Asynchronous networks-on-chip (NoCs) playa fundamental role to materialize energy efficiency and scalability of spiking neural network-based neuromorphic systems. An unmistakable trend in this field consists of using bundled-data encoding for NoC design, showing promise in overall cost metrics while incorporating moderate timing constraints. To date, no framework exists for cost-effective and flexible NoC design with this approach. This paper aims at bridging this gap, by making bundled-data NoCs available to neuromorphic system designers through a highly-configurable and technology-independent soft macro. To our knowledge, this is the first paper to prove synchronous-equivalent design flexibility for an asynchronous NoC.

An Asynchronous Soft Macro for Ultra-Low Power Communication in Neuromorphic Computing

Bertozzi D.
Primo
Conceptualization
;
2022

Abstract

Asynchronous networks-on-chip (NoCs) playa fundamental role to materialize energy efficiency and scalability of spiking neural network-based neuromorphic systems. An unmistakable trend in this field consists of using bundled-data encoding for NoC design, showing promise in overall cost metrics while incorporating moderate timing constraints. To date, no framework exists for cost-effective and flexible NoC design with this approach. This paper aims at bridging this gap, by making bundled-data NoCs available to neuromorphic system designers through a highly-configurable and technology-independent soft macro. To our knowledge, this is the first paper to prove synchronous-equivalent design flexibility for an asynchronous NoC.
2022
9781665409964
Asynchronous networks; Bundled data; Low-power communication; Network-based; Networks on chips; Neural-networks; Neuromorphic computing; Neuromorphic systems; NoC design; Ultra-low power
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2504332
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