and challenging. This paper proposes a new approachto modelling and characterizing big
data and AI workloads. We consider each big data and AI workload as a pipeline of one or
more classes of units of computation performed on different initial or intermediate data
inputs. Each class of unit of computation captures the common requirements while being
reasonably divorced from individual implementations, and hence we call it a data motif. For …