Exact In-Memory Multiplication Based on Deterministic Stochastic Computing

ISCAS(2020)

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摘要
Memristors offer the ability to both store and process data in memory, eliminating the overhead of data transfer between memory and processing unit. For data-intensive applications, developing efficient in-memory computing methods is under investigation. Stochastic computing (SC), a paradigm offering simple execution of complex operations, has been used for reliable and efficient multiplication of data in-memory. Current SC-based in-memory methods are incapable of producing accurate results. This work, to the best of our knowledge, develops the first accurate SC-based in-memory multiplier. For logical operations, we use Memristor-Aided Logic (MAGIC), and to generate bit-streams, we propose a novel method, which takes advantage of the intrinsic properties of memristors. The proposed design improves the speed and reduces the memory usage and energy consumption compared to the State-of-the-Art (SoA) accurate in-memory fixed-point and off-memory SC multipliers.
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关键词
logical operations,MAGIC,state-of-the-art accurate in-memory fixed-point multipliers,accurate SC-based in-memory multiplier,current SC-based in-memory methods,data in-memory,in-memory computing methods,data-intensive applications,data transfer,deterministic stochastic computing,in-memory multiplication,memristors,memristor-aided logic
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