[Docs] Update using-pc-sampling (#157)
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@@ -42,5 +42,4 @@
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# VSCode Workspaces
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*.code-workspace
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rocprofiler-sdk-build/CMakeCache.txt
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/rocprofiler-sdk-build
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@@ -63,7 +63,7 @@ To check the firmware versions, use:
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.. code-block:: bash
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# To check PSP TOS Firmware:
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# To check PSP TOS Firmware:
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sudo cat /sys/kernel/debug/dri/0/amdgpu_firmware_info | grep SOS
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# To check MEC Firmware:
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@@ -81,6 +81,8 @@ This generates two files, ``agent_info.csv`` and ``pc_sampling_host_trap.csv``.
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Here are the contents of ``pc_sampling_host_trap.csv`` file generated for MatrixTranspose sample application:
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.. _pc_sampling_host_trap:
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.. csv-table:: PC sampling host trap
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:file: /data/pc_sampling_host_trap.csv
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:widths: 20,10,10,10,10,20
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@@ -201,50 +203,53 @@ The preceding command generates a JSON file with the comprehensive output. Here
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For description of the fields in the JSON output, see :ref:`output-file-fields`.
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An Arbitrary Host-Trap PC Sampling Skid
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===============================================
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Host-trap PC sampling and arbitrary sampling skid
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==================================================
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Host-Trap PC sampling is a software-based technique that utilizes a background kernel thread
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to periodically interrupt running waves in order to capture the program counter (PC).
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Host-trap PC sampling is a software-based technique that utilizes a background kernel thread
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to periodically interrupt running waves to capture the program counter (PC).
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This method is effective for gathering performance data without requiring specialized hardware
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to snapshot the waves. However, it has limitations due to the potential delay between
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when a wave receives an interrupt and when it processes the interrupt to capture the PC.
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This delay can lead to a sampling skid, where the PC samples may be attributed to instructions
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to snapshot the waves. However, this method has certain limitations due to the potential delay between
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receiving and processing the interrupt by the wave to capture the PC.
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This delay can lead to a sampling skid, where the PC samples might be attributed to the instructions
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that are up to two instructions away from the actual source of latency.
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This results in a non-precise intra-kernel sampling method.
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When analyzing an application profile generated by host-trap PC sampling,
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developers should consider not only the reported most costly instruction but
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it is important to consider not only the costliest reported instruction but
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also the instructions immediately preceding or following it.
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If the costly instruction is near a branch instruction, it is important
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to also consider the instruction targeted by the branch and the one immediately following it.
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If the costly instruction is near a branch instruction, it is important
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to consider the instruction targeted by the branch and the one immediately following it as well.
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To address the limitations of host-trap sampling, the hardware-based stochastic PC sampling method
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has been developed. This method provides precise intra-kernel sampling with zero sampling skid,
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offering more accurate performance insights.
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It is important to note that the skid issue inherent in host-trap PC sampling will not be resolved
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in its current form. Therefore, users are encouraged to adopt stochastic PC sampling,
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starting with the GFX942 architecture, to achieve more precise performance profiling.
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It is important to note that the skid issue inherent in host-trap PC sampling is not likely to be resolved
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in its current form. Therefore, to achieve more precise performance profiling, it is recommended to adopt stochastic PC sampling starting with the gfx942 architecture.
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Hardware-Based (Stochastic) PC Sampling Method
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.. note::
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Host-trap PC sampling is supported on AMD Instinct MI200, MI300, MI325, MI350, and MI355.
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Hardware-based (stochastic) PC sampling method
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===============================================
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The new ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` has been introduced for gfx942 architecture.
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It employs a specific hardware for probing waves actively running on GPU.
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Beside information already provided with ``ROCPROFILER_PC_SAMPLING_METHOD_HOST_TRAP`` useful for determining hot-spots within the kernel,
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it delivers additional information that tells whether a sampled wave issued an instruction represented with particular PC.
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If not, it provides the reason for not issuing the instruction (stall reason).
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This type of information is particularly useful for understanding stalls during the kernel execution.
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The ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` method has been introduced for the gfx942 architecture.
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It employs a specific hardware for probing waves actively running on the GPU.
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Besides the information already provided with ``ROCPROFILER_PC_SAMPLING_METHOD_HOST_TRAP`` useful for
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determining hotspots within the kernel, this method delivers additional information, which helps to determine
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whether a sampled wave issued an instruction represented with the specified PC.
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If not, this method provides the reason for not issuing the instruction (stall reason).
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Such information is particularly useful for understanding stalls during kernel execution.
