mendevi.models.power_cores.PowerCores¶

class mendevi.models.power_cores.PowerCores[source]¶

Affine model to predict the power from the core utilisation.

With \(P_{static}\) and \(P_{core}\) two hyperparameters specific to each machine, but independent of the programme being executed.

Examples¶

>>> from mendevi.models.power_cores import PowerCores
>>> model = PowerCores()
>>> model.fit("<multithread.db>")
>>> model.predict(["paradoxe-32.rennes.grid5000.fr"], [0.0])
>>>

Initialise the model.

Parameters¶

titlestr, optional: The model title.
sourcesstr: All sources for the model, the conference paper, the authors, etc.
input_labelslist[str]: The name of all input parameters. The possibles values are :py:cst:`mendevi.plot.axis.Name`.
output_labelslist[str]: The name of all output parameters. The possibles values are :py:cst:`mendevi.plot.axis.Name`.
parametersobject, optional: The learnable parameters for regressive models.