Memristor chip accelerates compressed sensing by 11 times through hardware-software co-optimization
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Dec-2025 14:11 ET (22-Dec-2025 19:11 GMT/UTC)
To tackle the high energy and latency costs of compressed sensing workloads in edge computing, researchers at Tsinghua University developed a memristor-based compressed sensing accelerator (memCS). By utilizing a computing-in-memory (CIM) architecture and hardware-software co-optimization framework to mitigate accuracy loss from hardware non-idealities, the memCS achieved a near-software computing accuracy (31.11 dB peak signal-to-noise ratio) while delivering an 11.22x speedup and 30.46x energy savings compared to GPUs, paving the way for efficient edge computing.
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