Improving Streaming Graph Processing Performance using Input Knowledge

Author:

Basak Abanti1,Qu Zheng1,Lin Jilan2,Alameldeen Alaa R.3,Chishti Zeshan4,Ding Yufei1,Xie Yuan1

Affiliation:

1. University of California, Santa Barbara, United States of America

2. University of California, Santa Barbara, USA

3. Simon Fraser University, Canada

4. Intel, United States of America

Publisher

ACM

Reference72 articles.

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2. [n. d.]. Laboratory for Web Algorithms. http://law.di.unimi.it/datasets.php. [n. d.]. Laboratory for Web Algorithms. http://law.di.unimi.it/datasets.php.

3. [ 3 ] 2017. https://www.boost.org/doc/libs/1_67_0/libs/sort/doc/html/sort/parallel/parallel_stable_sort.html. [3] 2017. https://www.boost.org/doc/libs/1_67_0/libs/sort/doc/html/sort/parallel/parallel_stable_sort.html.

4. 2019. DARPA ERI: HIVE and Intel PUMA Graph Processor. https://fuse.wikichip.org/news/2611/darpa-eri-hive-and-intel-puma-graph-processor/. 2019. DARPA ERI: HIVE and Intel PUMA Graph Processor. https://fuse.wikichip.org/news/2611/darpa-eri-hive-and-intel-puma-graph-processor/.

5. [ 5 ] 2020. https://graphchallenge.mit.edu/darpa-hive. [5] 2020. https://graphchallenge.mit.edu/darpa-hive.

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