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Erik Schultheis

Eldar Kurtic

Andrei Panferov

Dan Alistarh

Jiale Chen

Alexandra Volkova

Vage Egiazarian

Mahdi Nikdan

Soroush Tabesh

Sergei Pankratov

Ionut-Vlad Modoranu

Peter Davies

Sidak Singh

Roberto Lopez Castro

Ilia Markov

Alexander Fedorov

Sharareh Alipour

Vitalii Aksenov

Bapi Chatterjee

Janne Korhonen

Joel Rybicki

Elias Frantar

Sokolova, Mariia

Mher Safaryan

Martin Töpfer

Alexandra Krumes

Elvir Crncevic

Trevor Brown

Giorgi Nadiradze



168 Publications

2019 | Published | Conference Paper | IST-REx-ID: 7201 | OA
SparCML: High-performance sparse communication for machine learning
C. Renggli, S. Ashkboos, M. Aghagolzadeh, D.-A. Alistarh, T. Hoefler, in:, International Conference for High Performance Computing, Networking, Storage and Analysis, SC, ACM, 2019.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Published | Conference Paper | IST-REx-ID: 7228
Scalable FIFO channels for programming via communicating sequential processes
N. Koval, D.-A. Alistarh, R. Elizarov, in:, 25th Anniversary of Euro-Par, Springer Nature, 2019, pp. 317–333.
View | DOI | WoS
 
2019 | Published | Conference Paper | IST-REx-ID: 7437 | OA
Distributed learning over unreliable networks
C. Yu, H. Tang, C. Renggli, S. Kassing, A. Singla, D.-A. Alistarh, C. Zhang, J. Liu, in:, 36th International Conference on Machine Learning, ICML 2019, IMLS, 2019, pp. 12481–12512.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 
2019 | Published | Conference Paper | IST-REx-ID: 7542 | OA
Powerset convolutional neural networks
C. Wendler, D.-A. Alistarh, M. Püschel, in:, Neural Information Processing Systems Foundation, 2019, pp. 927–938.
[Published Version] View | Download Published Version (ext.) | WoS | arXiv
 
2019 | Published | Conference Paper | IST-REx-ID: 6673 | OA
Efficiency guarantees for parallel incremental algorithms under relaxed schedulers
D.-A. Alistarh, G. Nadiradze, N. Koval, in:, 31st ACM Symposium on Parallelism in Algorithms and Architectures, ACM, 2019, pp. 145–154.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Published | Journal Article | IST-REx-ID: 7214 | OA
Recovering rearranged cancer chromosomes from karyotype graphs
S. Aganezov, I. Zban, V. Aksenov, N. Alexeev, M.C. Schatz, BMC Bioinformatics 20 (2019).
[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: 5961
A brief tutorial on distributed and concurrent machine learning
D.-A. Alistarh, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM, 2018, pp. 487–488.
View | DOI | WoS
 
2018 | Published | Conference Paper | IST-REx-ID: 5962 | OA
The convergence of stochastic gradient descent in asynchronous shared memory
D.-A. Alistarh, C. De Sa, N.H. Konstantinov, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM, 2018, pp. 169–178.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
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, 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, 2018, pp. 411–413.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
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, 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
 
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: 397
Harnessing epoch-based reclamation for efficient range queries
M. Arbel Raviv, T.A. Brown, in:, ACM, 2018, pp. 14–27.
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