Distributed Power-law Graph Computing: Theoretical and Empirical Analysis
Authors: Cong Xie, Ling Yan, Wu-Jun Li, Zhihua Zhang
NeurIPS 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Furthermore, empirical results on several large power-law graphs also show that DBH can outperform the state of the art. In this section, empirical evaluation on real and synthetic graphs is used to verify the effectiveness of our DBH method. |
| Researcher Affiliation | Academia | Cong Xie Dept. of Comp. Sci. and Eng. Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240, China xcgoner1108@gmail.com Ling Yan Dept. of Comp. Sci. and Eng. Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240, China yling0718@sjtu.edu.cn Wu-Jun Li National Key Lab. for Novel Software Tech. Dept. of Comp. Sci. and Tech. Nanjing University Nanjing 210023, China liwujun@nju.edu.cn Zhihua Zhang Dept. of Comp. Sci. and Eng. Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240, China zhang-zh@cs.sjtu.edu.cn |
| Pseudocode | Yes | Algorithm 1 Degree-based hashing (DBH) for vertex-cut GP |
| Open Source Code | No | The paper does not provide any explicit statements about the release of source code or links to a code repository for the methodology described. |
| Open Datasets | Yes | The graph datasets used in our experiments include both synthetic and real-world power-law graphs. ... The real-world graphs are shown in Table 1(c). Some of the real-world graphs are the same as those in the experiment of Power Graph. And some additional real-world graphs are from the UF Sparse Matrices Collection [5]. Table 1: Datasets (c) Real-world graphs Alias Graph |V| |E| Tw Twitter [10] 42M 1.47B Arab Arabic-2005 [5] 22M 0.6B Wiki Wiki [2] 5.7M 130M LJ Live Journal [16] 5.4M 79M WG Web Google [12] 0.9M 5.1M |
| Dataset Splits | No | The paper describes the datasets used (synthetic and real-world graphs) but does not provide specific details on how these datasets were split into training, validation, or test sets for reproducibility. |
| Hardware Specification | Yes | The cluster for experiment contains 64 machines connected via 1 GB Ethernet. Each machine has 24 Intel Xeon cores and 96GB of RAM. |
| Software Dependencies | No | The paper does not provide specific software dependency versions (e.g., library names with version numbers) for its implementation. |
| Experiment Setup | Yes | To test the speedup for real applications, we use the total execution time for Page Rank which is forced to take 100 iterations. |