6,151 research outputs found
A Survey of Fault-Tolerance and Fault-Recovery Techniques in Parallel Systems
Supercomputing systems today often come in the form of large numbers of
commodity systems linked together into a computing cluster. These systems, like
any distributed system, can have large numbers of independent hardware
components cooperating or collaborating on a computation. Unfortunately, any of
this vast number of components can fail at any time, resulting in potentially
erroneous output. In order to improve the robustness of supercomputing
applications in the presence of failures, many techniques have been developed
to provide resilience to these kinds of system faults. This survey provides an
overview of these various fault-tolerance techniques.Comment: 11 page
A fault-tolerance protocol for parallel applications with communication imbalance
ArticuloThe predicted failure rates of future supercomputers
loom the groundbreaking research large machines are
expected to foster. Therefore, resilient extreme-scale applications
are an absolute necessity to effectively use the new generation
of supercomputers. Rollback-recovery techniques have been
traditionally used in HPC to provide resilience. Among those
techniques, message logging provides the appealing features of
saving energy, accelerating recovery, and having low performance
penalty. Its increased memory consumption is, however, an
important downside. This paper introduces memory-constrained
message logging (MCML), a general framework for decreasing the
memory footprint of message-logging protocols. In particular, we
demonstrate the effectiveness of MCML in maintaining message
logging feasible for applications with substantial communication
imbalance. This type of applications appear in many scientific
fields. We present experimental results with several parallel codes
running on up to 4,096 cores. Using those results and an analytical
model, we predict MCML can reduce execution time up to 25%
and energy consumption up to 15%, at extreme scale
OPR
The ability to reproduce a parallel execution is desirable for debugging and program reliability purposes. In debugging (13), the programmer needs to manually step back in time, while for resilience (6) this is automatically performed by the the application upon failure. To be useful, replay has to faithfully reproduce the original execution. For parallel programs the main challenge is inferring and maintaining the order of conflicting operations (data races). Deterministic record and replay (R&R) techniques have been developed for multithreaded shared memory programs (5), as well as distributed memory programs (14). Our main interest is techniques for large scale scientific (3; 4) programming models
Lightweight Asynchronous Snapshots for Distributed Dataflows
Distributed stateful stream processing enables the deployment and execution
of large scale continuous computations in the cloud, targeting both low latency
and high throughput. One of the most fundamental challenges of this paradigm is
providing processing guarantees under potential failures. Existing approaches
rely on periodic global state snapshots that can be used for failure recovery.
Those approaches suffer from two main drawbacks. First, they often stall the
overall computation which impacts ingestion. Second, they eagerly persist all
records in transit along with the operation states which results in larger
snapshots than required. In this work we propose Asynchronous Barrier
Snapshotting (ABS), a lightweight algorithm suited for modern dataflow
execution engines that minimises space requirements. ABS persists only operator
states on acyclic execution topologies while keeping a minimal record log on
cyclic dataflows. We implemented ABS on Apache Flink, a distributed analytics
engine that supports stateful stream processing. Our evaluation shows that our
algorithm does not have a heavy impact on the execution, maintaining linear
scalability and performing well with frequent snapshots.Comment: 8 pages, 7 figure
A Survey of Checkpointing Algorithms in Mobile Ad Hoc Network
Checkpoint is defined as a fault tolerant technique that is a designated place in a program at which normal processing is interrupted specifically to preserve the status information necessary to allow resumption of processing at a later time. If there is a failure, computation may be restarted from the current checkpoint instead of repeating the computation from beginning. Checkpoint based rollback recovery is one of the widely used technique used in various areas like scientific computing, database, telecommunication and critical applications in distributed and mobile ad hoc network. The mobile ad hoc network architecture is one consisting of a set of self configure mobile hosts capable of communicating with each other without the assistance of base stations. The main problems of this environment are insufficient power and limited storage capacity, so the checkpointing is major challenge in mobile ad hoc network. This paper presents the review of the algorithms, which have been reported for checkpointing approaches in mobile ad hoc network
The cost of recovery protocols in web-based database systems
The cost of recovery protocols is important with respect to system performance during normal operation and failure in terms of overhead, and time taken to recover failed transactions. The cost of recovery protocols for web database systems has not been addressed much. In this paper, we present a quantitative study of cost of recovery protocols. For this purpose, we use an experiment setup to evaluate the performance of two recovery algorithms, namely the, two-phase commit algorithm and log-based algorithm. Our work is a step towards building reliable protocols for web database systems.<br /
Using migratable objects to enhance fault tolerance schemes in supercomputers
Supercomputers have seen an exponential increase in their size in the last two decades. Such a high growth rate is expected to take us to exascale in the timeframe 2018-2022. But, to bring a productive exascale environment about, it is necessary to focus on several key challenges. One of those challenges is fault tolerance. Machines at extreme scale will experience frequent failures and will require the system to avoid or overcome those failures. Various techniques have recently been developed to tolerate failures. The impact of these techniques and their scalability can be substantially enhanced by a parallel programming model called migratable objects. In this paper, we demonstrate how the migratable-objects model facilitates and improves several fault tolerance approaches. Our experimental results on thousands of cores suggest fault tolerance schemes based on migratable objects have low performance overhead and high scalability. Additionally, we present a performance model that predicts a significant benefit of using migratable objects to provide fault tolerance at extreme scale
Space Reclamation for Uncoordinated Checkpointing in Message-Passing Systems
Checkpointing and rollback recovery are techniques that can provide efficient recovery from transient process failures. In a message-passing system, the rollback of a message sender may cause the rollback of the corresponding receiver, and the system needs to roll back to a consistent set of checkpoints called recovery line. If the processes are allowed to take uncoordinated checkpoints, the above rollback propagation may result in the domino effect which prevents recovery line progression. Traditionally, only obsolete checkpoints before the global recovery line can be discarded, and the necessary and sufficient condition for identifying all garbage checkpoints has remained an open problem. A necessary and sufficient condition for achieving optimal garbage collection is derived and it is proved that the number of useful checkpoints is bounded by N(N+1)/2, where N is the number of processes. The approach is based on the maximum-sized antichain model of consistent global checkpoints and the technique of recovery line transformation and decomposition. It is also shown that, for systems requiring message logging to record in-transit messages, the same approach can be used to achieve optimal message log reclamation. As a final topic, a unifying framework is described by considering checkpoint coordination and exploiting piecewise determinism as mechanisms for bounding rollback propagation, and the applicability of the optimal garbage collection algorithm to domino-free recovery protocols is demonstrated
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