HIGHLIGHTS
- who: Andrea Baroni from the University of Modena and Reggio Emilia, Italy have published the article: An energy-efficient in-memory computing architecture for survival data analysis based on resistive switching memories, in the Journal: (JOURNAL)
- what: The authors present an IMC architecture based on RRAM technology that implements a deep neural_network for survival analysis of biomedical data, namely the DeepSurv (Katzman et_al, 2018). In this work, three different priority patterns were studied: i) weights with the greatest absolute value; ii) weights with the lowest absolute value; and iii) weights featuring the lowest quantization error . . .
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