Power down workload estimation
AssigneeMicron Technology, Inc.
InventorsDavid A. Palmer, Jonathan S. Parry, Reshmi Basu
Life of this patent
Estimating the term…
Abstract
Apparatuses and methods can be related power down workload estimations using artificial neural networks. Workload estimation can include predicting a duration of a subsequent power down event of the memory device. A quantity of maintenance operations to be performed on the memory device, may be predicted based on the predicted duration of the subsequent power down event, when the memory device is powered on after the subsequent power down event using an artificial neural network. The quantity of maintenance operations may be performed on the memory device prior to the subsequent power down event of the memory device.
Claims20
An apparatus, comprising:
- a memory device;
- a processing device coupled to the memory device and configured to:
- predict a duration of a subsequent power down event of the memory device;
- predict a quantity of maintenance operations to be performed on the memory device based on the predicted duration of the subsequent power down event when the memory device is powered on after the subsequent power down event using an artificial neural network (ANN);
- and
- perform the quantity of maintenance operations on the memory device prior to the subsequent powering down event of the memory device.
A method, comprising:
- predicting, by a processing device coupled to a memory device, a duration of a subsequent power down event of the memory device;
- predicting a quantity of maintenance operations to be performed on the memory device based on the predicted duration of the subsequent power down event when the memory device is powered on after the subsequent power down event using an artificial neural network (ANN);
- performing the quantity of maintenance operations on the memory device prior to the subsequent powering down event of the memory device;
- comparing the predicted duration of the subsequent power down event to an actual duration of the subsequent power down event when the memory device is powered on;
- and
- training the ANN with the comparison of the predicted duration of the subsequent power down event to the actual duration of the subsequent power down event.
A system, comprising:
- a memory device;
- a first artificial neural network (ANN) configured to predict a duration of a subsequent power down event of the memory device;
- a second ANN configured to predict a plurality of different types of maintenance operations to be performed on the memory device based on the predicted duration of the subsequent power down event when the memory device is powered on after the subsequent power down event using the first ANN;
- and
- a processing device coupled to the first ANN and the second ANN and configured to perform the plurality of different types of maintenance operations on the memory device prior to the subsequent powering down event of the memory device.
Dependencies are inferred from the claim text.