Tracing and Logging

Starting with version 2014.1, there are three tracing mechanisms available in LITMUS^RT, which are exposed as four sets of device files:

1. litmus_log: This trace contains text messages (created with the TRACE() macro, see debug_trace.h) that convey information useful for debugging. There is one global litmus_log buffer for the whole system. The litmus_log facility is essentially a replacement for printk(), which cannot be invoked from scheduling code without risking deadlock. Debug tracing must be enabled at compile time. Note that debug tracing creates significant overhead because string formatting takes place.

2. ft_cpu_traceX and ft_msg_traceX: These per-CPU traces (X denotes the CPU) contain binary-encoded time stamps. They are used for overhead tracing. There are two buffers for each processor to enable processor-local tracing. The "ft" stands for Feather-Trace. Feather-Trace is designed to create negligible overhead when event sources are disabled, and to incur only low overhead when recording time stamps. The trace ft_cpu_traceX contains time stamps of CPU-local scheduling events (such as scheduler invocation, context switches, etc.). The ft_msg_traceX trace contains timestamps related to inter-processor events (primarily rescheduling IPIs).

3. sched_traceX: This trace contains binary-encoded scheduling event information, e.g., an event can be recorded whenever a task got scheduled, a job was released, a job completed, etc. There is one sched_traceX buffer per processor (again, the X denotes the CPU). sched_trace is based on Feather-Trace and hence also incurs only little overhead when event sources are disabled.

Accessing Trace Buffers

litmus_log functionality is provided through the kernel's misc driver interface. The other two traces are exported to user space through standard character device drivers.

On systems with default udev rules, the devices are created in the /dev/litmus/ directory:

• The litmus_log trace is exported as /dev/litmus/log.

• The ft_cpu_traceX traces are exported as /dev/litmus/ft_cpu_trace0, /dev/litmus/ft_cpu_trace1, etc.

• The ft_msg_traceX traces are exported as /dev/litmus/ft_msg_trace0, /dev/litmus/ft_msg_trace1, etc.

• The sched_trace traces are exported as /dev/litmus/sched_trace0, /dev/litmus/sched_trace1, etc.

Recording Debug Traces

The litmus_log buffer can be read by simply opening the file and reading its contents:

cat /dev/litmus/log > my_debug_log

Kill the cat process to stop recording debug messages.

No post-processing is required since the debug messages are plain text. However, note that messages may appear in an order that differs from the sequence of events at runtime. If order is important (for example when debugging race conditions), then recorded messages can be sorted offline with the help of the sequence number at the start of each recorded message.

Example:

sort -n my_debug_log > my_sorted_debug_log

Hint: It's possible to use netcat(1) to send the debug messages to another host to avoid filesystem activity.

Hint: If cat is being starved, you can make it a real-time task itself with rt_launch from liblitmus.

Recording Overhead Traces

Feather-Trace allows for much more fine-grained tracing than the simple debug stream realized by litmus_log and hence requires special-purpose tools to be used. These tools are available as part of the ft_tools package (see list of repositories).

Feather-Trace events can be enabled on a per-event basis. Each event is identified by a unique 32-bit ID. Initially, when the device buffer is not being accessed by any user space programs (i.e., when the device driver is unused), all events are disabled. Events can be enabled (and subsequently disabled again) by writing binary commands to the buffer device file. Once events are enabled they can generate trace records, which are stored in the trace buffer. User space programs can obtain these records by reading from the device file. Reading a trace record removes it from the buffer, i.e., each record can be read exactly once. Records should be consumed shortly after they were created since buffer capacity is limited.

The tool ftcat, which is part of the ft_tools package (see above), automates the process of enabling events and retrieving trace records. It takes the name of the ft_trace device file and the events of interest as arguments:

ftcat <ft device> <event 1> <event 2> <event 3> ...

The tool enables the specified events and copies all recorded events to stdout.

Events can be specified either by their ID (see include/litmus/trace.h in the kernel directory for a list of time stamp generating events) or by their symbolic name. The following symbolic names are recognized:

• SCHED_START, SCHED_END: Used to measure the time spent to make a scheduling decision.

• CXS_START, CXS_END: Used to record the time spent to make a context switch.

• SCHED2_START, SCHED2_END: Used to measure the time spent to perform post-context-switch cleanup and management activities. This is part of the scheduling overhead but for technical reasons cannot be measured as part of the interval [SCHED_START, SCHED_END].

• TICK_START, TICK_END: Used to measure the overhead incurred due to Linux's periodic system tick. As of LITMUS^RT 2014.2, no LITMUS^RT-specific activity takes place during a system tick.

