAGE_DEBUG_SPLIT_STYLE = 'debug-file-directory'
            </literallayout>
            Once we've done that, we can install the debuginfo for busybox.
            The debug packages once built can be found in
            build/tmp/deploy/rpm/* on the host system. Find the
            busybox-dbg-...rpm file and copy it to the target. For example:
            <literallayout class='monospaced'>
     [trz@empanada core2]$ scp /home/trz/yocto/crownbay-tracing-dbg/build/tmp/deploy/rpm/core2/busybox-dbg-1.20.2-r2.core2.rpm root@192.168.1.31:
     root@192.168.1.31's password:
     busybox-dbg-1.20.2-r2.core2.rpm                     100% 1826KB   1.8MB/s   00:01
            </literallayout>
            Now install the debug rpm on the target:
            <literallayout class='monospaced'>
     root@crownbay:~# rpm -i busybox-dbg-1.20.2-r2.core2.rpm
            </literallayout>
            Now that the debuginfo is installed, we see that the busybox
            entries now display their functions symbolically:
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-busybox-debuginfo.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            If we expand one of the entries and press 'enter' on a leaf node,
            we're presented with a menu of actions we can take to get more
            information related to that entry:
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-busybox-dso-zoom-menu.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            One of these actions allows us to show a view that displays a
            busybox-centric view of the profiled functions (in this case we've
            also expanded all the nodes using the 'E' key):
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-busybox-dso-zoom.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            Finally, we can see that now that the busybox debuginfo is
            installed, the previously unresolved symbol in the
            sys_clock_gettime() entry mentioned previously is now resolved,
            and shows that the sys_clock_gettime system call that was the
            source of 6.75% of the copy-to-user overhead was initiated by
            the handle_input() busybox function:
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-g-copy-to-user-expanded-debuginfo.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            At the lowest level of detail, we can dive down to the assembly
            level and see which instructions caused the most overhead in a
            function. Pressing 'enter' on the 'udhcpc_main' function, we're
            again presented with a menu:
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-busybox-annotate-menu.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            Selecting 'Annotate udhcpc_main', we get a detailed listing of
            percentages by instruction for the udhcpc_main function. From the
            display, we can see that over 50% of the time spent in this
            function is taken up by a couple tests and the move of a
            constant (1) to a register:
        </para>

        <para>
            <imagedata fileref="figures/perf-wget-busybox-annotate-udhcpc.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            As a segue into tracing, let's try another profile using a
            different counter, something other than the default 'cycles'.
        </para>

        <para>
            The tracing and profiling infrastructure in Linux has become
            unified in a way that allows us to use the same tool with a
            completely different set of counters, not just the standard
            hardware counters that traditionally tools have had to restrict
            themselves to (of course the traditional tools can also make use
            of the expanded possibilities now available to them, and in some
            cases have, as mentioned previously).
        </para>

        <para>
            We can get a list of the available events that can be used to
            profile a workload via 'perf list':
            <literallayout class='monospaced'>
     root@crownbay:~# perf list

     List of pre-defined events (to be used in -e):
      cpu-cycles OR cycles                               [Hardware event]
      stalled-cycles-frontend OR idle-cycles-frontend    [Hardware event]
      stalled-cycles-backend OR idle-cycles-backend      [Hardware event]
      instructions                                       [Hardware event]
      cache-references                                   [Hardware event]
      cache-misses                                       [Hardware event]
      branch-instructions OR branches                    [Hardware event]
      branch-misses                                      [Hardware event]
      bus-cycles                                         [Hardware event]
      ref-cycles                                         [Hardware event]

      cpu-clock                                          [Software event]
      task-clock                                         [Software event]
      page-faults OR faults                              [Software event]
      minor-faults                                       [Software event]
      major-faults                                       [Software event]
      context-switches OR cs                             [Software event]
      cpu-migrations OR migrations                       [Software event]
      alignment-faults                                   [Software event]
      emulation-faults                                   [Software event]

