Process/thread migration and checkpointing in heterogeneous distributed systems

Jiang, Hai; Chaudhary, Vipin

doi:10.1109/hicss.2004.1265665

Cited by 14 publications

(18 citation statements)

References 17 publications

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“…[33], migration points [34], poll points [24,35], preemption points [36], and adaptation points [12]. In this text we shall call them migration points.…”

Section: Heterogeneous Migration Of Computationsmentioning

confidence: 99%

“…Also third-party library calls must be considered [12], as the migration schemes may not be capable of detecting the existence of their memory blocks and pointers.…”

Section: Ansi-cmentioning

confidence: 99%

“…MigThread [12] supports both process and (Posix) threads migration in C. It consists of a preprocessor and a runtime support module. The pre-processor acts at compile time, modifying the source code to include various tasks such as information collection, create tags for data structures and memory blocks, and detect and overcome unsafe cases.…”

Section: User-code Pre-processingmentioning

confidence: 99%

“…Indeed, persistence of a computation can be seen as the problem of moving it to the same location, or, otherwise, computation mobility can be achieved through the restoration of a computation persisted in a different host. Several techniques for capturing and restoring state are intended for both checkpointing and migration [12,16,24]. Checkpointing an application is the act of saving the application state in persistent storage in a form from which it can be restarted later.…”

Section: Heterogeneous Migration Of Computationsmentioning

confidence: 99%

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State of the art in heterogeneous strong migration of computations

Milanés

Rodríguez

Schulze

2007

Concurrency and Computation

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SUMMARYThe emergence of new environments, such as grids and mobile devices, poses new requirements for programming systems and models. Migration techniques, which have been extensively studied but not widely used, gain a chance to rise in light of these requirements. This survey reviews a particular case of migration that fits well into those environments-that is, heterogeneous strong migration of running computations at application level. We approach it from an implementation point of view, commenting on related issues and current solutions. We discuss the strong influence that language support for migration has on implementation issues, and the advantages that a higher level of support would represent for the portability and performance of the application, as well as in terms of control and flexibility for the programmer.

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“…[33], migration points [34], poll points [24,35], preemption points [36], and adaptation points [12]. In this text we shall call them migration points.…”

Section: Heterogeneous Migration Of Computationsmentioning

confidence: 99%

“…Also third-party library calls must be considered [12], as the migration schemes may not be capable of detecting the existence of their memory blocks and pointers.…”

Section: Ansi-cmentioning

confidence: 99%

Section: User-code Pre-processingmentioning

confidence: 99%

Section: Heterogeneous Migration Of Computationsmentioning

confidence: 99%

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State of the art in heterogeneous strong migration of computations

Milanés

Rodríguez

Schulze

2007

Concurrency and Computation

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“…If a failure is likely to occur on a computing core on which a job is being executed, then it is necessary to be able to move (migrate) the job onto a reliable core [21]. Such mechanisms are not readily available.…”

Section: Introductionmentioning

confidence: 99%

Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches

Varghese

McKee

Alexandrov

2014

Computers in Biology and Medicine

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Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches Varghese, B., McKee, G., & Alexandrov, V. (2014). Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches. General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights.Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the Research Portal that you believe breaches copyright or violates any law, please contact openaccess@qub.ac.uk. Background: Large-scale biological jobs on high-performance computing systems require manual intervention if one or more computing cores on which they execute fail. This places not only a cost on the maintenance of the job, but also a cost on the time taken for reinstating the job and the risk of losing data and execution accomplished by the job before it failed. Approaches which can proactively detect computing core failures and take action to relocate the computing core's job onto reliable cores can make a significant step towards automating fault tolerance.Method: This paper describes an experimental investigation into the use of multi-agent approaches for fault tolerance. Two approaches are studied, the first at the job level and the second at the core level. The approaches are investigated for single core failure scenarios that can occur in the execution of parallel reduction algorithms on computer clusters. A third approach is proposed that incorporates multi-agent technology both at the job and core level. Experiments are pursued in the context of genome searching, a popular computational biology application.Result: The key conclusion is that the approaches proposed are feasible for automating fault tolerance in high-performance computing systems with minimal human intervention. In a typical experiment in which the fault tolerance is studied, centralised and decentralised checkpointing approaches on an average add 90% to the actual time for executing the job. On the other hand, in the same experiment the multi-agent approaches add only 10% to the overall execution time.high-performance computing | fault tolerance | biological jobs | multi-agents | seamless execution | checkpoint Introduction T he scale of resources and computations required for executing large-scale biological jobs are significantly increasing [1,2]. With this increase the resultant number of failures while running these jobs will also increase and the time between failures will decrease [3,4,5]. It is not desirable to have to restart a job from the beginning if it has been executin...

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