MapReduce with Components for Processing Big Graphs

Rezende, Cenez Araújo; Carvalho, Francisco Heron de

doi:10.1109/wscad.2018.00026

Cited by 1 publication

(4 citation statements)

References 24 publications

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“…A framework of components for MapReduce computations has been designed for HPC Shelf [11]. It comprises a pair of component types of kind computation, named Mapper and Reducer, which represent mapping and reducing agents, and another pair of component types of kind connector, named Splitter and Shuffler, which intermediate communication of KV/KMV-pairs among mappers, reducers and data sources.…”

Section: Parallel Computing Systems Through An Example: Mapreducementioning

confidence: 99%

“…HTS (Hash Type System) [12] is a type system firstly introduced by HPE (Hash Programming Environment) [8,13], the first reference implementation of the Hash component model, for the following purposes:…”

Section: Contextual Contractsmentioning

confidence: 99%

“…15 reports execution times for this certification case study, by varying the number of processing nodes and cores per node involved in the execution of the tactical component ISP. 11 For simplicity, the sequential time has been calculated outside HPC Shelf through sequential calls to the verification tool, and collected through a shell script program. This is a reasonable assumption since the interest, in this performance evaluation, is to isolate the impact of parallel certification system deployment in the overall certification time.…”

Section: Certifying Montage Componentsmentioning

confidence: 99%

“…They do not present mapping stages. These systems have been adapted from case studies on the implementation of graph calculations, respectively triangle enumeration and single-source shortest path (SSSP), by using Gust, a framework for processing big graphs derived from the MapReduce framework [11].…”

Section: Mapreduce Workflowsmentioning

confidence: 99%

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A component-based framework for certification of components in a cloud of HPC services

Dantas

Carvalho

Barbosa

2020

Science of Computer Programming

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HPC Shelf is a proposal of a cloud computing platform to provide component-oriented services for High Performance Computing (HPC) applications. This paper presents a Verification-as-a-Service (VaaS) framework for component certification on HPC Shelf. Certification is aimed at providing higher confidence that components of parallel computing systems of HPC Shelf behave as expected according to one or more requirements expressed in their contracts. To this end, new abstractions are introduced, starting with certifier components. They are designed to inspect other components and verify them for different types of functional, non-functional and behavioral requirements. The certification framework is naturally based on parallel computing techniques to speed up verification tasks.

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Section: Parallel Computing Systems Through An Example: Mapreducementioning

confidence: 99%