Abstract
Processing-in-memory (PIM) is emerging as a new computing paradigm to replace the existing von Neumann computer architecture for data-intensive processing. For the higher end-user mobility, low-power operation capability is more increasingly required and components need to be renovated to make a way out of the conventional software-driven artificial intelligence. In this work, we investigate the hardware performances of PIM architecture that can be presumably constructed by resistive-switching random-access memory (ReRAM) synapse fabricated with a relatively larger thermal budget in the full Si processing compatibility. By introducing a medium-temperature oxidation in which the sputtered Ge atoms are oxidized at a relatively higher temperature compared with the ReRAM devices fabricated by physical vapor deposition at room temperature, higher device reliability has been acquired. Based on the empirically obtained device parameters, a PIM architecture has been conceived and a system-level evaluations have been performed in this work. Considerations include the cycle-to-cycle variation in the GeOx ReRAM synapse, analog-to-digital converter resolution, synaptic array size, and interconnect latency for the system-level evaluation with the Canadian Institute for Advance Research-10 dataset. A fully Si processing-compatible and robust ReRAM synapse and its applicability for PIM are demonstrated. Graphical Abstract: [Figure not available: see fulltext.]
Original language | English |
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Article number | 63 |
Journal | Nanoscale Research Letters |
Volume | 17 |
Issue number | 1 |
DOIs | |
State | Published - 2022 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s).
Keywords
- Germanium oxide
- Low-power hardware neural network
- Medium-temperature oxidation
- Processing-in-memory (PIM)
- Resistive-switching random-access memory (ReRAM)