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121 Publications
2021 | Conference Paper | IST-REx-ID: 9620 | 
D.-A. Alistarh and P. Davies, “Collecting coupons is faster with friends,” in Structural Information and Communication Complexity, Wrocław, Poland, 2021, vol. 12810, pp. 3–12.
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2021 | Conference Paper | IST-REx-ID: 9823 |
D.-A. Alistarh, F. Ellen, and J. Rybicki, “Wait-free approximate agreement on graphs,” in Structural Information and Communication Complexity, Wrocław, Poland, 2021, vol. 12810, pp. 87–105.
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2021 | Conference Paper | IST-REx-ID: 11458 |
E.-A. Peste, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating Compressed/DeCompressed training of deep neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 8557–8570.
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2021 | Conference Paper | IST-REx-ID: 13147 |
F. Alimisis, P. Davies, and D.-A. Alistarh, “Communication-efficient distributed optimization with quantized preconditioners,” in Proceedings of the 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 196–206.
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2021 | Journal Article | IST-REx-ID: 8723 |
S. Li et al., “Breaking (global) barriers in parallel stochastic optimization with wait-avoiding group averaging,” IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 7. IEEE, 2021.
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2021 | Journal Article | IST-REx-ID: 9827 |
B. Chatterjee, I. Walulya, and P. Tsigas, “Concurrent linearizable nearest neighbour search in LockFree-kD-tree,” Theoretical Computer Science, vol. 886. Elsevier, pp. 27–48, 2021.
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2021 | Conference Paper | IST-REx-ID: 9935 |
A. Czumaj, P. Davies, and M. Parter, “Improved deterministic (Δ+1) coloring in low-space MPC,” in Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Virtual, Italy, 2021, pp. 469–479.
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2021 | Conference Paper | IST-REx-ID: 9933 |
A. Czumaj, P. Davies, and M. Parter, “Component stability in low-space massively parallel computation,” in Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Virtual, Italy, 2021, pp. 481–491.
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2021 | Conference Paper | IST-REx-ID: 10432 |
G. Nadiradze, I. Markov, B. Chatterjee, V. Kungurtsev, and D.-A. Alistarh, “Elastic consistency: A practical consistency model for distributed stochastic gradient descent,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 10, pp. 9037–9045.
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2021 | Conference Paper | IST-REx-ID: 10049 |
K. Klein et al., “Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement,” in 2021 IEEE Symposium on Security and Privacy , San Francisco, CA, United States, 2021, pp. 268–284.
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2021 | Conference Paper | IST-REx-ID: 10854 |
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Virtual, Online, 2021, pp. 71–72.
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2021 | Journal Article | IST-REx-ID: 10855 |
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.
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2021 | Thesis | IST-REx-ID: 10429 |
G. Nadiradze, “On achieving scalability through relaxation,” Institute of Science and Technology Austria, 2021.
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2021 | Conference Paper | IST-REx-ID: 10435 |
G. Nadiradze, A. Sabour, P. Davies, S. Li, and D.-A. Alistarh, “Asynchronous decentralized SGD with quantized and local updates,” in 35th Conference on Neural Information Processing Systems, Sydney, Australia, 2021.
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2021 | Journal Article | IST-REx-ID: 9541 |
A. Czumaj, P. Davies, and M. Parter, “Graph sparsification for derandomizing massively parallel computation with low space,” ACM Transactions on Algorithms, vol. 17, no. 2. Association for Computing Machinery, 2021.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 9678 |
S. Brandt, B. Keller, J. Rybicki, J. Suomela, and J. Uitto, “Efficient load-balancing through distributed token dropping,” in Annual ACM Symposium on Parallelism in Algorithms and Architectures, Virtual Event, United States, 2021, pp. 129–139.
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2021 | Journal Article | IST-REx-ID: 8286 |
D.-A. Alistarh, G. Nadiradze, and A. Sabour, “Dynamic averaging load balancing on cycles,” Algorithmica. Springer Nature, 2021.
