Kenning measurements¶

Kenning measurements are a set of information describing the compilation and evaluation process happening in Kenning.

They contain such information as:

• classes used to construct the optimization/runtime pipeline, along with their parameters,

• the JSON scenario used in the run,

• the command used to run the scenario,

• versions of the Python modules used,

• performance measurements, such as CPU usage, GPU usage,

• quality measurements, such as predictions, ground truth, confusion matrix

All information is stored in JSON format.

Performance metrics¶

While quality measurements are problem-specific (collected in the evaluate method of the Dataset class), performance metrics are common across devices and applications.

Metrics are collected with a certain prefix <prefix>, indicating the scope of computations. There are:

• <prefix>_timestamp - gives a timestamp for measurement collection in seconds.

• <prefix>_cpus_percent - gives per-core CPU utilization in % in a form of a list of lists. They are % of per-CPU usages for every timestamp.

• <prefix>_mem_percent - gives overall memory usage in %.

• <prefix>_gpu_utilization - gives overall GPU utilization in % (only works on platforms with NVIDIA GPUs and NVIDIA Jetson embedded devices).

• <prefix>_gpu_mem_utilization - gives GPU memory utilization in % (only works on platforms with NVIDIA GPUs and NVIDIA Jetson embedded devices).