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Evaluating Online Global Recovery with Fenix Using Application-Aware In-Memory Checkpointing Techniques

Proceedings of the International Conference on Parallel Processing Workshops

Gamell, Marc; Katz, Daniel S.; Teranishi, Keita T.; Heroux, Michael A.; Van Der Wijngaart, Rob F.; Mattson, Timothy G.; Parashar, Manish

Exascale systems promise the potential for computation atunprecedented scales and resolutions, but achieving exascale by theend of this decade presents significant challenges. A key challenge isdue to the very large number of cores and components and the resultingmean time between failures (MTBF) in the order of hours orminutes. Since the typical run times of target scientific applicationsare longer than this MTBF, fault tolerance techniques will beessential. An important class of failures that must be addressed isprocess or node failures. While checkpoint/restart (C/R) is currentlythe most widely accepted technique for addressing processor failures, coordinated, stable-storage-based global C/R might be unfeasible atexascale when the time to checkpoint exceeds the expected MTBF. This paper explores transparent recovery via implicitly coordinated, diskless, application-driven checkpointing as a way to tolerateprocess failures in MPI applications at exascale. The discussedapproach leverages User Level Failure Mitigation (ULFM), which isbeing proposed as an MPI extension to allow applications to createpolicies for tolerating process failures. Specifically, this paper demonstrates how different implementations ofapplication-driven in-memory checkpoint storage and recovery comparein terms of performance and scalability. We also experimentally evaluate the effectiveness and scalability ofthe Fenix online global recovery framework on a production system-the Titan Cray XK7 at ORNL-and demonstrate the ability of Fenix totolerate dynamically injected failures using the execution of fourbenchmarks and mini-applications with different behaviors.

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Local recovery and failure masking for stencil-based applications at extreme scales

International Conference for High Performance Computing, Networking, Storage and Analysis, SC

Gamell, Marc; Teranishi, Keita T.; Heroux, Michael A.; Mayo, Jackson M.; Kolla, Hemanth K.; Chen, Jacqueline H.; Parashar, Manish

Application resilience is a key challenge that has to be addressed to realize the exascale vision. Online recovery, even when it involves all processes, can dramatically reduce the overhead of failures as compared to the more traditional approach where the job is terminated and restarted from the last checkpoint. In this paper we explore how local recovery can be used for certain classes of applications to further reduce overheads due to resilience. Specifically we develop programming support and scalable runtime mechanisms to enable online and transparent local recovery for stencil-based parallel applications on current leadership class systems. We also show how multiple independent failures can be masked to effectively reduce the impact on the total time to solution. We integrate these mechanisms with the S3D combustion simulation, and experimentally demonstrate (using the Titan Cray-XK7 system at ORNL) the ability to tolerate high failure rates (i.e., node failures every 5 seconds) with low overhead while sustaining performance, at scales up to 262144 cores.

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ASC ATDM Level 2 Milestone #5325: Asynchronous Many-Task Runtime System Analysis and Assessment for Next Generation Platforms

Baker, Gavin M.; Bettencourt, Matthew T.; Bova, S.W.; franko, ken f.; Gamell, Marc G.; Grant, Ryan E.; Hammond, Simon D.; Hollman, David S.; Knight, Samuel K.; Kolla, Hemanth K.; Lin, Paul L.; Olivier, Stephen O.; Sjaardema, Gregory D.; Slattengren, Nicole L.; Teranishi, Keita T.; Wilke, Jeremiah J.; Bennett, Janine C.; Clay, Robert L.; kale, laxkimant k.; Jain, Nikhil J.; Mikida, Eric M.; Aiken, Alex A.; Bauer, Michael B.; Lee, Wonchan L.; Slaughter, Elliott S.; Treichler, Sean T.; Berzins, Martin B.; Harman, Todd H.; humphreys, alan h.; schmidt, john s.; sunderland, dan s.; Mccormick, Pat M.; gutierrez, samuel g.; shulz, martin s.; Gamblin, Todd G.; Bremer, Peer-Timo B.

Abstract not provided.

ASC ATDM Level 2 Milestone #5325: Asynchronous Many-Task Runtime System Analysis and Assessment for Next Generation Platforms

Baker, Gavin M.; Bettencourt, Matthew T.; Bova, S.W.; franko, ken f.; Gamell, Marc G.; Grant, Ryan E.; Hammond, Simon D.; Hollman, David S.; Knight, Samuel K.; Kolla, Hemanth K.; Lin, Paul L.; Olivier, Stephen O.; Sjaardema, Gregory D.; Slattengren, Nicole L.; Teranishi, Keita T.; Wilke, Jeremiah J.; Bennett, Janine C.; Clay, Robert L.; kale, laxkimant k.; Jain, Nikhil J.; Mikida, Eric M.; Aiken, Alex A.; Bauer, Michael B.; Lee, Wonchan L.; Slaughter, Elliott S.; Treichler, Sean T.; Berzins, Martin B.; Harman, Todd H.; humphreys, alan h.; schmidt, john s.; sunderland, dan s.; Mccormick, Pat M.; gutierrez, samuel g.; shulz, martin s.; Gamblin, Todd G.; Bremer, Peer-Timo B.