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| arXiv
2021 | Journal Article | IST-REx-ID: 9571 |
A. Ramezani-Kebrya, F. Faghri, I. Markov, V. Aksenov, D.-A. Alistarh, and D. M. Roy, “NUQSGD: Provably communication-efficient data-parallel SGD via nonuniform quantization,” Journal of Machine Learning Research, vol. 22, no. 114. Journal of Machine Learning Research, p. 1−43, 2021.
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2021 | Journal Article | IST-REx-ID: 7939 |
K. Censor-Hillel, M. Dory, J. Korhonen, and D. Leitersdorf, “Fast approximate shortest paths in the congested clique,” Distributed Computing, vol. 34. Springer Nature, pp. 463–487, 2021.
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2021 | Journal Article | IST-REx-ID: 15267 |
A. Czumaj and P. Davies, “Exploiting spontaneous transmissions for broadcasting and leader election in radio networks,” Journal of the ACM, vol. 68, no. 2. Association for Computing Machinery, 2021.
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2021 | Conference Paper | IST-REx-ID: 15263 |
F. Alimisis, A. Orvieto, G. Becigneul, and A. Lucchi, “Momentum improves optimization on Riemannian manifolds,” in Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, San Diego, CA, United States; Virtual, 2021, vol. 130, pp. 1351–1359.
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2020 | Conference Paper | IST-REx-ID: 7272 |
M. Arbel-Raviv, T. A. Brown, and A. Morrison, “Getting to the root of concurrent binary search tree performance,” in Proceedings of the 2018 USENIX Annual Technical Conference, Boston, MA, United States, 2020, pp. 295–306.
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2020 | Conference Paper | IST-REx-ID: 7605 |
D.-A. Alistarh, A. Fedorov, and N. Koval, “In search of the fastest concurrent union-find algorithm,” in 23rd International Conference on Principles of Distributed Systems, Neuchatal, Switzerland, 2020, vol. 153, p. 15:1-15:16.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 7803 |
A. Czumaj, P. Davies, and M. Parter, “Simple, deterministic, constant-round coloring in the congested clique,” in Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing, Salerno, Italy, 2020, pp. 309–318.
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2020 | Conference Paper | IST-REx-ID: 8725 |
V. Aksenov, D.-A. Alistarh, A. Drozdova, and A. Mohtashami, “The splay-list: A distribution-adaptive concurrent skip-list,” in 34th International Symposium on Distributed Computing, Freiburg, Germany, 2020, vol. 179, p. 3:1-3:18.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 9632 |
S. P. Singh and D.-A. Alistarh, “WoodFisher: Efficient second-order approximation for neural network compression,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 18098–18109.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 9631 |
V. Aksenov, D.-A. Alistarh, and J. Korhonen, “Scalable belief propagation via relaxed scheduling,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 22361–22372.
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2020 | Conference Paper | IST-REx-ID: 9415 |
M. Kurtz et al., “Inducing and exploiting activation sparsity for fast neural network inference,” in 37th International Conference on Machine Learning, ICML 2020, Online, 2020, vol. 119, pp. 5533–5543.
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2020 | Journal Article | IST-REx-ID: 8268 |
N. M. Gurel et al., “Compressive sensing using iterative hard thresholding with low precision data representation: Theory and applications,” IEEE Transactions on Signal Processing, vol. 68. IEEE, pp. 4268–4282, 2020.
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2020 | Conference Paper | IST-REx-ID: 8722 |
S. Li, T. B.-N. Tal Ben-Nun, S. D. Girolamo, D.-A. Alistarh, and T. Hoefler, “Taming unbalanced training workloads in deep learning with partial collective operations,” in Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, San Diego, CA, United States, 2020, pp. 45–61.
