User-Level Memory Scheduler for Optimizing Application Performance in NUMA-Based Multicore Systems

TL;DR

This paper introduces a user-space memory scheduler that optimizes application performance on NUMA-based multicore systems by intelligently allocating memory nodes based on application characteristics.

Contribution

It presents a novel user-space memory scheduling approach that considers application-specific behavior in NUMA architectures, unlike traditional kernel-level methods.

Findings

Application performance improved by up to 25%.

The scheduler effectively allocates memory nodes based on application needs.

User-space approach enhances performance without kernel modifications.

Abstract

Multicore CPU architectures have been established as a structure for general-purpose systems for high-performance processing of applications. Recent multicore CPU has evolved as a system architecture based on non-uniform memory architecture. For the technique of using the kernel space that shifts the tasks to the ideal memory node, the characteristics of the applications of the user-space cannot be considered. Therefore, kernel level approaches cannot execute memory scheduling to recognize the importance of user applications. Moreover, users need to run applications after sufficiently understanding the multicore CPU based on non-uniform memory architecture to ensure the high performance of the user's applications. This paper presents a user-space memory scheduler that allocates the ideal memory node for tasks by monitoring the characteristics of non-uniform memory architecture. From our experiment, the proposed system improved the performance of the application by up to 25% compared to the existing system.