Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
121 Publications
2018 | Conference Paper | IST-REx-ID: 7116 | 
Grubic, D., Tam, L., Alistarh, D.-A., & Zhang, C. (2018). Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study. In Proceedings of the 21st International Conference on Extending Database Technology (pp. 145–156). Vienna, Austria: OpenProceedings. https://doi.org/10.5441/002/EDBT.2018.14
[Published Version]
View
| Files available
| DOI
2018 | Journal Article | IST-REx-ID: 6001
Alistarh, D.-A., Leiserson, W., Matveev, A., & Shavit, N. (2018). ThreadScan: Automatic and scalable memory reclamation. ACM Transactions on Parallel Computing. Association for Computing Machinery. https://doi.org/10.1145/3201897
View
| Files available
| DOI
2018 | Conference Paper | IST-REx-ID: 7812 |
Polino, A., Pascanu, R., & Alistarh, D.-A. (2018). Model compression via distillation and quantization. In 6th International Conference on Learning Representations. Vancouver, Canada.
[Published Version]
View
| Files available
| arXiv
2018 | Conference Paper | IST-REx-ID: 397
Arbel Raviv, M., & Brown, T. A. (2018). Harnessing epoch-based reclamation for efficient range queries (Vol. 53, pp. 14–27). Presented at the PPoPP: Principles and Practice of Parallel Programming, Vienna, Austria: ACM. https://doi.org/10.1145/3178487.3178489
View
| DOI
| WoS
2018 | Journal Article | IST-REx-ID: 43 |
Rybicki, J., Kisdi, E., & Anttila, J. (2018). Model of bacterial toxin-dependent pathogenesis explains infective dose. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1721061115
[Submitted Version]
View
| Files available
| DOI
| WoS
2018 | Journal Article | IST-REx-ID: 76 |
Lenzen, C., & Rybicki, J. (2018). Near-optimal self-stabilising counting and firing squads. Distributed Computing. Springer. https://doi.org/10.1007/s00446-018-0342-6
[Published Version]
View
| Files available
| DOI
| WoS
2018 | Conference Paper | IST-REx-ID: 85 |
Gilad, E., Brown, T. A., Oskin, M., & Etsion, Y. (2018). Snapshot based synchronization: A fast replacement for Hand-over-Hand locking (Vol. 11014, pp. 465–479). Presented at the Euro-Par: European Conference on Parallel Processing, Turin, Italy: Springer. https://doi.org/10.1007/978-3-319-96983-1_33
[Preprint]
View
| Files available
| DOI
| WoS
2018 | Conference Paper | IST-REx-ID: 5962 |
Alistarh, D.-A., De Sa, C., & Konstantinov, N. H. (2018). The convergence of stochastic gradient descent in asynchronous shared memory. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18 (pp. 169–178). Egham, United Kingdom: ACM Press. https://doi.org/10.1145/3212734.3212763
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 5961
Alistarh, D.-A. (2018). A brief tutorial on distributed and concurrent machine learning. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18 (pp. 487–488). Egham, United Kingdom: ACM Press. https://doi.org/10.1145/3212734.3212798
View
| DOI
| WoS
2018 | Conference Paper | IST-REx-ID: 5963 |
Alistarh, D.-A., Brown, T. A., Kopinsky, J., & Nadiradze, G. (2018). Relaxed schedulers can efficiently parallelize iterative algorithms. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18 (pp. 377–386). Egham, United Kingdom: ACM Press. https://doi.org/10.1145/3212734.3212756
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv