rocm-systems/projects/rocprofiler-systems/docs/conceptual/data-collection-modes.rst

.. meta::
   :description: ROCm Systems Profiler data collection modes documentation
   :keywords: rocprof-sys, rocprofiler-systems, Omnitrace, ROCm, profiler, data collection, tracking, visualization, tool, Instinct, accelerator, AMD

**********************
Data collection modes
**********************

ROCm Systems Profiler supports several modes of recording trace and profiling data for your application.

.. note::

   For an explanation of the terms used in this topic, see
   the :doc:`ROCm Systems Profiler glossary <../reference/rocprof-sys-glossary>`.

+-----------------------------+---------------------------------------------------------+
| Mode                        | Description                                             |
+=============================+=========================================================+
| Binary Instrumentation      | Locates functions (and loops, if desired) in the binary |
|                             | and inserts snippets at the entry and exit              |
+-----------------------------+---------------------------------------------------------+
| Statistical Sampling        | Periodically pauses application at specified intervals  |
|                             | and records various metrics for the given call stack    |
+-----------------------------+---------------------------------------------------------+
| Callback APIs               | Parallelism frameworks such as ROCm, OpenMP, and Kokkos |
|                             | make callbacks into ROCm Systems Profiler to provide    |
|                             | information about the work the API is performing        |
+-----------------------------+---------------------------------------------------------+
| Dynamic Symbol Interception | Wrap function symbols defined in a position independent |
|                             | dynamic library/executable, like ``pthread_mutex_lock`` |
|                             | in ``libpthread.so`` or ``MPI_Init`` in the MPI library |
+-----------------------------+---------------------------------------------------------+
| User API                    | User-defined regions and controls for User API ROCm     |
|                             | Systems Profiler                                        |
+-----------------------------+---------------------------------------------------------+

The two most generic and important modes are binary instrumentation and statistical sampling.
It is important to understand their advantages and disadvantages.
Binary instrumentation and statistical sampling can be performed with the ``rocprof-sys-instrument``
executable. For statistical sampling, it's highly recommended to use the
``rocprof-sys-sample`` executable instead if binary instrumentation isn't required or needed.
Callback APIs and dynamic symbol interception can be utilized with either tool.

Binary instrumentation
-----------------------------------

Binary instrumentation lets you record deterministic measurements for
every single invocation of a given function.
Binary instrumentation effectively adds instructions to the target application to
collect the required information. It therefore has the potential to cause performance
changes which might, in some cases, lead to inaccurate results. The effect depends on
the information being collected and which features are activated in ROCm Systems Profiler.
For example, collecting only the wall-clock timing data
has less of an effect than collecting the wall-clock timing, CPU-clock timing,
memory usage, cache-misses, and number of instructions that were run. Similarly,
collecting a flat profile has less overhead than a hierarchical profile
and collecting a trace OR a profile has less overhead than collecting a
trace AND a profile.

In ROCm Systems Profiler, the primary heuristic for controlling the overhead with binary
instrumentation is the minimum number of instructions for selecting functions
for instrumentation.

Statistical sampling
-----------------------------------

Statistical call-stack sampling periodically interrupts the application at
regular intervals using operating system interrupts.
Sampling is typically less numerically accurate and specific, but the
target program runs at nearly full speed.
In contrast to the data derived from binary instrumentation, the resulting
data is not exact but is instead a statistical approximation.
However, sampling often provides a more accurate picture of the application
execution because it is less intrusive to the target application and has fewer
side effects on memory caches or instruction decoding pipelines. Furthermore,
because sampling does not affect the execution speed as much, is it
relatively immune to over-evaluating the cost of small, frequently called
functions or "tight" loops.

In ROCm Systems Profiler, the overhead for statistical sampling depends on the
sampling rate and whether the samples are taken with respect to the CPU time
and/or real time.

Binary instrumentation vs. statistical sampling example
-------------------------------------------------------

Consider the following code:

.. code-block:: c++

   long fib(long n)
   {
        if(n < 2) return n;
        return fib(n - 1) + fib(n - 2);
   }

   void run(long n)
   {
        long result = fib(n);
        printf("[%li] fibonacci(%li) = %li\n", i, n, result);
   }

   int main(int argc, char** argv)
   {
        long nfib = 30;
        long nitr = 10;
        if(argc > 1) nfib = atol(argv[1]);
        if(argc > 2) nitr = atol(argv[2]);

        for(long i = 0; i < nitr; ++i)
            run(nfib);

        return 0;
   }

Binary instrumentation of the ``fib`` function will record **every single invocation**
of the function. For a very small function
such as ``fib``, this results in **significant** overhead since this simple function
takes about 20 instructions, whereas the entry and
exit snippets are ~1024 instructions. Therefore, you generally want to avoid
instrumenting functions where the instrumented function has significantly fewer
instructions than entry and exit instrumentation. (Note that many of the
instructions in entry and exit functions are either logging functions or
depend on the runtime settings and thus might never run). However,
due to the number of potential instructions in the entry and exit snippets,
the default behavior of ``rocprof-sys-instrument`` is to only instrument functions
which contain at least 1024 instructions.

