System and method for optimizing performance of a solid-state drive using a deep neural network

A data storage device comprising:

• one or more flash media;
• a controller configured to control the one or more flash media;
• and
• one or more deep neural network (DNN) modules for predicting an I/O access pattern of a host computer,
• wherein the one or more DNN modules receive one or more input vectors from the controller, provide one or more prediction outputs to the controller that are associated with one or more past I/O requests and a current I/O request received from the host computer using the one or more input vectors, and the one or more prediction outputs include at least one predicted I/O request following the current I/O request, and
• wherein the controller prefetches data stored in the flash media that is associated with the at least one predicted I/O request.

A bridge device comprising:

• one or more processors;
• one or more deep neural network (DNN) modules;
• a processor access module providing an interface between the one or more processors and the one or more DNN modules;
• a host interface;
• and
• a device interface to a solid-state drive (SSD),
• wherein the one or more DNN modules receive one or more input vectors from the SSD via the host interface, provide one or more prediction outputs to the SSD that are associated with one or more past I/O requests from the remote initiator and a current I/O request received from the remote initiator using the one or more input vectors, and the one or more prediction outputs include at least one predicted I/O request following the current I/O request, and
• wherein the SSD prefetches data stored in the flash media that is associated with the at least one predicted I/O request and provides the data to the bridge device via the device interface.