Phase change memory as synapse for ultra-dense neuromorphic systems: application to complex visual pattern extraction

Manan Suri (1) , Olivier Bichler (2) , Damien Querlioz (3) , Olga Cueto (1) , Luca Perniola (1) , Véronique Sousa (1) , Dominique Vuillaume (4) , Christian Gamrat (5) , Barbara Desalvo (1)

1 CEA-LETI - Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information
2 DSCIN (CEA, LIST) - Département Systèmes et Circuits Intégrés Numériques
3 IEF - Institut d'électronique fondamentale
4 IEMN - Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520
5 LCEI - Laboratoire Calculateurs Embarqués et Image

We demonstrate a unique energy efficient methodology to use Phase Change Memory (PCM) as synapse in ultra-dense large scale neuromorphic systems. PCM devices with different chalcogenide materials were characterized to demonstrate synaptic behavior. Multi-physical simulations were used to interpret the results. We propose special circuit architecture (“the 2-PCM synapse”), read, write, and reset programming schemes suitable for the use of PCM in neural networks. A versatile behavioral model of PCM which can be used for simulating large scale neural systems is introduced. First demonstration of complex visual pattern extraction from real world data using PCM synapses in a 2-layer spiking neural network (SNN) is shown. System power analysis for different scaled PCM technologies is also provided.

Domaines: Micro et nanotechnologies/Microélectronique; Neurosciences [q-bio.NC]

Manan Suri, Olivier Bichler, Damien Querlioz, Olga Cueto, Luca Perniola, et al.. Phase change memory as synapse for ultra-dense neuromorphic systems: application to complex visual pattern extraction. IEEE International Electron Devices Meeting (IEDM 2011), Dec 2011, Washington, DC, United States. ⟨10.1109/IEDM.2011.6131488⟩. ⟨hal-00799997⟩