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117 Publications


2018 | Published | Conference Paper | IST-REx-ID: 5963 | OA
Relaxed schedulers can efficiently parallelize iterative algorithms
D.-A. Alistarh, T.A. Brown, J. Kopinsky, G. Nadiradze, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 377–386.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 5964 | OA
Brief Announcement: Performance prediction for coarse-grained locking
V. Aksenov, D.-A. Alistarh, P. Kuznetsov, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 411–413.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

2018 | Published | Journal Article | IST-REx-ID: 76 | OA
Near-optimal self-stabilising counting and firing squads
C. Lenzen, J. Rybicki, Distributed Computing (2018).
[Published Version] View | Files available | DOI | WoS
 

2018 | Published | Conference Paper | IST-REx-ID: 7812 | OA
Model compression via distillation and quantization
A. Polino, R. Pascanu, D.-A. Alistarh, in:, 6th International Conference on Learning Representations, 2018.
[Published Version] View | Files available | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 85 | OA
Snapshot based synchronization: A fast replacement for Hand-over-Hand locking
E. Gilad, T.A. Brown, M. Oskin, Y. Etsion, in:, Springer, 2018, pp. 465–479.
[Preprint] View | Files available | DOI | WoS
 

2018 | Published | Conference Paper | IST-REx-ID: 5965 | OA
Distributionally linearizable data structures
D.-A. Alistarh, T.A. Brown, J. Kopinsky, J.Z. Li, G. Nadiradze, in:, Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, ACM Press, 2018, pp. 133–142.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 5966 | OA
The transactional conflict problem
D.-A. Alistarh, S.K. Haider, R. Kübler, G. Nadiradze, in:, Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, ACM Press, 2018, pp. 383–392.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2018 | Published | Journal Article | IST-REx-ID: 6001
ThreadScan: Automatic and scalable memory reclamation
D.-A. Alistarh, W. Leiserson, A. Matveev, N. Shavit, ACM Transactions on Parallel Computing 4 (2018).
View | Files available | DOI
 

2018 | Published | Conference Paper | IST-REx-ID: 6031
Fast quantized arithmetic on x86: Trading compute for data movement
A. Stojanov, T.M. Smith, D.-A. Alistarh, M. Puschel, in:, 2018 IEEE International Workshop on Signal Processing Systems, IEEE, 2018.
View | DOI | WoS
 

2018 | Published | Conference Paper | IST-REx-ID: 6558 | OA
Byzantine stochastic gradient descent
D.-A. Alistarh, Z. Allen-Zhu, J. Li, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2018, pp. 4613–4623.
[Published Version] View | Download Published Version (ext.) | WoS | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 6589 | OA
The convergence of sparsified gradient methods
D.-A. Alistarh, T. Hoefler, M. Johansson, N.H. Konstantinov, S. Khirirat, C. Renggli, in:, Advances in Neural Information Processing Systems 31, Neural Information Processing Systems Foundation, 2018, pp. 5973–5983.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 7116 | OA
Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study
D. Grubic, L. Tam, D.-A. Alistarh, C. Zhang, in:, Proceedings of the 21st International Conference on Extending Database Technology, OpenProceedings, 2018, pp. 145–156.
[Published Version] View | Files available | DOI
 

2018 | Published | Conference Paper | IST-REx-ID: 7123 | OA
Space-optimal majority in population protocols
D.-A. Alistarh, J. Aspnes, R. Gelashvili, in:, Proceedings of the 29th Annual ACM-SIAM Symposium on Discrete Algorithms, ACM, 2018, pp. 2221–2239.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2017 | Published | Conference Paper | IST-REx-ID: 431 | OA
QSGD: Communication-efficient SGD via gradient quantization and encoding
D.-A. Alistarh, D. Grubic, J. Li, R. Tomioka, M. Vojnović, in:, Neural Information Processing Systems Foundation, 2017, pp. 1710–1721.
[Submitted Version] View | Download Submitted Version (ext.) | arXiv
 

2017 | Published | Conference Paper | IST-REx-ID: 432 | OA
ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning
H. Zhang, J. Li, K. Kara, D.-A. Alistarh, J. Liu, C. Zhang, in:, Proceedings of Machine Learning Research, ML Research Press, 2017, pp. 4035–4043.
[Submitted Version] View | Files available
 

2017 | Published | Conference Paper | IST-REx-ID: 487
Towards unlicensed cellular networks in TV white spaces
G. Baig, B. Radunovic, D.-A. Alistarh, M. Balkwill, T. Karagiannis, L. Qiu, in:, Proceedings of the 2017 13th International Conference on Emerging Networking EXperiments and Technologies, ACM, 2017, pp. 2–14.
View | DOI
 

2017 | Published | Conference Paper | IST-REx-ID: 791 | OA
The power of choice in priority scheduling
D.-A. Alistarh, J. Kopinsky, J. Li, G. Nadiradze, in:, Proceedings of the ACM Symposium on Principles of Distributed Computing, ACM, 2017, pp. 283–292.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

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