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Graph filter banks allow the wavelet transform to be extended for processing graph signals.
Instead of join processing, graph exploration is used to boost the system's performance.
Finally, in modern SPEs windows are not special entities, but rather one of the possible operators that compose the processing graph.
Similar with the Fourier transform in classical signal processing, graph Fourier transform performs the expansion of a graph signal into a Laplacian eigenvector basis of signals [14].
At the same time, a complete modeling of the execution semantics of modern SPEs should also take into account the topology of the processing graph.
In this work we propose a self-adaptive processing graph that provides elasticity and scalability by automatically increasing or decreasing the number of processing operators to improve performance and resource utilization of the system.
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We build minimal processing graphs that include a single source and a single window operator w that outputs the entire content of w.
Differently from Neo4j, GraphChi has not been conceived for querying large graph-structured databases, but for efficiently processing graphs stored in secondary memory.
The data preprocessing and network analysis modules include two established packages, Hemodynamic Evoked Response (Homer) and Graph-Theoretical Network Analysis (Gretna), for fNIRS data processing and graph theory-based network analysis, respectively.
By further processing this graph, we obtain an edge-labeled directed multi-graph that reveals the independence and causality information of the transitions with respect to the flow of specific resources between reactions.
The spatiotemporal compression is a key solution for processing big graph data in the cloud environment.
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