**2023 IEEE International Symposium on Workload Characterization (IISWC’23)**

October 1-3, 2023, Ghent, Belgium

**DOI: 10.1109/IISWC59245.2023.00029**

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Progress in High-Performance Computing in general, and High-Performance Graph Processing in particular, is highly dependent on the availability of publicly-accessible, relevant, and realistic data sets.

In this paper, we announce publication of **MS-BioGraphs**, a new family of **publicly-available real-world edge-weighted graph datasets with up to 2.5 trillion edges**, that is, 6.6 times greater than the largest graph published recently.

We briefly review the two main challenges we faced in generating large graph datasets and our solutions, that are, (i) optimizing data structures and algorithms for this multi-step process and (ii) WebGraph parallel compression technique. We also study some characteristics of MS-BioGraphs.

The datasets are available on https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs .

Please visit https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/ for a complete version of this paper.

**Bibtex**

```
@INPROCEEDINGS{10.1109/IISWC59245.2023.00029,
author = {Koohi Esfahani, Mohsen and Boldi, Paolo and Vandierendonck, Hans and Kilpatrick, Peter and Vigna, Sebastiano},
booktitle={2023 IEEE International Symposium on Workload Characterization (IISWC'23)},
title={Dataset Announcement: {MS-BioGraphs}, Trillion-Scale Public Real-World Sequence Similarity Graphs},
year={2023},
volume={},
number={},
pages={},
location={Belgium, Ghent},
publisher={IEEE Computer Society},
doi={10.1109/IISWC59245.2023.00029}
}
```

**MS-BioGraphs**

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