This guide will show you how to quickly start running workloads using Workload Automation 2.



This is a quick summary. For more detailed instructions, please see the Installation section.

Make sure you have Python 2.7 and a recent Android SDK with API level 18 or above installed on your system. A complete install of the Android SDK is required, as WA uses a number of its utilities, not just adb. For the SDK, make sure that either ANDROID_HOME environment variable is set, or that adb is in your PATH.


If you plan to run Workload Automation on Linux devices only, SSH is required, and Android SDK is optional if you wish to run WA on Android devices at a later time.

However, you would be starting off with a limited number of workloads that will run on Linux devices.

In addition to the base Python 2.7 install, you will also need to have pip (Python’s package manager) installed as well. This is usually a separate package.

Once you have those, you can install WA with:

sudo -H pip install wlauto

This will install Workload Automation on your system, along with its mandatory dependencies.

(Optional) Verify installation

Once the tarball has been installed, try executing

wa -h

You should see a help message outlining available subcommands.

(Optional) APK files

A large number of WA workloads are installed as APK files. These cannot be distributed with WA and so you will need to obtain those separately.

For more details, please see the Installation section.

Configure Your Device

Locate the device configuration file, config.py, under the ~/.workload_automation directory. Then adjust the device configuration settings accordingly to the device you are using.


By default, the device is set to ‘generic_android’. WA is configured to work with a generic Android device through adb. If you only have one device listed when you execute adb devices, and your device has a standard Android configuration, then no extra configuration is required.

However, if your device is connected via network, you will have to manually execute adb connect <device ip> so that it appears in the device listing.

If you have multiple devices connected, you will need to tell WA which one you want it to use. You can do that by setting adb_name in device_config section.

# ...

device_config = dict(
        adb_name = 'abcdef0123456789',
        # ...

# ...


First, set the device to ‘generic_linux’

# ...
  device = 'generic_linux'
# ...

Find the device_config section and add these parameters

# ...

device_config = dict(
        host = '',
        username = 'root',
        password = 'password'
        # ...

# ...


  • Host is the IP of your target Linux device
  • Username is the user for the device
  • Password is the password for the device

Enabling and Disabling Instrumentation

Some instrumentation tools are enabled after your initial install of WA.


Some Linux devices may not be able to run certain instruments provided by WA (e.g. cpufreq is disabled or unsupported by the device).

As a start, keep the ‘execution_time’ instrument enabled while commenting out the rest to disable them.

# ...

Instrumentation = [
        # Records the time it took to run the workload

        # Collects /proc/interrupts before and after execution and does a diff.
        # 'interrupts',

        # Collects the contents of/sys/devices/system/cpu before and after execution and does a diff.
        # 'cpufreq',

        # ...

This should give you basic functionality. If you are working with a development board or you need some advanced functionality (e.g. big.LITTLE tuning parameters), additional configuration may be required. Please see the Setting Up A Device section for more details.

Running Your First Workload

The simplest way to run a workload is to specify it as a parameter to WA run sub-command:

wa run dhrystone

You will see INFO output from WA as it executes each stage of the run. A completed run output should look something like this:

INFO     Initializing
INFO     Running workloads
INFO     Connecting to device
INFO     Initializing device
INFO     Running workload 1 dhrystone (iteration 1)
INFO            Setting up
INFO            Executing
INFO            Processing result
INFO            Tearing down
INFO     Processing overall results
INFO     Status available in wa_output/status.txt
INFO     Done.
INFO     Ran a total of 1 iterations: 1 OK
INFO     Results can be found in wa_output

Once the run has completed, you will find a directory called wa_output in the location where you have invoked wa run. Within this directory, you will find a “results.csv” file which will contain results obtained for dhrystone, as well as a “run.log” file containing detailed log output for the run. You will also find a sub-directory called ‘drystone_1_1’ that contains the results for that iteration. Finally, you will find a copy of the agenda file in the wa_output/__meta subdirectory. The contents of iteration-specific subdirectories will vary from workload to workload, and, along with the contents of the main output directory, will depend on the instrumentation and result processors that were enabled for that run.

The run sub-command takes a number of options that control its behavior, you can view those by executing wa run -h. Please see the Commands section for details.

Create an Agenda

Simply running a single workload is normally of little use. Typically, you would want to specify several workloads, setup the device state and, possibly, enable additional instrumentation. To do this, you would need to create an “agenda” for the run that outlines everything you want WA to do.

Agendas are written using YAML markup language. A simple agenda might look like this:

        instrumentation: [~execution_time]
        result_processors: [json]
        iterations: 2
        - memcpy
        - name: dhrystone
                mloops: 5
                threads: 1

This agenda

  • Specifies two workloads: memcpy and dhrystone.
  • Specifies that dhrystone should run in one thread and execute five million loops.
  • Specifies that each of the two workloads should be run twice.
  • Enables json result processor, in addition to the result processors enabled in the config.py.
  • Disables execution_time instrument, if it is enabled in the config.py

An agenda can be created in a text editor and saved as a YAML file. Please make note of where you have saved the agenda.

Please see Agenda section for more options.


These examples show some useful options with the wa run command.

To run your own agenda:

wa run <path/to/agenda> (e.g. wa run ~/myagenda.yaml)

To redirect the output to a different directory other than wa_output:

wa run dhrystone -d my_output_directory

To use a different config.py file:

wa run -c myconfig.py dhrystone

To use the same output directory but override existing contents to store new dhrystone results:

wa run -f dhrystone

To display verbose output while running memcpy:

wa run --verbose memcpy


If you have installed Workload Automation via pip, then run this command to uninstall it:

sudo pip uninstall wlauto


It will not remove any user configuration (e.g. the ~/.workload_automation directory).


To upgrade Workload Automation to the latest version via pip, run:

sudo pip install --upgrade --no-deps wlauto