Machine learning assisted quality of service (qos) for solid state drives

Abstract

A method for meeting quality of service (QoS) requirements in a flash controller that includes one or more instruction queues and a neural network engine. A configuration file for a QoS neural network is loaded into the neural network engine. A current command is received at the instruction queue(s). Feature values corresponding to commands in the instruction queue(s) are identified and are loaded into the neural network engine. A neural network operation of the QoS neural network is performed using as input the identified feature values to predict latency of the current command. The predicted latency is compared to a first latency threshold. When the predicted latency exceeds the first latency threshold one or more of the commands in the instruction queue(s) are modified. The commands are not modified when the predicted latency does not exceed the latency threshold. A next command in the instruction queue(s) is then performed.