      L1-dcache-loads                                    [Hardware cache event]
      L1-dcache-load-misses                              [Hardware cache event]
      L1-dcache-prefetch-misses                          [Hardware cache event]
      L1-icache-loads                                    [Hardware cache event]
      L1-icache-load-misses                              [Hardware cache event]
      .
      .
      .
      rNNN                                               [Raw hardware event descriptor]
      cpu/t1=v1[,t2=v2,t3 ...]/modifier                  [Raw hardware event descriptor]
       (see 'perf list --help' on how to encode it)

      mem:&lt;addr&gt;[:access]                                [Hardware breakpoint]

      sunrpc:rpc_call_status                             [Tracepoint event]
      sunrpc:rpc_bind_status                             [Tracepoint event]
      sunrpc:rpc_connect_status                          [Tracepoint event]
      sunrpc:rpc_task_begin                              [Tracepoint event]
      skb:kfree_skb                                      [Tracepoint event]
      skb:consume_skb                                    [Tracepoint event]
      skb:skb_copy_datagram_iovec                        [Tracepoint event]
      net:net_dev_xmit                                   [Tracepoint event]
      net:net_dev_queue                                  [Tracepoint event]
      net:netif_receive_skb                              [Tracepoint event]
      net:netif_rx                                       [Tracepoint event]
      napi:napi_poll                                     [Tracepoint event]
      sock:sock_rcvqueue_full                            [Tracepoint event]
      sock:sock_exceed_buf_limit                         [Tracepoint event]
      udp:udp_fail_queue_rcv_skb                         [Tracepoint event]
      hda:hda_send_cmd                                   [Tracepoint event]
      hda:hda_get_response                               [Tracepoint event]
      hda:hda_bus_reset                                  [Tracepoint event]
      scsi:scsi_dispatch_cmd_start                       [Tracepoint event]
      scsi:scsi_dispatch_cmd_error                       [Tracepoint event]
      scsi:scsi_eh_wakeup                                [Tracepoint event]
      drm:drm_vblank_event                               [Tracepoint event]
      drm:drm_vblank_event_queued                        [Tracepoint event]
      drm:drm_vblank_event_delivered                     [Tracepoint event]
      random:mix_pool_bytes                              [Tracepoint event]
      random:mix_pool_bytes_nolock                       [Tracepoint event]
      random:credit_entropy_bits                         [Tracepoint event]
      gpio:gpio_direction                                [Tracepoint event]
      gpio:gpio_value                                    [Tracepoint event]
      block:block_rq_abort                               [Tracepoint event]
      block:block_rq_requeue                             [Tracepoint event]
      block:block_rq_issue                               [Tracepoint event]
      block:block_bio_bounce                             [Tracepoint event]
      block:block_bio_complete                           [Tracepoint event]
      block:block_bio_backmerge                          [Tracepoint event]
      .
      .
      writeback:writeback_wake_thread                    [Tracepoint event]
      writeback:writeback_wake_forker_thread             [Tracepoint event]
