DenRAM: neuromorphic dendritic architecture with RRAM for efficient temporal processing with delays

Simone D’Agostino, Filippo Moro, Tristan Torchet, Yiğit Demirağ, Laurent Grenouillet, Niccolò Castellani, Giacomo Indiveri, Elisa Vianello and Melika Payvand ()
Additional contact information
Simone D’Agostino: University of Zurich and ETH Zurich
Filippo Moro: University of Zurich and ETH Zurich
Tristan Torchet: University of Zurich and ETH Zurich
Yiğit Demirağ: University of Zurich and ETH Zurich
Laurent Grenouillet: Université Grenoble Alpes
Niccolò Castellani: Université Grenoble Alpes
Giacomo Indiveri: University of Zurich and ETH Zurich
Elisa Vianello: Université Grenoble Alpes
Melika Payvand: University of Zurich and ETH Zurich

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Neuroscience findings emphasize the role of dendritic branching in neocortical pyramidal neurons for non-linear computations and signal processing. Dendritic branches facilitate temporal feature detection via synaptic delays that enable coincidence detection (CD) mechanisms. Spiking neural networks highlight the significance of delays for spatio-temporal pattern recognition in feed-forward networks, eliminating the need for recurrent structures. Here, we introduce DenRAM, a novel analog electronic feed-forward spiking neural network with dendritic compartments. Utilizing 130 nm technology integrated with resistive RAM (RRAM), DenRAM incorporates both delays and synaptic weights. By configuring RRAMs to emulate bio-realistic delays and exploiting their heterogeneity, DenRAM mimics synaptic delays and efficiently performs CD for pattern recognition. Hardware-aware simulations on temporal benchmarks show DenRAM’s robustness against hardware noise, and its higher accuracy over recurrent networks. DenRAM advances temporal processing in neuromorphic computing, optimizes memory usage, and marks progress in low-power, real-time signal processing

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-47764-w Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47764-w

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-47764-w

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().