28 nm FDSOI embedded PCM exhibiting near zero drift at 12 K for cryogenic SNNs
Seeking to circumvent conventional computing bottlenecks, hardware alternatives, from brain-inspired designs to cryogenic quantum systems, necessitate integrating emerging non-volatile memories. Yet, the immaturity and unreliability of cryogenic-compatible memories hinder scalable computing advancements. This study characterizes 28 nm FD-SOI substrate-embedded Ge-rich Ge2Sb2Te5 phase change memories (ePCMs) down to 12 K to overcome these hurdles. It reveals that ePCMs is cryogenic compatible and can encode multiple resistance states with minimal drift, essential for advanced computing solutions. Through simulations, the ePCM’s impact on a spiking neural network (SNN) performing MNIST classification is evaluated. The SNN maintains high accuracy for extended periods of 2 years at cryogenic temperatures, while an accuracy drop of 10.8% is observed at room temperature. These results highlight the potential of multilevel ePCMs in brain-inspired cryogenic computing applications, offering a promising avenue for the evolution of unconventional computing systems.
Authors
- Pierre-Antoine Mouny (ORCID: https://orcid.org/0000-0003-4941-8347)
- João Henrique Quintino Palhares (ORCID: https://orcid.org/0000-0002-2820-1627)
- Yann Beilliard (ORCID: https://orcid.org/0000-0003-0311-8840)
- Jury Sandrini
- Lorena Anghel (ORCID: https://orcid.org/0000-0001-9569-0072)
- Philippe Galy
- Nikhil Garg (ORCID: https://orcid.org/0000-0002-9210-2826)
- Dominique Drouin (ORCID: https://orcid.org/0000-0003-2156-967X)
- F. Arnaud (ORCID: https://orcid.org/0000-0002-8426-6695)
- Fabien Alibart (ORCID: https://orcid.org/0000-0002-9591-220X)
Institutions
- Institut polytechnique de Grenoble (FR)
- Centre National de la Recherche Scientifique (FR)
- Université de Sherbrooke (CA)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- CEA Grenoble (FR)
- STMicroelectronics (France) (FR)
- Spintronique et Technologie des Composants (FR)
- Université Grenoble Alpes (FR)
Publication Details
- Journal
- npj Unconventional Computing
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1038/s44335-024-00008-y
- Citations
- 9
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.88
Funders
- Indian National Science Academy
- Université de Sherbrooke
- Association Nationale de la Recherche et de la Technologie
- Centre National de la Recherche Scientifique
- École Centrale de Lyon