      writeback:writeback_bdi_register                   [Tracepoint event]
      .
      .
      writeback:writeback_single_inode_requeue           [Tracepoint event]
      writeback:writeback_single_inode                   [Tracepoint event]
      kmem:kmalloc                                       [Tracepoint event]
      kmem:kmem_cache_alloc                              [Tracepoint event]
      kmem:mm_page_alloc                                 [Tracepoint event]
      kmem:mm_page_alloc_zone_locked                     [Tracepoint event]
      kmem:mm_page_pcpu_drain                            [Tracepoint event]
      kmem:mm_page_alloc_extfrag                         [Tracepoint event]
      vmscan:mm_vmscan_kswapd_sleep                      [Tracepoint event]
      vmscan:mm_vmscan_kswapd_wake                       [Tracepoint event]
      vmscan:mm_vmscan_wakeup_kswapd                     [Tracepoint event]
      vmscan:mm_vmscan_direct_reclaim_begin              [Tracepoint event]
      .
      .
      module:module_get                                  [Tracepoint event]
      module:module_put                                  [Tracepoint event]
      module:module_request                              [Tracepoint event]
      sched:sched_kthread_stop                           [Tracepoint event]
      sched:sched_wakeup                                 [Tracepoint event]
      sched:sched_wakeup_new                             [Tracepoint event]
      sched:sched_process_fork                           [Tracepoint event]
      sched:sched_process_exec                           [Tracepoint event]
      sched:sched_stat_runtime                           [Tracepoint event]
      rcu:rcu_utilization                                [Tracepoint event]
      workqueue:workqueue_queue_work                     [Tracepoint event]
      workqueue:workqueue_execute_end                    [Tracepoint event]
      signal:signal_generate                             [Tracepoint event]
      signal:signal_deliver                              [Tracepoint event]
      timer:timer_init                                   [Tracepoint event]
      timer:timer_start                                  [Tracepoint event]
      timer:hrtimer_cancel                               [Tracepoint event]
      timer:itimer_state                                 [Tracepoint event]
      timer:itimer_expire                                [Tracepoint event]
      irq:irq_handler_entry                              [Tracepoint event]
      irq:irq_handler_exit                               [Tracepoint event]
      irq:softirq_entry                                  [Tracepoint event]
      irq:softirq_exit                                   [Tracepoint event]
      irq:softirq_raise                                  [Tracepoint event]
      printk:console                                     [Tracepoint event]
      task:task_newtask                                  [Tracepoint event]
      task:task_rename                                   [Tracepoint event]
      syscalls:sys_enter_socketcall                      [Tracepoint event]
      syscalls:sys_exit_socketcall                       [Tracepoint event]
      .
      .
      .
      syscalls:sys_enter_unshare                         [Tracepoint event]
      syscalls:sys_exit_unshare                          [Tracepoint event]
      raw_syscalls:sys_enter                             [Tracepoint event]
      raw_syscalls:sys_exit                              [Tracepoint event]
            </literallayout>
        </para>

