Patent attributes
A method and apparatus for sustaining performance of a data storage device by predictively determining resource needs and executing processes to meet those needs before the resources are actually needed. According to certain embodiments, a controller collects commands coming from a host and provides these to a machine learning model such as a recurrent neural network (RNN). The RNN is trained using this data, and output of the trained model is used to predict future commands. As future commands are developed by the RNN, resource allocation processes such as garbage collection may be initiated prior to the actual need, during times when processing cycles in the data storage device are available. By operating the garbage collection when the device has available processing may mitigate transition to an urgent mode.
