66 citations · 237 across the 42 of their papers we have counts for
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cs.ET2019
Training of Quantized Deep Neural Networks using a Magnetic Tunnel Junction-Based Synapse
Tzofnat Greenberg Toledo, Ben Perach, Itay Hubara +2
Quantized neural networks (QNNs) are being actively researched as a solution for the computational complexity and memory intensity of deep neural networks. This has sparked efforts…
cs.AR2019★ 4 cited
The Bitlet Model: Defining a Litmus Test for the Bitwise Processing-in-Memory Paradigm
Kunal Korgaonkar, Ronny Ronen, Anupam Chattopadhyay +1
This paper describes an analytical modeling tool called Bitlet that can be used, in a parameterized fashion, to understand the affinity of workloads to processing-in-memory (PIM) a…