        <note>
            Tying It Together: These are exactly the same set of events defined
            by the trace event subsystem and exposed by
            ftrace/tracecmd/kernelshark as files in
            /sys/kernel/debug/tracing/events, by SystemTap as
            kernel.trace("tracepoint_name") and (partially) accessed by LTTng.
        </note>

        <para>
            Only a subset of these would be of interest to us when looking at
            this workload, so let's choose the most likely subsystems
            (identified by the string before the colon in the Tracepoint events)
            and do a 'perf stat' run using only those wildcarded subsystems:
            <literallayout class='monospaced'>
     root@crownbay:~# perf stat -e skb:* -e net:* -e napi:* -e sched:* -e workqueue:* -e irq:* -e syscalls:* wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
     Performance counter stats for 'wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2':

                 23323 skb:kfree_skb
                     0 skb:consume_skb
                 49897 skb:skb_copy_datagram_iovec
                  6217 net:net_dev_xmit
                  6217 net:net_dev_queue
                  7962 net:netif_receive_skb
                     2 net:netif_rx
                  8340 napi:napi_poll
                     0 sched:sched_kthread_stop
                     0 sched:sched_kthread_stop_ret
                  3749 sched:sched_wakeup
                     0 sched:sched_wakeup_new
                     0 sched:sched_switch
                    29 sched:sched_migrate_task
                     0 sched:sched_process_free
                     1 sched:sched_process_exit
                     0 sched:sched_wait_task
                     0 sched:sched_process_wait
                     0 sched:sched_process_fork
                     1 sched:sched_process_exec
                     0 sched:sched_stat_wait
         2106519415641 sched:sched_stat_sleep
                     0 sched:sched_stat_iowait
             147453613 sched:sched_stat_blocked
           12903026955 sched:sched_stat_runtime
                     0 sched:sched_pi_setprio
                  3574 workqueue:workqueue_queue_work
                  3574 workqueue:workqueue_activate_work
                     0 workqueue:workqueue_execute_start
                     0 workqueue:workqueue_execute_end
                 16631 irq:irq_handler_entry
                 16631 irq:irq_handler_exit
                 28521 irq:softirq_entry
                 28521 irq:softirq_exit
                 28728 irq:softirq_raise
                     1 syscalls:sys_enter_sendmmsg
                     1 syscalls:sys_exit_sendmmsg
                     0 syscalls:sys_enter_recvmmsg
                     0 syscalls:sys_exit_recvmmsg
                    14 syscalls:sys_enter_socketcall
                    14 syscalls:sys_exit_socketcall
                       .
                       .
                       .
                 16965 syscalls:sys_enter_read
                 16965 syscalls:sys_exit_read
                 12854 syscalls:sys_enter_write
                 12854 syscalls:sys_exit_write
                       .
                       .
                       .

          58.029710972 seconds time elapsed
            </literallayout>
            Let's pick one of these tracepoints and tell perf to do a profile
            using it as the sampling event:
            <literallayout class='monospaced'>
     root@crownbay:~# perf record -g -e sched:sched_wakeup wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
            </literallayout>
        </para>

        <para>
            <imagedata fileref="figures/sched-wakeup-profile.png" width="6in" depth="7in" align="center" scalefit="1" />
        </para>

        <para>
            The screenshot above shows the results of running a profile using
            sched:sched_switch tracepoint, which shows the relative costs of
            various paths to sched_wakeup (note that sched_wakeup is the
            name of the tracepoint - it's actually defined just inside
            ttwu_do_wakeup(), which accounts for the function name actually
            displayed in the profile:
            <literallayout class='monospaced'>
     /*
      * Mark the task runnable and perform wakeup-preemption.
      */
     static void
     ttwu_do_wakeup(struct rq *rq, struct task_struct *p, int wake_flags)
     {
          trace_sched_wakeup(p, true);
          .
          .
          .
     }
            </literallayout>
            A couple of the more interesting callchains are expanded and
            displayed above, basically some network receive paths that
            presumably end up waking up wget (busybox) when network data is
            ready.
        </para>

        <para>
            Note that because tracepoints are normally used for tracing,
            the default sampling period for tracepoints is 1 i.e. for
            tracepoints perf will sample on every event occurrence (this
            can be changed using the -c option). This is in contrast to
            hardware counters such as for example the default 'cycles'
            hardware counter used for normal profiling, where sampling
            periods are much higher (in the thousands) because profiling should
            have as low an overhead as possible and sampling on every cycle w
            ould be prohibitively expensive.
        </para>
    </section>

    <section id='using-perf-to-do-basic-tracing'>
        <title>Using perf to do Basic Tracing</title>

        <para>
            Profiling is a great tool for solving many problems or for
            getting a high-level view of what's going on with a workload or
            across the system. It is however by definition an approximation,
            as suggested by the most prominent word associated with it,
            'sampling'. On the one hand, it allows a representative picture of
            what's going on in the system to be cheaply taken, but on the other
            hand, that cheapness limits its utility when that data suggests a
            need to 'dive down' more deeply to discover what's really going
            on. In such cases, the only way to see what's really going on is
            to be able to look at (or summarize more intelligently) the
            individual steps that go into the higher-level behavior exposed
            by the coarse-grained profiling data.
        </para>

