Asynchronous Large-Scale Graph Processing Made Easy
Summary: GRACE separates application logic from execution policies, exposing a BSP-style synchronous API while executing pluggable async policies in the engine. Engine-driven asynchronous execution matches fully-asynchronous convergence while preserving BSP-like scalability and programmability. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Guozhang Wang (Cornell University)
- 2. Wenlei Xie (Cornell University)
- 3. Alan Demers (Cornell University)
- 4. Johannes Gehrke (Cornell University)
BibTeX Citation
@inproceedings{wang_cidr13,
address = {Amsterdam, Netherlands},
series = {{CIDR} '13},
title = {{Asynchronous Large-Scale Graph Processing Made Easy}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Wang, Guozhang and Xie, Wenlei and Demers, Alan and Gehrke, Johannes},
year = {2013}
}
Incoming Citations (Sorted by Pagerank)
Showing 16 of 16 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0012250108 |
| 20 | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2012 | VLDB | 0.00056944564 |
| 372 | HaLoop: Efficient Iterative Data Processing on Large Clusters | 2010 | VLDB | 0.0001981521 |
| 455 | Differential dataflow | 2013 | CIDR | 0.00018133241 |
| 4,047 | Behavioral Simulations in MapReduce | 2010 | VLDB | 6.9380465e-05 |
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