An Overview of In-memory Processing with Emerging Non-volatile Memory for Data-intensive Applications
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Abstract (arXiv)
The conventional von Neumann architecture has been revealed as a major performance and energy bottleneck for rising data-intensive applications. %, due to the intensive data movements. The decade-old idea of leveraging in-memory processing to eliminate substantial data movements has returned and led extensive research activities. The effectiveness of in-memory processing heavily relies on memory scalability, which cannot be satisfied by traditional memory technologies. Emerging non-volatile memories (eNVMs) that pose appealing qualities such as excellent scaling and low energy consumption, on the other hand, have been heavily investigated and explored for realizing in-memory processing architecture. In this paper, we summarize the recent research progress in eNVM-based in-memory processing from various aspects, including the adopted memory technologies, locations of the in-memory processing in the system, supported arithmetics, as well as applied applications.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jun 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1; 2025: 1; 2026: 1.
5 papers.
- 2024CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Acceleratorscited by 3
- 2023Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticitycited by 2
- 2021Brain-inspired Cognition in Next Generation Racetrack Memoriescited by 1
- 2025Efficient Calibration for RRAM-based In-Memory Computing using DoRAcited by 0
- 2026Robust Reasoning and Learning with Brain-Inspired Representations under Hardware-Induced Nonlinearitiescited by 0
- 2026Robust Reasoning and Learning with Brain-Inspired Representations under Hardware-Induced Nonlinearities13 Apr 2026
- 2025Efficient Calibration for RRAM-based In-Memory Computing using DoRA2 Apr 2025
- 2024CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators23 Jan 2024
- 2023Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity2 Feb 2023
- 2021Brain-inspired Cognition in Next Generation Racetrack Memories3 Nov 2021