        <para>
            As a concrete example, we can trace all the events we think might
            be applicable to our workload:
            <literallayout class='monospaced'>
     root@crownbay:~# perf record -g -e skb:* -e net:* -e napi:* -e sched:sched_switch -e sched:sched_wakeup -e irq:*
      -e syscalls:sys_enter_read -e syscalls:sys_exit_read -e syscalls:sys_enter_write -e syscalls:sys_exit_write
      wget http://downloads.yoctoproject.org/mirror/sources/linux-2.6.19.2.tar.bz2
            </literallayout>
            We can look at the raw trace output using 'perf script' with no
            arguments:
            <literallayout class='monospaced'>
     root@crownbay:~# perf script

           perf  1262 [000] 11624.857082: sys_exit_read: 0x0
           perf  1262 [000] 11624.857193: sched_wakeup: comm=migration/0 pid=6 prio=0 success=1 target_cpu=000
           wget  1262 [001] 11624.858021: softirq_raise: vec=1 [action=TIMER]
           wget  1262 [001] 11624.858074: softirq_entry: vec=1 [action=TIMER]
           wget  1262 [001] 11624.858081: softirq_exit: vec=1 [action=TIMER]
           wget  1262 [001] 11624.858166: sys_enter_read: fd: 0x0003, buf: 0xbf82c940, count: 0x0200
           wget  1262 [001] 11624.858177: sys_exit_read: 0x200
           wget  1262 [001] 11624.858878: kfree_skb: skbaddr=0xeb248d80 protocol=0 location=0xc15a5308
           wget  1262 [001] 11624.858945: kfree_skb: skbaddr=0xeb248000 protocol=0 location=0xc15a5308
           wget  1262 [001] 11624.859020: softirq_raise: vec=1 [action=TIMER]
           wget  1262 [001] 11624.859076: softirq_entry: vec=1 [action=TIMER]
           wget  1262 [001] 11624.859083: softirq_exit: vec=1 [action=TIMER]
           wget  1262 [001] 11624.859167: sys_enter_read: fd: 0x0003, buf: 0xb7720000, count: 0x0400
           wget  1262 [001] 11624.859192: sys_exit_read: 0x1d7
           wget  1262 [001] 11624.859228: sys_enter_read: fd: 0x0003, buf: 0xb7720000, count: 0x0400
           wget  1262 [001] 11624.859233: sys_exit_read: 0x0
           wget  1262 [001] 11624.859573: sys_enter_read: fd: 0x0003, buf: 0xbf82c580, count: 0x0200
           wget  1262 [001] 11624.859584: sys_exit_read: 0x200
           wget  1262 [001] 11624.859864: sys_enter_read: fd: 0x0003, buf: 0xb7720000, count: 0x0400
           wget  1262 [001] 11624.859888: sys_exit_read: 0x400
           wget  1262 [001] 11624.859935: sys_enter_read: fd: 0x0003, buf: 0xb7720000, count: 0x0400
           wget  1262 [001] 11624.859944: sys_exit_read: 0x400
            </literallayout>
            This gives us a detailed timestamped sequence of events that
            occurred within the workload with respect to those events.
        </para>

        <para>
            In many ways, profiling can be viewed as a subset of tracing -
            theoretically, if you have a set of trace events that's sufficient
            to capture all the important aspects of a workload, you can derive
            any of the results or views that a profiling run can.
        </para>

        <para>
            Another aspect of traditional profiling is that while powerful in
            many ways, it's limited by the granularity of the underlying data.
            Profiling tools offer various ways of sorting and presenting the
            sample data, which make it much more useful and amenable to user
            experimentation, but in the end it can't be used in an open-ended
            way to extract data that just isn't present as a consequence of
            the fact that conceptually, most of it has been thrown away.
        </para>

        <para>
            Full-blown detailed tracing data does however offer the opportunity
            to manipulate and present the information collected during a
            tracing run in an infinite variety of ways.
        </para>