However, recording every single invocation of the function can be extremely
useful for detecting anomalies, such as profiles that show minimum or maximum values much smaller or larger
than the average or a high standard deviation. In this case, the traces help you
identify exactly when and where those instances deviated from the norm.
Compare the level of detail in the following traces. In the top image,
every instance of the ``fib`` function is instrumented, while in the bottom image,
the ``fib`` call-stack is derived via sampling.

Binary instrumentation of the Fibonacci function
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. image:: ../data/fibonacci-instrumented.png
   :alt: Visualization of the output of a binary instrumentation of the Fibonacci function

Statistical sampling of the Fibonacci function
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. image:: ../data/fibonacci-sampling.png
   :alt: Visualization of the output of a statistical sample of the Fibonacci function

Overview of profiling modes
----------------------------

ROCm Systems Profiler provides several complementary profiling approaches that can be used independently or in combination. Profiling modes are controlled via the ``ROCPROFSYS_MODE`` environment variable, which determines the active backends and features.

Available values for ``ROCPROFSYS_MODE``: `trace`, `sampling`, `causal`, and `coverage`.

Primary collection modes
^^^^^^^^^^^^^^^^^^^^^^^^

.. list-table::
   :header-rows: 1
   :widths: 25 75

   * - **Mode**
     - **Purpose**
   * - **Trace mode**
     - Event tracing
   * - **Profile mode**
     - High-level summary profiles
   * - **Sampling mode**
     - Statistical call-stack sampling
   * - **Causal mode**
     - Performance impact analysis
   * - **Coverage mode**
     - Code coverage analysis

Trace mode (default)
^^^^^^^^^^^^^^^^^^^^^^^^

Tracing mode generates comprehensive, deterministic traces of every event and measurement during application execution. This mode can be enabled using ``ROCPROFSYS_TRACE=true``, ``ROCPROFSYS_MODE=trace``, or by using the ``--trace`` / ``-T`` CLI flag.

ROCm Systems Profiler provides two tracing implementations:

- **Cached Mode (default)**: By default, when tracing is enabled, ROCm Systems Profiler uses deferred trace generation with minimal runtime overhead. Trace data is buffered during execution and written after the application completes, significantly reducing performance impact during profiling.

- **Legacy Mode**: ``ROCPROFSYS_TRACE_LEGACY=true`` or ``--trace-legacy`` / ``-L`` enables direct mode where trace data is written immediately during execution. This mode provides real-time trace generation but has higher runtime overhead compared to cached mode.

Additional configuration options to control the tracing behavior include:

- ``ROCPROFSYS_TRACE_DELAY`` (``--trace-wait``): Delay before starting trace collection (in seconds).
- ``ROCPROFSYS_TRACE_DURATION`` (``--trace-duration``): Duration of trace collection (in seconds).
- ``ROCPROFSYS_TRACE_PERIODS`` (``--trace-periods``): Specifies multiple delay/duration periods in the format ``<DELAY>:<DURATION>``, ``<DELAY>:<DURATION>:<REPEAT>``, or ``<DELAY>:<DURATION>:<REPEAT>:<CLOCK_ID>``.
- ``ROCPROFSYS_TRACE_PERIOD_CLOCK_ID`` (``--trace-clock-id``): Clock type for timing, such as ``realtime``, ``monotonic``, ``cputime``.

Profile mode
^^^^^^^^^^^^^^^^^^^^^^^^

Profile mode generates high-level summary profiles with statistical aggregations (mean, min, max, stddev). This mode can be enabled using ``ROCPROFSYS_PROFILE=true``. This mode uses the **Timemory** backend. When tracing is enabled, profiling is turned off by default, and vice versa. However, both modes can be turned on at the same time.

By default, only wall-clock timing is collected. Additional metrics can be configured using ``ROCPROFSYS_TIMEMORY_COMPONENTS``, which enables hardware counters (via PAPI), CPU, memory, and system metrics. To view the available components, use: ``rocprof-sys-avail --components --description``.

