A MapReduce scratchpad memory for multi-core cloud computing applications

Kachris, Christoforos; Sirakoulis, Georgios Ch.; Soudris, Dimitrios

doi:10.1016/j.micpro.2015.08.007

Cited by 9 publications

(3 citation statements)

References 13 publications

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“…for the Spark environment [818]. Other big data frameworks accelerated by FPGAs are Apache Flink in heterogeneous hardware [819], Apache Mesos for cluster management for the HetSpark framework [820] and Phoenix MapReduce in multi-core FPGA's systems [821].…”

Section: Spark (Also Known As Apache Sparkmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.

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Section: Spark (Also Known As Apache Sparkmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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“…Hadoop addresses large data of text files by default [35] . But it saves the image files and processing method differently.…”

Section: Block (2 D ) 2 Pca Algorithm Implementationmentioning

confidence: 99%

The improved (2 D ) 2 PCA algorithm and its parallel implementation based on image block

Song

Chen

Wei

et al. 2016

Microprocessors and Microsystems

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“…Christoforos Kachris, Georgios Ch. Sirakoulis and Dimitrios Soudris presented a novel scratchpad memory architecture that was used accelerate MapReduce applications by indexing and processing the key/value pairs [18]. Shin-Jer Yang and Yi-Ru Chen conducted a thorough research on one of the critical technologies in cloud computing, the MapReduce programming model [19].…”

Section: Introductionmentioning

confidence: 99%