        <para>
            Another way to look at it is that there are only so many ways that
            the 'primitive' counters can be used on their own to generate
            interesting output; to get anything more complicated than simple
            counts requires some amount of additional logic, which is typically
            very specific to the problem at hand. For example, if we wanted to
            make use of a 'counter' that maps to the value of the time
            difference between when a process was scheduled to run on a
            processor and the time it actually ran, we wouldn't expect such
            a counter to exist on its own, but we could derive one called say
            'wakeup_latency' and use it to extract a useful view of that metric
            from trace data. Likewise, we really can't figure out from standard
            profiling tools how much data every process on the system reads and
            writes, along with how many of those reads and writes fail
            completely. If we have sufficient trace data, however, we could
            with the right tools easily extract and present that information,
            but we'd need something other than pre-canned profiling tools to
            do that.
        </para>

        <para>
            Luckily, there is general-purpose way to handle such needs,
            called 'programming languages'. Making programming languages
            easily available to apply to such problems given the specific
            format of data is called a 'programming language binding' for
            that data and language. Perf supports two programming language
            bindings, one for Python and one for Perl.
        </para>

        <note>
            Tying It Together: Language bindings for manipulating and
            aggregating trace data are of course not a new
            idea.  One of the first projects to do this was IBM's DProbes
            dpcc compiler, an ANSI C compiler which targeted a low-level
            assembly language running on an in-kernel interpreter on the
            target system.  This is exactly analagous to what Sun's DTrace
            did, except that DTrace invented its own language for the purpose.
            Systemtap, heavily inspired by DTrace, also created its own
            one-off language, but rather than running the product on an
            in-kernel interpreter, created an elaborate compiler-based
            machinery to translate its language into kernel modules written
            in C.
        </note>

        <para>
            Now that we have the trace data in perf.data, we can use
            'perf script -g' to generate a skeleton script with handlers
            for the read/write entry/exit events we recorded:
            <literallayout class='monospaced'>
     root@crownbay:~# perf script -g python
     generated Python script: perf-script.py
            </literallayout>
            The skeleton script simply creates a python function for each
            event type in the perf.data file. The body of each function simply
            prints the event name along with its parameters. For example:
            <literallayout class='monospaced'>
     def net__netif_rx(event_name, context, common_cpu,
            common_secs, common_nsecs, common_pid, common_comm,
            skbaddr, len, name):
                    print_header(event_name, common_cpu, common_secs, common_nsecs,
                            common_pid, common_comm)

		     print "skbaddr=%u, len=%u, name=%s\n" % (skbaddr, len, name),
            </literallayout>
            We can run that script directly to print all of the events
            contained in the perf.data file:
            <literallayout class='monospaced'>
     root@crownbay:~# perf script -s perf-script.py

     in trace_begin
     syscalls__sys_exit_read     0 11624.857082795     1262 perf                  nr=3, ret=0
     sched__sched_wakeup      0 11624.857193498     1262 perf                  comm=migration/0, pid=6, prio=0,      success=1, target_cpu=0
     irq__softirq_raise       1 11624.858021635     1262 wget                  vec=TIMER
     irq__softirq_entry       1 11624.858074075     1262 wget                  vec=TIMER
     irq__softirq_exit        1 11624.858081389     1262 wget                  vec=TIMER
     syscalls__sys_enter_read     1 11624.858166434     1262 wget                  nr=3, fd=3, buf=3213019456,      count=512
     syscalls__sys_exit_read     1 11624.858177924     1262 wget                  nr=3, ret=512
     skb__kfree_skb           1 11624.858878188     1262 wget                  skbaddr=3945041280,           location=3243922184, protocol=0
     skb__kfree_skb           1 11624.858945608     1262 wget                  skbaddr=3945037824,      location=3243922184, protocol=0
     irq__softirq_raise       1 11624.859020942     1262 wget                  vec=TIMER
     irq__softirq_entry       1 11624.859076935     1262 wget                  vec=TIMER
     irq__softirq_exit        1 11624.859083469     1262 wget                  vec=TIMER
     syscalls__sys_enter_read     1 11624.859167565     1262 wget                  nr=3, fd=3, buf=3077701632,      count=1024
     syscalls__sys_exit_read     1 11624.859192533     1262 wget                  nr=3, ret=471
     syscalls__sys_enter_read     1 11624.859228072     1262 wget                  nr=3, fd=3, buf=3077701632,      count=1024
     syscalls__sys_exit_read     1 11624.859233707     1262 wget                  nr=3, ret=0
     syscalls__sys_enter_read     1 11624.859573008     1262 wget                  nr=3, fd=3, buf=3213018496,      count=512
     syscalls__sys_exit_read     1 11624.859584818     1262 wget                  nr=3, ret=512
     syscalls__sys_enter_read     1 11624.859864562     1262 wget                  nr=3, fd=3, buf=3077701632,      count=1024
     syscalls__sys_exit_read     1 11624.859888770     1262 wget                  nr=3, ret=1024
     syscalls__sys_enter_read     1 11624.859935140     1262 wget                  nr=3, fd=3, buf=3077701632,      count=1024
     syscalls__sys_exit_read     1 11624.859944032     1262 wget                  nr=3, ret=1024
            </literallayout>
            That in itself isn't very useful; after all, we can accomplish
            pretty much the same thing by simply running 'perf script'
            without arguments in the same directory as the perf.data file.
        </para>