Profile types:

- **Flat Profile** (``--flat-profile``): Aggregated metrics per function across all contexts.
- **Hierarchical Profile** (``--profile``): Metrics organized by call-stack context.

.. tip:: Start with a flat profile to identify high-impact functions, then use a hierarchical profile to analyze critical paths.

Sampling mode
^^^^^^^^^^^^^^^^^^^^^^^^

Sampling uses statistical call-stack sampling through periodic software interrupts per thread, as described in :doc:`Sampling the call stack <../how-to/sampling-call-stack>`.

Sampling types:

1. **CPU-Time sampling** (default)

* Enabled using ``ROCPROFSYS_SAMPLING_CPUTIME=ON`` or ``--cputime`` (rocprof-sys-sample), ``--sample-cputime`` (rocprof-sys-run). The sampling can be controlled using:

  * ``ROCPROFSYS_SAMPLING_CPUTIME_FREQ``
  * ``ROCPROFSYS_SAMPLING_CPUTIME_DELAY``
  * ``ROCPROFSYS_SAMPLING_CPUTIME_SIGNAL``

2. **Real-Time sampling**

* Enabled using ``ROCPROFSYS_SAMPLING_REALTIME=ON`` or ``--realtime`` (rocprof-sys-sample), ``--sample-realtime`` (rocprof-sys-run). The sampling can be controlled using:

  * ``ROCPROFSYS_SAMPLING_REALTIME_FREQ``
  * ``ROCPROFSYS_SAMPLING_REALTIME_DELAY``
  * ``ROCPROFSYS_SAMPLING_REALTIME_SIGNAL``

3. **Overflow sampling**

* Enabled using ``ROCPROFSYS_SAMPLING_OVERFLOW=ON`` or ``--sample-overflow`` (rocprof-sys-run). It requires Linux ``perf`` support (``/proc/sys/kernel/perf_event_paranoid <= 2``) as described in :ref:`rocprof-sys_papi_events`. The sampling can be controlled using:

  * ``ROCPROFSYS_SAMPLING_OVERFLOW_FREQ``
  * ``ROCPROFSYS_SAMPLING_OVERFLOW_EVENT``
  * ``ROCPROFSYS_SAMPLING_OVERFLOW_SIGNAL``
  * ``ROCPROFSYS_SAMPLING_OVERFLOW_TIDS``

4. **Process sampling**

* Enabled using ``ROCPROFSYS_USE_PROCESS_SAMPLING=ON`` (default ON). The sampling can be controlled using:

  * ``ROCPROFSYS_PROCESS_SAMPLING_FREQ``
  * ``ROCPROFSYS_SAMPLING_CPUS``
  * ``ROCPROFSYS_SAMPLING_GPUS``

.. note:: If sampling is enabled but no specific type is selected, CPU-time sampling is used by default.

To enable sampling:

1. Use ``rocprof-sys-sample`` (auto-enables sampling).
2. Set ``ROCPROFSYS_USE_SAMPLING=ON`` and ``ROCPROFSYS_MODE=sampling``.
3. Use ``-S`` or ``--sample`` with ``rocprof-sys-run``.
4. Use ``-M sampling`` or ``--mode sampling`` with ``rocprof-sys-instrument``. Use of ``rocprof-sys-sample`` is **recommended** over ``rocprof-sys-instrument -M sampling`` when binary instrumentation is not necessary. For more details, see :doc:`Sampling the call stack <../how-to/sampling-call-stack>`.

Causal mode
^^^^^^^^^^^^^^^^^^^^^^^^
Causal profiling quantifies the potential impact of optimizations in parallel code and predicts where efforts should be focused as described in :doc:`Performing causal profiling <../how-to/performing-causal-profiling>`.
This mode can be enabled using: ``ROCPROFSYS_USE_CAUSAL=true`` or ``ROCPROFSYS_MODE=causal``.

Coverage mode
^^^^^^^^^^^^^^^^^^^^^^^^

Coverage mode tracks which parts of your code are executed during a run. It uses binary instrumentation to record function and/or basic block execution. This mode can be enabled using: ``rocprof-sys-instrument -M coverage``.

Granularity options:

- Function-level: ``--coverage=function`` (``CODECOV_FUNCTION``)
- Basic block-level: ``--coverage=basic_block`` (``CODECOV_BASIC_BLOCK``)

.. note:: Coverage mode disables several other features and all other modes to reduce overhead.