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cs.AR2023
Just-in-time Quantization with Processing-In-Memory for Efficient ML Training
Mohamed Assem Ibrahim, Shaizeen Aga, Ada Li +2
Data format innovations have been critical for machine learning (ML) scaling, which in turn fuels ground-breaking ML capabilities. However, even in the presence of low-precision fo…
cs.AR2023
Inclusive-PIM: Hardware-Software Co-design for Broad Acceleration on Commercial PIM Architectures
Johnathan Alsop, Shaizeen Aga, Mohamed Ibrahim +3
Continual demand for memory bandwidth has made it worthwhile for memory vendors to reassess processing in memory (PIM), which enables higher bandwidth by placing compute units in/n…