Elastic Coordination for Scalable Machine Learning

Project Period: 2019-03-01 – 2024-02-29
Funder: EC/H2020
Acronym
ScaleML
Principal Investigator
Department(s)
Grant Number
805223
Funder
EC/H2020

44 Publications

2024 | Published | Thesis | IST-REx-ID: 17485 | OA
Compressing large neural networks : Algorithms, systems and scaling laws
E. Frantar, Compressing Large Neural Networks : Algorithms, Systems and Scaling Laws, Institute of Science and Technology Austria, 2024.
[Published Version] View | Files available | DOI
 
2024 | Published | Thesis | IST-REx-ID: 17490 | OA
Communication-efficient distributed training of deep neural networks: An algorithms and systems perspective
I. Markov, Communication-Efficient Distributed Training of Deep Neural Networks: An Algorithms and Systems Perspective, Institute of Science and Technology Austria, 2024.
[Published Version] View | Files available | DOI
 
2023 | Published | Journal Article | IST-REx-ID: 14364 | OA
Why extension-based proofs fail
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, L. Zhu, SIAM Journal on Computing 52 (2023) 913–944.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 14458 | OA
SparseGPT: Massive language models can be accurately pruned in one-shot
E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10323–10337.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 14460 | OA
SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge
M. Nikdan, T. Pegolotti, E.B. Iofinova, E. Kurtic, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 26215–26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 14461 | OA
Quantized distributed training of large models with convergence guarantees
I. Markov, A. Vladu, Q. Guo, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 24020–24044.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2023 | Published | Conference Paper | IST-REx-ID: 17378 | OA
OPTQ: Accurate post-training quantization for generative pre-trained transformers
E. Frantar, S. Ashkboos, T. Hoefler, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , International Conference on Learning Representations, 2023.
[Published Version] View | Files available
 
2023 | Published | Journal Article | IST-REx-ID: 12566 | OA
Wait-free approximate agreement on graphs
D.-A. Alistarh, F. Ellen, J. Rybicki, Theoretical Computer Science 948 (2023).
[Published Version] View | Files available | DOI | WoS
 
2023 | Published | Conference Paper | IST-REx-ID: 13053 | OA
CrAM: A Compression-Aware Minimizer
A. Krumes, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , OpenReview, 2023.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2023 | Published | Thesis | IST-REx-ID: 13074 | OA
Efficiency and generalization of sparse neural networks
A. Krumes, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.
[Published Version] View | Files available | DOI
 
2023 | Published | Conference Paper | IST-REx-ID: 14771 | OA
Bias in pruned vision models: In-depth analysis and countermeasures
E.B. Iofinova, A. Krumes, D.-A. Alistarh, in:, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–24373.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 11180 | OA
Multi-queues can be state-of-the-art priority schedulers
A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, in:, Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 353–367.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 11183 | OA
Beyond distributed subgraph detection: Induced subgraphs, multicolored problems and graph parameters
A. Nikabadi, J. Korhonen, in:, Q. Bramas, V. Gramoli, A. Milani (Eds.), 25th International Conference on Principles of Distributed Systems, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
[Published Version] View | Files available | DOI
 
2022 | Published | Conference Paper | IST-REx-ID: 11184 | OA
Fast graphical population protocols
D.-A. Alistarh, R. Gelashvili, J. Rybicki, in:, Q. Bramas, V. Gramoli, A. Milani (Eds.), 25th International Conference on Principles of Distributed Systems, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
[Published Version] View | Files available | DOI | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 11844 | OA
Near-optimal leader election in population protocols on graphs
D.-A. Alistarh, J. Rybicki, S. Voitovych, in:, Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2022, pp. 246–256.
[Published Version] View | Files available | DOI | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 17059 | OA
SPDY: Accurate pruning with speedup guarantees
E. Frantar, D.-A. Alistarh, in:, 39th International Conference on Machine Learning, ML Research Press, 2022, pp. 6726–6743.
[Published Version] View | Files available | WoS
 
2022 | Published | Conference Paper | IST-REx-ID: 17087 | OA
Optimal brain compression: A framework for accurate post-training quantization and pruning
E. Frantar, S.P. Singh, D.-A. Alistarh, in:, 36th Conference on Neural Information Processing Systems, ML Research Press, 2022.
[Submitted Version] View | Files available | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 12299 | OA
How well do sparse ImageNet models transfer?
E.B. Iofinova, A. Krumes, M. Kurtz, D.-A. Alistarh, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–12266.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Published | Journal Article | IST-REx-ID: 8286 | OA
Dynamic averaging load balancing on cycles
D.-A. Alistarh, G. Nadiradze, A. Sabour, Algorithmica 84 (2022) 1007–1029.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10217 | OA
Lower bounds for shared-memory leader election under bounded write contention
D.-A. Alistarh, R. Gelashvili, G. Nadiradze, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
[Published Version] View | Files available | DOI
 

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