Live Demonstration: Energy-Efficient Data Symbol Detection via Boosted Learning for Multi-Actuator Data Storage Systems

The equipment includes a laptop, Xilinx ZCU102 Dev Board, and a hard-disk drive (HDD) interface module. Fig. 1 illustrates the demonstration setup. All of the devices will be powered by their own power adaptors. The HDD interface module, which is provided by the Data Storage Systems Center (DSSC) at Carnegie Mellon University, can be controlled by the laptop to generate the raw readback signals for the machine- learning (ML) module implemented on the Xilinx ZCU102 to perform data symbol detection. The classified outputs are sent back to the laptop for result analysis and demonstration with a graphical user interface (GUI).