2019 · 17 citations · 20 references
ComputingComputer ScienceHigh-performance ComputingBig Data AnalyticsData ManagementParallel ComputingData ParallelismData PipelinesData-flow AnalysisDataflow ModelingBig Data ArchitectureData-intensive ComputingDataflow ArchitecturesDataflow SemanticsIteration CyclesLarge-scale Data Processing
The dataflow model is gradually becoming the de facto standard for big data applications. While many popular frameworks are built around this model, very little research has been done on understanding its inner workings, which in turn has led to inefficiencies in existing frameworks. It is important to note that understanding the relationship between dataflow and HPC building blocks allows us to address and alleviate many of these fundamental inefficiencies by learning from the extensive research literature in the HPC community. In this paper we present TSet’s, the dataflow abstraction of Twister2, which is a big data framework designed for high-performance dataflow and iterative computations. We discuss the dataflow model adopted by TSet’s and the rationale behind implementing iteration handling at the worker level. Finally, we evaluate TSet’s to show the performance of the framework.
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TensorFlow: A system for large-scale machine learning
Martı́n Abadi, Paul Barham, Jianmin Chen et al. · arXiv (Cornell University) · 2016 · 8.8K citations · Full text
TensorFlow: a system for large-scale machine learning
Martı́n Abadi, Paul Barham, Jianmin Chen et al. · Operating Systems Design and Implementation · 2016 · 6.4K citations
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Matei Zaharia, Reynold Xin, Patrick Wendell et al. · Communications of the ACM · 2016 · 2.3K citations