{"ID":2845658,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.03203","arxiv_id":"2511.03203","title":"An Event-Driven Spiking Compute-In-Memory Macro based on SOT-MRAM","abstract":"The application of Magnetic Random-Access Memory (MRAM) in computing-in-memory (CIM) has gained significant attention. However, existing designs often suffer from high energy consumption due to their reliance on complex analog circuits for computation. In this work, we present a Spin-Orbit- Torque MRAM(SOT-MRAM)-based CIM macro that employs an event-driven spiking processing for high energy efficiency. The SOT-MRAM crossbar adopts a hybrid series-parallel cell structure to efficiently support matrix-vector multiplication (MVM). Signal information is (en) decoded as spikes using lightweight circuits, eliminating the need for conventional area- and powerintensive analog circuits. The SOT-MRAM macro is designed and evaluated in 28nm technology, and experimental results show that it achieves a peak energy efficiency of 243.6 TOPS/W, significantly outperforming existing designs.","short_abstract":"The application of Magnetic Random-Access Memory (MRAM) in computing-in-memory (CIM) has gained significant attention. However, existing designs often suffer from high energy consumption due to their reliance on complex analog circuits for computation. In this work, we present a Spin-Orbit- Torque MRAM(SOT-MRAM)-based...","url_abs":"https://arxiv.org/abs/2511.03203","url_pdf":"https://arxiv.org/pdf/2511.03203v2","authors":"[\"Deyang Yu\",\"Chenchen Liu\",\"Chuanjie Zhang\",\"Xiao Fang\",\"Weisheng Zhao\"]","published":"2025-11-05T05:38:59Z","proceeding":"cs.AR","tasks":"[\"cs.AR\"]","methods":"[]","has_code":false}