PREM-Based Optimal Task Segmentation Under Fixed Priority Scheduling

Recently, a large number of works have discussed scheduling tasks consisting of a sequence of memory phases, where code and data are moved between main memory and local memory, and computation phases, where the task executes based on the content of local memory only; the key idea is to prevent main memory contention by scheduling the memory phase of one task in parallel with computation phases of tasks running on other cores. This paper provides two main contributions: (1) we present a compiler-level tool, based on the LLVM intermediate representation, that automatically converts a program into a conditional sequence of segments comprising memory and computation phases; (2) we propose an algorithm to find optimal segmentation decisions for a task set scheduled according to a fixed-priority partitioned scheme. Our evaluation shows that the proposed framework can be feasibly applied to realistic programs, and vastly overperforms a baseline greedy approach.