Publication | Closed Access
A 40-nm, 2M-Cell, 8b-Precision, Hybrid SLC-MLC PCM Computing-in-Memory Macro with 20.5 - 65.0TOPS/W for Tiny-Al Edge Devices
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Citations
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References
2022
Year
EngineeringComputer ArchitectureTiny-al Edge DevicesHigh-performance ArchitectureComputing SystemsAdaptive MemoryMemory DevicesAnalog Nvcim DesignsParallel ComputingElectrical EngineeringComputer EngineeringComputer ScienceMicroelectronicsMemory ArchitectureHardware AccelerationMicrofabricationEdge ComputingApplied PhysicsMulti-access Edge ComputingSemiconductor MemoryStorage TypeEfficient Edge ComputingIn-memory Computing
Efficient edge computing, with sufficiently large on-chip memory capacity, is essential in the internet-of-everything era. Nonvolatile computing-in-memory (nvCIM) reduces the data transfer overhead by bringing computation closer, in proximity, to the memory [1]–[4]. While the multi-level cell (MLC) has higher storage density than the single-level cell (SLC). A few MLC or analog nvCIM designs had been proposed, but they either target simpler neural-net models [5] or are implemented using a less area-efficient differential cell [6]. Furthermore, representing the entire weight vector using one storage type does not exploit the drastic accuracy difference between the upper and the lower bits.
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