{"ID":2894327,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.11134","arxiv_id":"2507.11134","title":"Fault-Free Analog Computing with Imperfect Hardware","abstract":"The growing demand for edge computing and AI drives research into analog in-memory computing using memristors, which overcome data movement bottlenecks by computing directly within memory. However, device failures and variations critically limit analog systems' precision and reliability. Existing fault-tolerance techniques, such as redundancy and retraining, are often inadequate for high-precision applications or scenarios requiring fixed matrices and privacy preservation. Here, we introduce and experimentally demonstrate a fault-free matrix representation where target matrices are decomposed into products of two adjustable sub-matrices programmed onto analog hardware. This indirect, adaptive representation enables mathematical optimization to bypass faulty devices and eliminate differential pairs, significantly enhancing computational density. Our memristor-based system achieved \u003e99.999% cosine similarity for a Discrete Fourier Transform matrix despite 39% device fault rate, a fidelity unattainable with conventional direct representation, which fails with single device faults (0.01% rate). We demonstrated 56-fold bit-error-rate reduction in wireless communication and \u003e196% density with 179% energy efficiency improvements compared to state-of-the-art techniques. This method, validated on memristors, applies broadly to emerging memories and non-electrical computing substrates, showing that device yield is no longer the primary bottleneck in analog computing hardware.","short_abstract":"The growing demand for edge computing and AI drives research into analog in-memory computing using memristors, which overcome data movement bottlenecks by computing directly within memory. However, device failures and variations critically limit analog systems' precision and reliability. Existing fault-tolerance techni...","url_abs":"https://arxiv.org/abs/2507.11134","url_pdf":"https://arxiv.org/pdf/2507.11134v1","authors":"[\"Zhicheng Xu\",\"Jiawei Liu\",\"Sitao Huang\",\"Zefan Li\",\"Shengbo Wang\",\"Bo Wen\",\"Ruibin Mao\",\"Mingrui Jiang\",\"Giacomo Pedretti\",\"Jim Ignowski\",\"Kaibin Huang\",\"Can Li\"]","published":"2025-07-15T09:37:05Z","proceeding":"cs.ET","tasks":"[\"cs.ET\",\"cs.AR\"]","methods":"[]","has_code":false}