As AI applications rapidly advance, AI models are being tasked with processing massive amounts of data containing billions – or even trillions – of parameters. Each large workload involves numerous iterations for data comparison, predictive calculations, and parameter results updating during training. Hence, there is a constant demand for flexible memory expansion and memory sharing among d...
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