"Receiver makes right" data conversion in PVM

Zhou, Honbo; Geist, Al

doi:10.1109/pccc.1995.472453

Cited by 11 publications

(3 citation statements)

References 6 publications

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“…In addition, the technique of saving in the lowest precision of the group requires knowledge of the group members before checkpointing takes place.  Receiver makes right technique [39]: the originator of the data simply checkpoints the data in its own precision. This technique has been used in [35].…”

Section: Portabilitymentioning

confidence: 99%

Abstraction Checkpointing Levels: Problems and Solutions

Meroufel¹,

Belalem²

2014

IJC

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A common approach to guarantee an acceptable level of fault tolerance in scientific computing is the checkpointing. In this strategy: when a task fails, it is allowed to be restarted from the recently checked pointed state rather than from the beginning, which reduces the system loss and ensures the reliability. Several systems use the checkpointing to ensure the fault tolerance such as HPC, distributed discrete event simulation and Clouds. The literature proposes several classifications of checkpointing techniques using different metrics and criteria. In this paper we focus on the classification based on abstraction level. In this classification the checkpointing is categorized into two principal types: application level and system level. Each of these levels has its advantages and suffers from many problems. The difference between our present paper and the others surveys proposed in the literature is that: in this paper we will study each level in details. We will also study and analyze some works that propose solutions to solve the problems and exceed the limits of each abstraction level.

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Section: Portabilitymentioning

confidence: 99%

Abstraction Checkpointing Levels: Problems and Solutions

Meroufel¹,

Belalem²

2014

IJC

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“…One of the most popular data conversion schemes, called External Data Representations (XDR) [37], exploits this strategy. Translating the data at the destination, as in the Receiver Makes Right (RMR) [38] strategy, is commonly preferred to the choice of doing it at the origin, because when both architectures are equal the translation step can be avoided. There are also variants of those schemes, such as coarse-grain tagged receiver makes right (CGT-RMR), which is a tagged RMR version with improved ease of use and data conversion speed for large data chunks [39].…”

Section: Data Serialization and De-serializationmentioning

confidence: 99%

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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“…And each platform is only equipped with a set of routines for conversion between local and intermediate formats. Zhou and Geist [11] proposed an asymmetric data conversion technique, called "receiver makes it right" (RMR), where data conversion is performed only on the receiver side. Thus, the receiver should be able to convert and accept data from all other machines.…”

Section: Heterogeneitymentioning

confidence: 99%