JitSim: A Simulator for Predicting Scalability of Parallel Applications in Presence of OS Jitter

Abstract

AbstractTraditionally, Operating system jitter has been a source of performance degradation for parallel applications running on large number of processors. While some large scale HPC systems such as Blue Gene/L and Cray XT4, mitigate jitter by making use of a specialized light-weight operating system on compute nodes, other clusters have attempted using HPC-ready commodity operating systems such as ZeptoOS (based on Linux). However, as large systems continue to be designed to work with commodity OSes, OS jitter still remains an active area of research within the HPC community. While, it is true that some of the specialized commodity OSes like ZeptoOS have relatively low OS jitter levels, there is still a need to have a quick and easy set of tools that can predict the impact of OS jitter at a given configuration and processor number. Such tools are also required to validate and compare any new techniques or OS enhancements that mitigate jitter. Emulating jitter on a large “jitter-free” platform using either synthetic jitter or real traces from commodity OSes has been proposed as one useful mechanism to study scalability behavior under the presence of jitter. However, this requires access to large scale jitter free systems, which are few in number and not so easily accessible. As new systems are built, that should scale up to a million tasks and more, the emulation approach is still limited by the largest jitter free system available. In this paper we present jitSim - a simulation framework for predicting scalability of parallel compute intensive applications in presence of OS jitter using trace driven simulation. The jitter simulation framework can be used to quickly simulate the effects of jitter that is characteristic of a given OS using a given trace. Furthermore, this system can be used to predict scalability up to any arbitrarily large number of task counts. Our methodology comprises of collection of real jitter traces, measurement of network latency, message passing stack latency, and shared memory latency. The simulation framework takes the above as inputs and then simulates multiple parallel tasks starting at randomly chosen points in the jitter trace and executing a compute phase. We validate the simulation results by comparing it with real data and demonstrate the efficacy of the simulation framework by evaluating various jitter mitigation techniques through simulation.KeywordsMessaging Passing InterfaceMessage PassingParallel ApplicationSimulation FrameworkParallel TaskThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.