        <para>
            We can however replace the print statements in the generated
            function bodies with whatever we want, and thereby make it
            infinitely more useful.
        </para>

        <para>
            As a simple example, let's just replace the print statements in
            the function bodies with a simple function that does nothing but
            increment a per-event count. When the program is run against a
            perf.data file, each time a particular event is encountered,
            a tally is incremented for that event. For example:
            <literallayout class='monospaced'>
     def net__netif_rx(event_name, context, common_cpu,
            common_secs, common_nsecs, common_pid, common_comm,
            skbaddr, len, name):
		          inc_counts(event_name)
            </literallayout>
            Each event handler function in the generated code is modified
            to do this. For convenience, we define a common function called
            inc_counts() that each handler calls; inc_counts simply tallies
            a count for each event using the 'counts' hash, which is a
            specialized has function that does Perl-like autovivification, a
            capability that's extremely useful for kinds of multi-level
            aggregation commonly used in processing traces (see perf's
            documentation on the Python language binding for details):
            <literallayout class='monospaced'>
     counts = autodict()

     def inc_counts(event_name):
            try:
                    counts[event_name] += 1
            except TypeError:
                    counts[event_name] = 1
            </literallayout>
            Finally, at the end of the trace processing run, we want to
            print the result of all the per-event tallies. For that, we
            use the special 'trace_end()' function:
            <literallayout class='monospaced'>
     def trace_end():
            for event_name, count in counts.iteritems():
                    print "%-40s %10s\n" % (event_name, count)
            </literallayout>
            The end result is a summary of all the events recorded in the
            trace:
            <literallayout>
     skb__skb_copy_datagram_iovec                  13148
     irq__softirq_entry                             4796
     irq__irq_handler_exit                          3805
     irq__softirq_exit                              4795
     syscalls__sys_enter_write                      8990
     net__net_dev_xmit                               652
     skb__kfree_skb                                 4047
     sched__sched_wakeup                            1155
     irq__irq_handler_entry                         3804
     irq__softirq_raise                             4799
     net__net_dev_queue                              652
     syscalls__sys_enter_read                      17599
     net__netif_receive_skb                         1743
     syscalls__sys_exit_read                       17598
     net__netif_rx                                     2
     napi__napi_poll                                1877
     syscalls__sys_exit_write                       8990
            </literallayout>
            Note that this is pretty much exactly the same information we get
            from 'perf stat', which goes a little way to support the idea
            mentioned previously that given the right kind of trace data,
            higher-level profiling-type summaries can be derived from it.
        </para>

        <para>
            Documentation on using the
            <ulink url='http://linux.die.net/man/1/perf-script-python'>'perf script' python binding</ulink>.
        </para>
    </section>





</section>
</chapter>
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