GraphGuess: Approximate Graph Processing System with Adaptive Correction
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-12597-3_18
Reference29 articles.
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2. Ahn, J., Hong, S., Yoo, S., Mutlu, O., Choi, K.: A scalable processing-in-memory accelerator for parallel graph processing. ACM SIGARCH Comput. Archit. News 43(3), 105–117 (2016). https://doi.org/10.1145/2749469.2750386
3. Bernstein, A., et al.: Fully-dynamic graph sparsifiers against an adaptive adversary. arXiv preprint arXiv:2004.08432 (2020)
4. Besta, M., et al.: Slim graph: practical lossy graph compression for approximate graph processing, storage, and analytics. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–25 (2019). https://doi.org/10.1145/3295500.3356182
5. Capelli, L.A., Hu, Z., Zakian, T.A.: iPregel: a combiner-based in-memory shared memory vertex-centric framework. In: Proceedings of the 47th International Conference on Parallel Processing Companion, pp. 1–10 (2018). https://doi.org/10.1145/3229710.3229719
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