Modular DFR: Digital Delayed Feedback Reservoir Model for Enhancing Design Flexibility
This work addresses hardware implementation challenges for reservoir computing systems, offering a more efficient and flexible digital design, though it is incremental in improving existing DFR methods.
The paper tackled the lack of design flexibility and high power consumption in digital delayed feedback reservoirs (DFRs) by proposing a novel modular DFR model, resulting in a 10x power reduction and 5.3x throughput improvement while maintaining or improving accuracy.
A delayed feedback reservoir (DFR) is a type of reservoir computing system well-suited for hardware implementations owing to its simple structure. Most existing DFR implementations use analog circuits that require both digital-to-analog and analog-to-digital converters for interfacing. However, digital DFRs emulate analog nonlinear components in the digital domain, resulting in a lack of design flexibility and higher power consumption. In this paper, we propose a novel modular DFR model that is suitable for fully digital implementations. The proposed model reduces the number of hyperparameters and allows flexibility in the selection of the nonlinear function, which improves the accuracy while reducing the power consumption. We further present two DFR realizations with different nonlinear functions, achieving 10x power reduction and 5.3x throughput improvement while maintaining equal or better accuracy.