• QUANTUM_BOUDARY_START, QUANTUM_BOUNDARY_END`: Used to measure the overhead incurred in quantum-driven plugins (e.g., PFAIR) at the start of each quantum. Available since LITMUS^RT 2014.2.

• PLUGIN_SCHED_START, PLUGIN_SCHED_END: Like [SCHED_START, SCHED_END], but only measures the time spent by the active scheduling plugin. There is no equivalent SCHED2 counterpart because the scheduling plugins do not directly contribute to the SCHED2 overhead.

• RELEASE_START, RELEASE_END: Used to measure the time spent to enqueue a newly-released job in a ready queue.

• RELEASE_LATENCY: Used to measure the difference between when a timer should have fired, and when it actually did fire. In contrast to all other time stamps, this overhead is directly measured in nanoseconds (and not in processor cycles as the other overheads).

For example, the following command can be used to store the length of context switches and scheduling decisions in the file my_trace.

$ ftcat /dev/litmus/ft_cpu_trace0 CXS_START CXS_END SCHED_START SCHED_END SCHED2_START SCHED2_END > my_trace_of_scheduling_events_on_cpu0

The tracing can be stopped by interrupting ftcat with ^C or by sending SIGTERM with kill(1).

To record IPI timestamps, use the following command.

$  ftcat /dev/litmus/ft_msg_trace1 SEND_RESCHED_START SEND_RESCHED_END  > my_trace_of_IPIs_received_by_cpu1

To record all overheads on all CPUs, one must start two ftcat instances for each ${CPU}: one to record /dev/litmus/ft_cpu_trace${CPU} and one to record /dev/litmus/ft_msg_trace${CPU}. This is best automated with a script.

Note that all overhead traces are stored in the byte order of the host.

Post-Processing Overhead Traces

The binary event stream recorded by ftcat is of course of limited direct use—the data has yet to be exported for analysis. This can be achieved with the tool ft2csv, which is also part of the ft_tools package.

As the name suggests, ft2csv extracts intervals defined by pairs of time stamps in a recorded trace and displays them as comma-separated values (CSV). It takes the name of an overhead trace and one start event as arguments:

ft2csv <start event> <overhead trace>

Events are specified in the same way as with ftcat. For example, the following command can be used to print the context-switch lengths that were recorded in the example above to stdout.

$ ft2csv CXS_START my_trace_of_scheduling_events_on_cpu0
2397634444579592, 2397634444583328, 3736
2397634477323130, 2397634477326686, 3556
2397634477346366, 2397634477348986, 2620
2397634611910924, 2397634611914348, 3424
...

For each event, the start time (in clock cycles) is given in the first column, the end time is given in the second column, and the length is given in the third column (again, in cycles).

ft2csv accepts a few options that affect how events are filtered. By default, events that do not involve real-time tasks are ignored. This can be changed by specifying the -b option. If one happens to be processing output on a little-endian host that was produced on a big-endian host then the -e option can come in handy.

Once the recorded overheads have been exported to CSV files they can be easily analyzed with tools such as Python's csv module, Octave, or Matlab.

One can either analyze the trace from each CPU individually, or just concatenate all traces (e.g., cat my_trace_of_scheduling_events_on_cpu0 my_trace_of_scheduling_events_on_cpu1 ... > all_events) and then run ft2csv on the resulting set of all events.

Recording Scheduling Traces

Scheduling traces are also recorded using Feather-Trace. However, a different binary format is used. The definition and an explanation of the format can be found in the file include/litmus/sched_trace.h (in the kernel directory).

Since sched_trace uses per-processor buffers several ftcat instances have to be launched. The ft_tools package includes a wrapper script called st_trace that automates this setup procedure. st_trace accepts a tag as the only argument. The tag is used to assign a unique name to the trace files.

The following example illustrates how st_trace is used with the tag global-exp.

$ st_trace global-exp
CPU 0: 8204 > st-global-exp-0.bin [0]
CPU 1: 8205 > st-global-exp-1.bin [0]
CPU 2: 8206 > st-global-exp-2.bin [0]
CPU 3: 8207 > st-global-exp-3.bin [0]
Press Enter to end tracing... # enter pressed

Disabling 9 events.
Disabling 9 events.
Disabling 9 events.
Disabling 9 events.
/home/litmus/log0: 1234 bytes read.
/home/litmus/log1: 1234 bytes read.
/home/litmus/log2: 1234 bytes read.
/home/litmus/log3: 1234 bytes read.

Note that st_trace may have to be modified to change the default sched_trace device locations and the ftcat binary.

Hint: The dummy real-time task rtspin (distributed as part of the liblitmus package) may be useful when studying/testing the behavior of a scheduler plugin.

Recorded scheduling traces can be analyzed with Unit-Trace.

Concluding Remarks

If you have any questions, please ask for help on the mailing list.