(Invited) Development, Characterization, and Modeling of a TaOx ReRAM for a Neuromorphic Accelerator
Resistive random access memory (ReRAM), or memristors, may be capable of significantly improving the efficiency of neuromorphic computing, when used as a central component of an analog hardware accelerator. However, the significant electrical variation within a single device and between devices degr...
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| creator | Marinella, Matthew J. Mickel, Patrick R Lohn, Andrew J Hughart, David R. Bondi, Robert Mamaluy, Denis Hjalmarson, Harold P. Stevens, James E Decker, Seth Apodaca, Roger T Evans, Brian Aimone, James Bradley Rothganger, Fred James, Conrad D. DeBenedictis, Erik P |
| description | Resistive random access memory (ReRAM), or memristors, may be capable of significantly improving the efficiency of neuromorphic computing, when used as a central component of an analog hardware accelerator. However, the significant electrical variation within a single device and between devices degrades the maximum efficiency and accuracy which can be achieved by a ReRAM-based neuromorphic accelerator. In this report, the electrical variability is characterized, with a particular focus on that which is due to fundamental, intrinsic factors. Analytical and ab initio models are presented which offer insight into the factors responsible for this variability. |
| doi_str_mv | 10.1149/06414.0037ecst |
| format | Conference Proceeding |
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| fulltext | fulltext |
| identifier | ISSN: 1938-5862 |
| ispartof | ECS transactions, 2014, Vol.64 (14), p.37-42 |
| issn | 1938-5862 1938-6737 1938-6737 |
| language | eng |
| recordid | cdi_osti_scitechconnect_1241770 |
| source | Institute of Physics Journals |
| title | (Invited) Development, Characterization, and Modeling of a TaOx ReRAM for a Neuromorphic Accelerator |
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