Planned intervention: On Thursday March 28th 07:00 UTC Zenodo will be unavailable for up to 5 minutes to perform a database upgrade.
Published February 24, 2018 | Version 1
Software Open

Grazelle-PPoPP18

  • 1. Stanford University
  • 2. University of California, Santa Cruz

Description

Grazelle is a high-performance hybrid (push-based and pull-based) graph processing framework targeting a single machine containing or more x86-64-based processors. It is the embodiment of the two optimization strategies described in the PPoPP 2018 paper Making Pull-Based Graph Processing Performant.

The content of this repository is intended to support the results presented in the aforementioned paper. It contains all the source code and documentation required to build and run Grazelle as configured for each experiment presented in the paper as well as pre-converted ready-to-use versions of the datasets used in the evaluation.

Files

Grazelle-PPoPP18.zip

Files (39.0 GB)

Name Size Download all
md5:45971aabaaef46eee8b624e87ba5bec8
65.8 MB Download
md5:aa0fdbada2168a16856cc6c40847d01b
65.3 MB Download
md5:2d054051587e411ae3acfd672cc7db6a
183.0 MB Download
md5:69ae66521af095fff0f9bd2a3dc94cd4
182.9 MB Download
md5:e49eb84a1ff1a141507f91a01f203655
7.7 GB Download
md5:2b70cecb248240deab0599f74d711524
6.9 GB Download
md5:ee2d8a9ecb25c3f44ddce5f0e0145f1d
102.8 kB Preview Download
md5:fe82462ec6e2bc4e60e9a0c78600a214
213.4 MB Download
md5:a0f812fd939c827e21c1a41c8da56375
215.2 MB Download
md5:6a07b589171c7fbeee7c6f0201f80519
4.2 GB Download
md5:3e2b886f1506ac0530762c35eab35648
4.3 GB Download
md5:d953152569a76ad258b24e4df96b59ea
7.7 GB Download
md5:017699806ad40f19bcfaee30f35d90b9
7.4 GB Download

Additional details

Related works

Is supplement to
10.1145/3178487.3178506 (DOI)

References

  • Jure Leskovec and Andrej Krevl. 2014. SNAP Datasets: Stanford Large Network Dataset Collection. http://snap.stanford.edu/data. (2014).
  • Camil Demetrescu. 2010. 9th DIMACS Implementation Challenge. http://www.dis.uniroma1.it/challenge9/download.shtml. (2010).
  • Paolo Boldi, Marco Rosa, Massimo Santini, and Sebastiano Vigna. 2011. Layered Label Propagation: A MultiResolution Coordinate-Free Ordering for Compressing Social Networks. In WWW '11. ACM, 587–596.
  • Paolo Boldi and Sebastiano Vigna. 2004. The WebGraph Framework I: Compression Techniques. In WWW '04. ACM, 595–601.