Method for Optimizing Memory Access Based on Machine Learning Model and Related Device

A device, comprising:

• a processor;
• and
• a memory storing instructions, wherein the instructions are performed by the processor to perform:
• convert a portion of a machine learning model corresponding to an operation requirement of a hardware into a directed acyclic graph, wherein the portion of the machine learning model comprises multiple fusions, and the directed acyclic graph comprises a plurality of vertices and a plurality of directed edges, wherein an edge ei,j is from a vertex Vi to a vertex Vj, and a value of the edge ei,j is set to indicate a total amount of an external memory accesses from an input of fusioni to an output of fusionj-1, where i, j are positive integers and j is larger than i, and wherein the external memory is located outside of the hardware;
• and
• determine a shortest path, wherein the shortest path is from a starting vertex to a destination vertex with a smallest total amount of external memory accesses, wherein the starting vertex does not have an input edge, and the destination vertex does not have an output edge.