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To use this method on gfx942, we recommend listing available PC sampling configurations to verify if the latest ROCm stack is installed
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on the system by running:
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To use this method on gfx942, it is recommended to list available PC sampling configurations to verify if the latest ROCm stack is installed on the system using:
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.. code-block:: bash
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rocprofv3 -L
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Output similar to the following indicates that the ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` method is available:
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An output similar to the following indicates that the ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` method is available:
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.. code-block:: bash
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@@ -257,22 +262,30 @@ Output similar to the following indicates that the ``ROCPROFILER_PC_SAMPLING_MET
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Max_Interval :2147483648
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Flags :interval pow2
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Please note that on gfx942, `ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC` requires intervals to be specified in cycles, whose values are powers of 2
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.. note::
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To profile a gfx942 accelerated application with ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` PC sampling, one can use the following command:
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On gfx942, ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` requires intervals to be specified in cycles with values as powers of 2.
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To profile an application with ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` PC sampling enabled on gfx942, use:
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.. code-block:: bash
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rocprofv3 --pc-sampling-beta-enabled --pc-sampling-method stochastic --pc-sampling-unit cycles --pc-sampling-interval 1048576 --output-format csv, json -- <application_path>
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The previous command serializes samples in both CSV and JSON output formats in the ``pc_sampling_stochastic.csv`` and ``out_results.json`` files, respectively.
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The preceding command serializes samples in both CSV and JSON output formats in the ``pc_sampling_stochastic.csv`` and ``out_results.json`` files, respectively.
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Comparing the ``pc_sampling_stochastic.csv`` to ``pc_sampling_host_trap`` from previous section, one can notice that the ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` method
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generates additional fields:
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- ``Wave_Issued_Instruction``: Indicates whether the wave issued an instruction (value 1) represented with particular PC or not (value 0)
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- ``Instruction_Type``: If the value of ``Wave_Issued_Instruction`` is 1, this fields indicates the type of the issued instruction. Otherwise, this fields irrelevant.
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- ``Stall_Reason``: If the value of ``Wave_Issued_Instruction`` is 0, this fields indicates the reason for not issuing the instruction (stall reason). Otherwise, this field is irrelevant.
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- ``Wave_Count``: Total number of waves actively running on a compute unit when the sample was generated.
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On comparing the :ref:`pc_sampling_stochastic.csv <pc_sampling_stochastic>` to :ref:`pc_sampling_host_trap.csv <pc_sampling_host_trap>`, you can notice that the ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` method
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generates the following additional fields:
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- ``Wave_Issued_Instruction``: Indicates whether the wave issued an instruction represented with the specified PC. Value = 1 for yes and 0 for no.
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- ``Instruction_Type``: If the value of ``Wave_Issued_Instruction`` is 1, this field indicates the type of the issued instruction. Otherwise, this field remains irrelevant.
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- ``Stall_Reason``: If the value of ``Wave_Issued_Instruction`` is 0, this field indicates the reason for not issuing the instruction (stall reason). Otherwise, this field remains irrelevant.
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- ``Wave_Count``: Total number of waves actively running on a compute unit when the sample is generated.
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.. _pc_sampling_stochastic:
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.. csv-table:: PC sampling stochastic with debug symbols
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:file: /data/pc_sampling_stochastic_debug.csv
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@@ -280,7 +293,8 @@ generates additional fields:
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:header-rows: 1
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Similarly, ``ROCPROFILER_PC_SAMPLING_METHOD_STOCHASTIC`` method delivers additional information to every sample in the JSON output.
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The following snippet shows one sample from ``out_results.json`` file.
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Here is a ``out_results.json`` file sample:
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.. code-block:: text
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@@ -351,7 +365,10 @@ The following snippet shows one sample from ``out_results.json`` file.
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},
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Fields starting with ``arb_state_`` are of particular interest as they indicate the state of the arbiter at the time of sampling.
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Namely, ``arb_state_issue_`` fields indicate what type of instructions arbiter issued at the time of sampling.
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On the other hand, ``arb_state_stall_`` fields indicate what type of instructions were stalled at the time of sampling.
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For example, ``arb_state_issue_`` fields indicate the type of instructions issued by the arbiter at the time of sampling.
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On the other hand, ``arb_state_stall_`` fields indicate the type of instructions stalled at the time of sampling.
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This information is useful for understanding how many instructions per cycle (IPC) are issued.
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.. note::
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The stochastic PC sampling is supported on AMD Instinct MI300, MI325, MI350, and MI355.
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