Containment domains: A scalable, efficient, and flexible resilience scheme for exascale systems

Chung, Jinsuk; Lee, Ikhwan; Sullivan, Michael; Ryoo, Jee Ho; Kim, Dong Wan; Yoon, Doe Hyun; Kaplan, Larry; Erez, Mattan

doi:10.1109/sc.2012.36

Cited by 51 publications

(32 citation statements)

References 22 publications

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“…Since much is unsure about future fault tolerance solutions, there is active research into programming abstractions for resilience. For example, Chung et al [39] present containment domains: a programming construct that enables programmers to explicitly define the fault tolerance requirements for sections of code. Rolex [95] is a C/C++ language extension that incorporates resilience into application code.…”

Section: Programming Abstractionsmentioning

confidence: 99%

The Landscape of Exascale Research

et al. 2020

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The next generation of supercomputers will break the exascale barrier. Soon we will have systems capable of at least one quintillion (billion billion) floating-point operations per second (10 18 FLOPS). Tremendous amounts of work have been invested into identifying and overcoming the challenges of the exascale era. In this work, we present an overview of these efforts and provide insight into the important trends, developments, and exciting research opportunities in exascale computing. We use a three-stage approach in which we (1) discuss various exascale landmark studies, (2) use data-driven techniques to analyze the large collection of related literature, and (3) discuss eight research areas in depth based on influential articles. Overall, we observe that great advancements have been made in tackling the two primary exascale challenges: energy efficiency and fault tolerance. However, as we look forward, we still foresee two major concerns: the lack of suitable programming tools and the growing gap between processor performance and data bandwidth (i.e., memory, storage, networks). Although we will certainly reach exascale soon, without additional research, these issues could potentially limit the applicability of exascale computing.

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Section: Programming Abstractionsmentioning

confidence: 99%

The Landscape of Exascale Research

et al. 2020

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“…We have not explored fully the semantics and applications of nested failure handling in FTA; however, when provided, it would allow users to handle a variety of failures, including silent data corruption detected in the application inside a code block. This would allow to apply concepts, such as containment domains [6], in MPI applications.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Fault Tolerance Assistant (FTA): An Exception Handling Programming Model for MPI Applications

Fang

Laguna

Sato

et al. 2016

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Future high-performance computing systems may face frequent failures with their rapid increase in scale and complexity. Resilience to faults has become a major challenge for large-scale applications running on supercomputers, which demands fault tolerance support for prevalent MPI applications. Among failure scenarios, process failures are one of the most severe issues as they usually lead to termination of applications. However, the widely used MPI implementations do not provide mechanisms for fault tolerance. We propose FTA-MPI (Fault Tolerance Assistant MPI), a programming model that provides support for failure detection, failure notification and recovery. Specifically, FTA-MPI exploits a try/catch model that enables failure localization and transparent recovery of process failures in MPI applications. We demonstrate FTA-MPI with synthetic applications and a molecular dynamics code CoMD, and show that FTA-MPI provides high programmability for users and enables convenient and flexible recovery of process failures.

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“…These include projects such as MPICH-V [3], which combined lightweight checkpointing with message logging. Other new advances include Containment Domains [5], which allow the application to prevent errors in one part of the system from affecting others. Our work is in line with this last concept, presenting a heavily optimized solution for recovery on coprocessors.…”

Section: Related Workmentioning

confidence: 99%

Vocl-Ft

Peña

Bland

Balaji

2015

Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

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Popular accelerator programming models rely on offloading computation operations and their corresponding data transfers to the coprocessors, leveraging synchronization points where needed. In this paper we identify and explore how such a programming model enables optimization opportunities not utilized in traditional checkpoint/restart systems, and we analyze them as the building blocks for an efficient fault-tolerant system for accelerators. Although we leverage our techniques to protect from detected but uncorrected ECC errors in the device memory in OpenCL-accelerated applications, coprocessor reliability solutions based on different error detectors and similar API semantics can directly adopt the techniques we propose. Adding error detection and protection involves a tradeoff between runtime overhead and recovery time. Although optimal configurations depend on the particular application, the length of the run, the error rate, and the temporary storage speed, our test cases reveal a good balance with significantly reduced runtime overheads.

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Containment domains: A scalable, efficient, and flexible resilience scheme for exascale systems

Cited by 51 publications

References 22 publications

The Landscape of Exascale Research

The Landscape of Exascale Research

Fault Tolerance Assistant (FTA): An Exception Handling Programming Model for MPI Applications

Vocl-Ft

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