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174 Publications
2018 |
Published |
Conference Paper |
IST-REx-ID: 6031
A. Stojanov, T. M. Smith, D.-A. Alistarh, and M. Puschel, “Fast quantized arithmetic on x86: Trading compute for data movement,” in 2018 IEEE International Workshop on Signal Processing Systems, Cape Town, South Africa, 2018, vol. 2018–October.
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| DOI
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2018 |
Published |
Journal Article |
IST-REx-ID: 76 |
C. Lenzen and J. Rybicki, “Near-optimal self-stabilising counting and firing squads,” Distributed Computing. Springer, 2018.
[Published Version]
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2018 |
Published |
Conference Paper |
IST-REx-ID: 7812 |
A. Polino, R. Pascanu, and D.-A. Alistarh, “Model compression via distillation and quantization,” in 6th International Conference on Learning Representations, Vancouver, Canada, 2018.
[Published Version]
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 85 |
E. Gilad, T. A. Brown, M. Oskin, and Y. Etsion, “Snapshot based synchronization: A fast replacement for Hand-over-Hand locking,” presented at the Euro-Par: European Conference on Parallel Processing, Turin, Italy, 2018, vol. 11014, pp. 465–479.
[Preprint]
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2018 |
Published |
Conference Paper |
IST-REx-ID: 6558 |
D.-A. Alistarh, Z. Allen-Zhu, and J. Li, “Byzantine stochastic gradient descent,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2018, vol. 2018, pp. 4613–4623.
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| WoS
| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 7116 |
D. Grubic, L. Tam, D.-A. Alistarh, and C. Zhang, “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, Vienna, Austria, 2018, pp. 145–156.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 7123 |
D.-A. Alistarh, J. Aspnes, and R. Gelashvili, “Space-optimal majority in population protocols,” in Proceedings of the 29th Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, LA, United States, 2018, pp. 2221–2239.
[Preprint]
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| arXiv
2018 |
Published |
Journal Article |
IST-REx-ID: 43 |
J. Rybicki, E. Kisdi, and J. Anttila, “Model of bacterial toxin-dependent pathogenesis explains infective dose,” Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 42. National Academy of Sciences, pp. 10690–10695, 2018.
[Submitted Version]
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2018 |
Published |
Conference Paper |
IST-REx-ID: 6589 |
D.-A. Alistarh, T. Hoefler, M. Johansson, N. H. Konstantinov, S. Khirirat, and C. Renggli, “The convergence of sparsified gradient methods,” in 32nd Conference on Neural Information Processing Systems, Montreal, Canada, 2018, pp. 5973–5983.
[Preprint]
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 487
G. Baig, B. Radunovic, D.-A. Alistarh, M. Balkwill, T. Karagiannis, and L. Qiu, “Towards unlicensed cellular networks in TV white spaces,” in Proceedings of the 2017 13th International Conference on emerging Networking EXperiments and Technologies, Incheon, South Korea, 2017, pp. 2–14.
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2017 |
Published |
Conference Paper |
IST-REx-ID: 791 |
D.-A. Alistarh, J. Kopinsky, J. Li, and G. Nadiradze, “The power of choice in priority scheduling,” in Proceedings of the ACM Symposium on Principles of Distributed Computing, Washington, WA, USA, 2017, vol. Part F129314, pp. 283–292.
[Submitted Version]
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 431 |
D.-A. Alistarh, D. Grubic, J. Li, R. Tomioka, and M. Vojnović, “QSGD: Communication-efficient SGD via gradient quantization and encoding,” presented at the NIPS: Neural Information Processing System, Long Beach, CA, United States, 2017, vol. 2017, pp. 1710–1721.
[Submitted Version]
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 432 |
H. Zhang, J. Li, K. Kara, D.-A. Alistarh, J. Liu, and C. Zhang, “ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning,” in Proceedings of Machine Learning Research, Sydney, Australia, 2017, vol. 70, pp. 4035–4043.
[Submitted Version]
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