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Found 2 papers, 1 papers with code
Analog or Digital In-memory Computing? Benchmarking through Quantitative Modeling
In-Memory Computing (IMC) has emerged as a promising paradigm for energy-efficient, throughput-efficient and area-efficient machine learning at the edge.
ZigZag: A Memory-Centric Rapid DNN Accelerator Design Space Exploration Framework
This work introduces ZigZag, a memory-centric rapid DNN accelerator DSE framework which extends the DSE with uneven mapping opportunities, in which operands at shared memory levels are no longer bound to use the same memory levels for each loop index.
Distributed, Parallel, and Cluster Computing C.1.4; C.3; C.4
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