A trace-driven methodology to evaluate and optimize memory management services of distributed operating systems for lightweight manycores

Abstract

Lightweight manycores belong to a new class of emerging lowpower processors for the Exascale era. These processors present several challenges for the development of applications, such as distributed memory architecture, limited amount of on-chip memory and no cache coherence. Recently, distributed Operating Systems (OSs) have been proposed to address these challenges in a transparent way. In these systems, different OS services are deployed across the processor cores, being the memory management service one of the most important ones. However, the intrinsic characteristics and memory limitations of lightweight manycores bring several challenges to the design, implementation and future optimizations of memory management services. In this work, we propose a tracedriven methodology to evaluate and optimize features of a memory management service of distributed OSs for lightweight manycores. By using a compact representation of the page access pattern of the applications, our methodology is capable of mimicking the memory access pattern of the original applications on the target distributed OS running on a lightweight manycore. We integrated our methodology in a distributed OS (Nanvix) and validated it using three applications from a specific benchmark for lightweight manycores (CAP Bench). Then, we applied our methodology to carry out a case study using a software-managed cache implementation available in Nanvix. Our methodology enabled us to evaluate different page replacement policies on Kalray MPPA-256, even without the required support from the architecture to implement them. CCS CONCEPTS• Computer systems organization → System on a chip; Very long instruction word; Multiple instruction, multiple data; Parallel architectures;