Abstract: Many recently proposed graph-processing frameworks utilize powerful computer clusters with dozens of cores to process massive graphs.
Abstract—Many recently proposed graph-processing frame- works utilize powerful computer clusters with dozens of cores to process massive graphs.
Massive Graph Processing on Nanocomputers. Idea: Write custom implementations of iterative graph algorithms for tiny, cheap computers like the Raspberry Pi ...
Many recently proposed graph-processing frameworks utilize powerful computer clusters with dozens of cores to process massive graphs.
... Massive Graph Processing on Nanocomputers}, author={Bryan Rainey and David F. ... computer, GraphChi can process over one hundred thousand graph updates ...
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Bryan Rainey, David F. Gleich : Massive graph processing on nanocomputers. IEEE BigData 2016: 3326-3335. [+][–]. Coauthor network. maximize.
Apr 8, 2024 · In this work we investigate how we can get the best possible performance on commodity systems from graphs that cannot fit into DRAM by ...
Missing: Massive nanocomputers.
May 31, 2018 · Caption: The researchers were able to process several large graphs — with up to 3.5 billion nodes and 128 billion connecting lines — by plugging ...
Missing: nanocomputers. | Show results with:nanocomputers.
ABSTRACT. Graph workloads are critical in many areas. Unfortunately, graph sizes have been increasing faster than DRAM capacity. As a re- sult, large-scale ...
Missing: nanocomputers. | Show results with:nanocomputers.