This report provides in-depth information and analysis to help create a technical road map for developing next-generation programming models and runtime systems that support Advanced Simulation and Computing (ASC) work- load requirements. The focus herein is on asynchronous many-task (AMT) model and runtime systems, which are of great interest in the context of "Oriascale7 computing, as they hold the promise to address key issues associated with future extreme-scale computer architectures. This report includes a thorough qualitative and quantitative examination of three best-of-class AIM] runtime systems – Charm-++, Legion, and Uintah, all of which are in use as part of the Centers. The studies focus on each of the runtimes' programmability, performance, and mutability. Through the experiments and analysis presented, several overarching Predictive Science Academic Alliance Program II (PSAAP-II) Asc findings emerge. From a performance perspective, AIV runtimes show tremendous potential for addressing extreme- scale challenges. Empirical studies show an AM runtime can mitigate performance heterogeneity inherent to the machine itself and that Message Passing Interface (MP1) and AM11runtimes perform comparably under balanced conditions. From a programmability and mutability perspective however, none of the runtimes in this study are currently ready for use in developing production-ready Sandia ASC applications. The report concludes by recommending a co- design path forward, wherein application, programming model, and runtime system developers work together to define requirements and solutions. Such a requirements-driven co-design approach benefits the community as a whole, with widespread community engagement mitigating risk for both application developers developers. and high-performance computing runtime systein

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Exploring failure recovery for stencil-based applications at extreme scales

HPDC 2015 - Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing

Gamell, Marc; Teranishi, Keita T.; Heroux, Michael A.; Mayo, Jackson M.; Kolla, Hemanth K.; Chen, Jacqueline H.; Parashar, Manish

Application resilience is a key challenge that must be ad-dressed in order to realize the exascale vision. Previous work has shown that online recovery, even when done in a global manner (i.e., involving all processes), can dramatically re-duce the overhead of failures when compared to the more traditional approach of terminating the job and restarting it from the last stored checkpoint. In this paper we suggest going one step further, and explore how local recovery can be used for certain classes of applications to reduce the over-heads due to failures. Specifically we study the feasibility of local recovery for stencil-based parallel applications and we show how multiple independent failures can be masked to effectively reduce the impact on the total time to solution.

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Lessons Learned from Porting the MiniAero Application to Charm++

Hollman, David S.; Hollman, David S.; Bennett, Janine C.; Bennett, Janine C.; Wilke, Jeremiah J.; Wilke, Jeremiah J.; Kolla, Hemanth K.; Kolla, Hemanth K.; Lin, Paul L.; Lin, Paul L.; Slattengren, Nicole S.; Slattengren, Nicole S.; Teranishi, Keita T.; Teranishi, Keita T.; franko, ken f.; franko, ken f.; Jain, Nikhil J.; Jain, Nikhil J.; Mikida, Eric M.; Mikida, Eric M.

Abstract not provided.

Versioned distributed arrays for resilience in scientific applications: Global View Resilience

Procedia Computer Science

Chien, A.; Balaji, P.; Beckman, P.; Dun, N.; Fang, A.; Fujita, H.; Iskra, K.; Rubenstein, Z.; Zheng, Z.; Schreiber, R.; Hammond, J.; Dinan, J.; Laguna, I.; Richards, D.; Dubey, A.; Van Straalen, B.; Hoemmen, M.; Heroux, Michael A.; Teranishi, Keita T.; Siegel, A.

Exascale studies project reliability challenges for future high-performance computing (HPC) systems. We propose the Global View Resilience (GVR) system, a library that enables applications to add resilience in a portable, application-controlled fashion using versioned distributed arrays. We describe GVR's interfaces to distributed arrays, versioning, and cross-layer error recovery. Using several large applications (OpenMC, the preconditioned conjugate gradient solver PCG, ddcMD, and Chombo), we evaluate the programmer effort to add resilience. The required changes are small (<2% LOC), localized, and machine-independent, requiring no software architecture changes. We also measure the overhead of adding GVR versioning and show that generally overheads <2% are achieved. We conclude that GVR's interfaces and implementation are flexible and portable and create a gentle-slope path to tolerate growing error rates in future systems.

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Results 26–50 of 55
Results 26–50 of 55