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DTSTAMP:20210808T235331Z
LOCATION:Room A
DTSTART;TZID=America/Chicago:20210811T103000
DTEND;TZID=America/Chicago:20210811T113000
UID:icpp_ICPP 2021_sess112@linklings.com
SUMMARY:4A: Graph Computing
DESCRIPTION:Conference Paper\n\nCommunication Avoiding All-Pairs Shortest
Paths Algorithm for Sparse graphs\n\nZhu, Hua, Jin\n\nIn this paper, we p
ropose a parallel algorithm for computing all-pairs shortest paths (APSP)
for sparse graphs on the distributed memory system with $p$ processors.
To exploit the graph sparsity, we first preprocess the graph by utilizing
several known algorithmic techniques in linear algebra such...\n\n--------
-------------\nAscetic: Enhancing Cross-Iterations Data Efficiency in Ou
t-of-Memory Graph Processing on GPUs\n\nTang, Zhao, Wang, Gong, Zhang...\n
\nGraph analytics are widely used in real-world applications, and GPUs are
major accelerators for such applications.\nHowever, as graph sizes become
significantly larger than the capacity of GPU memory, the performance can
degrade significantly due to the heavy overhead moving large amount of da
ta betw...\n\n---------------------\nExploiting in-Hub Temporal Locality i
n SpMV-based Graph Processing\n\nKoohi Esfahani, Kilpatrick, Vandierendonc
k\n\nThe skewed degree distribution of real-world graphs is the main sourc
e of poor locality in graph processing, especially in the pull traversal o
rder of a graph. This paper argues that different vertices in power-law gr
aphs have different locality characteristics and therefore the traversal m
ethod sho...\n\n---------------------\nAn Edge-Fencing Strategy for Optimi
zing SSSP Computations on Large-Scale Graphs\n\nYu, Wang, Luo\n\nThe Singl
e-Source Shortest Path (SSSP) problem is to compute the shortest distances
in a weighted graph from a source vertex to every other vertex. This pape
r focuses on parallel efficiency and scalability of SSSP computations on l
arge-scale graphs. We propose an edge-fencing strategy to customize a...\n
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