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121 Publications

2018 | Conference Paper | IST-REx-ID: 7116 | OA
Grubic, Demjan, et al. “Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study.” Proceedings of the 21st International Conference on Extending Database Technology, OpenProceedings, 2018, pp. 145–56, doi:10.5441/002/EDBT.2018.14.
[Published Version] View | Files available | DOI
 
2018 | Journal Article | IST-REx-ID: 6001
Alistarh, Dan-Adrian, et al. “ThreadScan: Automatic and Scalable Memory Reclamation.” ACM Transactions on Parallel Computing, vol. 4, no. 4, 18, Association for Computing Machinery, 2018, doi:10.1145/3201897.
View | Files available | DOI
 
2018 | Conference Paper | IST-REx-ID: 7812 | OA
Polino, Antonio, et al. “Model Compression via Distillation and Quantization.” 6th International Conference on Learning Representations, 2018.
[Published Version] View | Files available | arXiv
 
2018 | Conference Paper | IST-REx-ID: 397
Arbel Raviv, Maya, and Trevor A. Brown. Harnessing Epoch-Based Reclamation for Efficient Range Queries. Vol. 53, no. 1, ACM, 2018, pp. 14–27, doi:10.1145/3178487.3178489.
View | DOI | WoS
 
2018 | Journal Article | IST-REx-ID: 43 | OA
Rybicki, Joel, et al. “Model of Bacterial Toxin-Dependent Pathogenesis Explains Infective Dose.” PNAS, vol. 115, no. 42, National Academy of Sciences, 2018, pp. 10690–95, doi:10.1073/pnas.1721061115.
[Submitted Version] View | Files available | DOI | WoS
 
2018 | Journal Article | IST-REx-ID: 76 | OA
Lenzen, Christoph, and Joel Rybicki. “Near-Optimal Self-Stabilising Counting and Firing Squads.” Distributed Computing, Springer, 2018, doi:10.1007/s00446-018-0342-6.
[Published Version] View | Files available | DOI | WoS
 
2018 | Conference Paper | IST-REx-ID: 85 | OA
Gilad, Eran, et al. Snapshot Based Synchronization: A Fast Replacement for Hand-over-Hand Locking. Vol. 11014, Springer, 2018, pp. 465–79, doi:10.1007/978-3-319-96983-1_33.
[Preprint] View | Files available | DOI | WoS
 
2018 | Conference Paper | IST-REx-ID: 5962 | OA
Alistarh, Dan-Adrian, et al. “The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 169–78, doi:10.1145/3212734.3212763.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2018 | Conference Paper | IST-REx-ID: 5961
Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine Learning.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 487–88, doi:10.1145/3212734.3212798.
View | DOI | WoS
 
2018 | Conference Paper | IST-REx-ID: 5963 | OA
Alistarh, Dan-Adrian, et al. “Relaxed Schedulers Can Efficiently Parallelize Iterative Algorithms.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 377–86, doi:10.1145/3212734.3212756.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

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