2 papers
cs.LG2025
NeFT: Negative Feedback Training to Improve Robustness of Compute-In-Memory DNN Accelerators
Yifan Qin, Zheyu Yan, Dailin Gan +5
Compute-in-memory accelerators built upon non-volatile memory devices excel in energy efficiency and latency when performing deep neural network (DNN) inference, thanks to their in…
cs.AR2025
Shared-PIM: Enabling Concurrent Computation and Data Flow for Faster Processing-in-DRAM
Ahmed Mamdouh, Haoran Geng, Michael Niemier +2
Processing-in-Memory (PIM) enhances memory with computational capabilities, potentially solving energy and latency issues associated with data transfer between memory and processor…