rocm-systems/projects/rdc/docs/how-to/features.rst

.. meta::
  :description: documentation of the installation, configuration, and use of the ROCm Data Center tool 
  :keywords: ROCm Data Center tool, RDC, ROCm, API, reference, data type, support

.. _rdc-features:

******************************************
RDC tool feature overview
******************************************

This topic provides information related to the features of the RDC tool. 

.. figure:: ../data/features.png

    RDC components and framework for describing features


Discovery
=========

The Discovery feature enables you to locate and display information of GPUs present in the compute node.

Example:

.. code-block:: shell
  
    $ rdci discovery <host_name> -l
    2 GPUs found

.. list-table::

    * - **GPU Index**
      - **Device Information**

    * - 0 
      - Name: AMD Radeon Instinct MI50 Accelerator

    * - 1 
      - Name: AMD Radeon Instinct MI50 Accelerator


.. code-block:: shell
  
    $ rdci -l : list available GPUs
    $ rdci -u: No SSL authentication


Groups
======

This section explains the GPU and field groups features.

GPU Groups
----------

With the GPU groups feature, you can create, delete, and list logical groups of GPU.

.. code-block:: shell
  
    $ rdci group -c GPU_GROUP
    Successfully created a group with a group ID 1
 
    $ rdci group -g 1 -a 0,1
    Successfully added the GPU 0,1 to group 1
 
    $ rdci group –l
 
    1 group found


.. list-table::

    * - **Group ID**
      - **Group Name**
      - **GPU Index**

    * - 1 
      - GPU_GROUP
      - 0, 1


.. code-block:: shell
  
    $ rdci group -d 1
    Successfully removed group 1
 
    -c create; –g group id; –a add GPU index; –l list; -d delete group 


Field Groups
------------

The Field Groups feature provides you the options to create, delete, and list field groups.

.. code-block:: shell
  
    $ rdci fieldgroup -c <fgroup> -f 150,155
    Successfully created a field group with a group ID 1
 
    $ rdci fieldgroup -l
 
    1 group found


.. list-table::

    * - **Group ID**
      - **Group Name**
      - **Field IDs**

    * - 1 
      - Fgroup
      - 150, 155


.. code-block:: shell
  
    $ rdci fieldgroup -d 1
    Successfully removed field group 1
 
    rdci dmon –l
    Supported fields Ids: 
    100 RDC_FI_GPU_CLOCK:  Current GPU clock freq.
    150 RDC_FI_GPU_TEMP:  GPU temp. in milli Celsius.
    155 RDC_FI_POWER_USAGE:  Power usage in microwatts.
    203 RDC_FI_GPU_UTIL:  GPU busy percentage.
    525 RDC_FI_GPU_MEMORY_USAGE: VRAM Memory usage in bytes
    
    -c create; –g group id; –a add GPU index; –l list; -d delete group


Monitor Errors
--------------

You can define ``RDC_FI_ECC_CORRECT_TOTAL`` or ``RDC_FI_ECC_UNCORRECT_TOTAL`` field to get the RAS Error-Correcting Code (ECC) counter:

* 312 ``RDC_FI_ECC_CORRECT_TOTAL``: Accumulated correctable ECC errors
* 313 ``RDC_FI_ECC_UNCORRECT_TOTAL``: Accumulated uncorrectable ECC errors


Device Monitoring
=================

The RDC tool enables you to monitor the GPU fields.

.. code-block:: shell
  
    $ rdci dmon -f <field_group> -g <gpu_group> -c 5 -d 1000
 
 
    1 group found


.. list-table::

    * - **GPU Index**
      - **TEMP (m°C)**
      - **POWER (µW)**

    * - 0 
      - 25000
      - 520500


.. code-block:: shell
  
    rdci dmon –l
    Supported fields Ids: 
    100 RDC_FI_GPU_CLOCK:  Current GPU clock freq.
    150 RDC_FI_GPU_TEMP:  GPU temp. in milli Celsius.
    155 RDC_FI_POWER_USAGE:  Power usage in microwatts.
    203 RDC_FI_GPU_UTIL:  GPU busy percentage.
    525 RDC_FI_GPU_MEMORY_USAGE: VRAM Memory usage in bytes
    
    -e field ids; -i GPU index; -c count; -d delay; -l list; -f fieldgroup id 


Job Stats
=========

You can display GPU statistics for any given workload.

.. code-block:: shell
  
    $ rdci stats -s 2 -g 1
  Successfully started recording job 2 with a group ID 1
 
  $ rdci stats -j 2


.. list-table::

    * - **Summary**
      - **Executive Status**

    * - Start time 
      - 1586795401

    * - End time 
      - 1586795445

    * - Total execution time 
      - 44

    * - ==============
      - ==============

    * - Energy Consumed (Joules) 
      - 21682

    * - Power Usage (Watts) 
      - Max: 49 Min: 13 Avg: 34

    * - GPU Clock (MHz) 
      - Max: 1000 Min: 300 Avg: 903

    * - GPU Utilization (%) 
      - Max: 69 Min: 0 Avg: 2

    * - Max GPU Memory Used (bytes) 
      - 524320768

    * - Memory Utilization (%) 
      - Max: 12 Min: 11 Avg: 12


.. code-block:: shell
  
    $ rdci stats -x 2
    Successfully stopped recording job 2
 
    -s start recording on job id; -g group id; -j display job stats; –x stop recording. 


Job Stats Use Case
------------------

A common use case is to record GPU statistics associated with any job or workload. The following example shows how all these features can be put together for this use case:


.. figure:: ../data/features_jobs.png

    An example showing how job statistics can be recorded


rdci commands
^^^^^^^^^^^^^

.. code-block:: shell
  
    $ rdci group -c group1

    successfully created a group with a group ID 1

    $ rdci group -g 1 -a 0,1

    GPU 0,1 is added to group 1 successfully.

    rdci stats -s 123 -g 1

    job 123 recorded successfully with the group ID 

    rdci stats -x 123

    job 123 stops recording successfully 

    rdci stats -j 123

    job stats printed 


Error-Correcting Code Output
============================

In the job output, this feature prints out the Error-Correcting Code (ECC) errors while running the job.

Diagnostic
==========

You can run diagnostic on a GPU group as shown below:

.. code-block:: shell
  
    $ rdci diag -g <gpu_group>
 
    No compute process:  Pass
    Node topology check:  Pass
    GPU parameters check:  Pass
    Compute Queue ready:  Pass
    System memory check:  Pass
    =============== Diagnostic Details ==================
    No compute process:  No processes running on any devices.
    Node topology check:  No link detected.
    GPU parameters check:  GPU 0 Critical Edge temperature in range.
    Compute Queue ready:  Run binary search task on GPU 0 Pass.
    System memory check:  Max Single Allocation Memory Test for GPU 0 Pass. CPUAccessToGPUMemoryTest for GPU 0 Pass. GPUAccessToCPUMemoryTest for GPU 0 Pass.