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| arXiv
2020 | Journal Article | IST-REx-ID: 7224 |
J. Rybicki, N. Abrego, and O. Ovaskainen, “Habitat fragmentation and species diversity in competitive communities,” Ecology Letters, vol. 23, no. 3. Wiley, pp. 506–517, 2020.
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2020 | Conference Paper | IST-REx-ID: 8724 |
N. H. Konstantinov, E. Frantar, D.-A. Alistarh, and C. Lampert, “On the sample complexity of adversarial multi-source PAC learning,” in Proceedings of the 37th International Conference on Machine Learning, Online, 2020, vol. 119, pp. 5416–5425.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 7213 |
S. Bhatia, B. Chatterjee, D. Nathani, and M. Kaul, “A persistent homology perspective to the link prediction problem,” in Complex Networks and their applications VIII, Lisbon, Portugal, 2020, vol. 881, pp. 27–39.
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2020 | Conference Paper | IST-REx-ID: 7802 |
A. Czumaj, P. Davies, and M. Parter, “Graph sparsification for derandomizing massively parallel computation with low space,” in Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020), Virtual Event, United States, 2020, no. 7, pp. 175–185.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 7636 |
T. A. Brown, A. Prokopec, and D.-A. Alistarh, “Non-blocking interpolation search trees with doubly-logarithmic running time,” in Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, San Diego, CA, United States, 2020, pp. 276–291.
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2020 | Conference Paper | IST-REx-ID: 8191
D.-A. Alistarh, T. A. Brown, and N. Singhal, “Memory tagging: Minimalist synchronization for scalable concurrent data structures,” in Annual ACM Symposium on Parallelism in Algorithms and Architectures, Virtual Event, United States, 2020, no. 7, pp. 37–49.
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2020 | Conference Paper | IST-REx-ID: 7635
N. Koval, M. Sokolova, A. Fedorov, D.-A. Alistarh, and D. Tsitelov, “Testing concurrency on the JVM with Lincheck,” in Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, San Diego, CA, United States, 2020, pp. 423–424.
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2020 | Conference Paper | IST-REx-ID: 15074 |
S. Brandt, B. Keller, J. Rybicki, J. Suomela, and J. Uitto, “Brief announcement: Efficient load-balancing through distributed token dropping,” in 34th International Symposium on Distributed Computing, Virtual, 2020, vol. 179.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 15077 |
D.-A. Alistarh, G. Nadiradze, and A. Sabour, “Dynamic averaging load balancing on cycles,” in 47th International Colloquium on Automata, Languages, and Programming, Saarbrücken, Germany, Virtual, 2020, vol. 168.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 15086 |
F. Faghri, I. Tabrizian, I. Markov, D.-A. Alistarh, D. Roy, and A. Ramezani-Kebrya, “Adaptive gradient quantization for data-parallel SGD,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33.
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2019 | Journal Article | IST-REx-ID: 6759 |
V. Jelínek and M. Töpfer, “On grounded L-graphs and their relatives,” Electronic Journal of Combinatorics, vol. 26, no. 3. Electronic Journal of Combinatorics, 2019.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 6931 |
T. Nowak and J. Rybicki, “Byzantine approximate agreement on graphs,” in 33rd International Symposium on Distributed Computing, Budapest, Hungary, 2019, vol. 146, p. 29:1--29:17.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 5947 |
B. Chatterjee, S. Peri, M. Sa, and N. Singhal, “A simple and practical concurrent non-blocking unbounded graph with linearizable reachability queries,” in ACM International Conference Proceeding Series, Bangalore, India, 2019, pp. 168–177.
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2019 | Journal Article | IST-REx-ID: 6936 |
O. Ovaskainen, J. Rybicki, and N. Abrego, “What can observational data reveal about metacommunity processes?,” Ecography, vol. 42, no. 11. Wiley, pp. 1877–1886, 2019.
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2019 | Journal Article | IST-REx-ID: 6972 |
C. Lenzen and J. Rybicki, “Self-stabilising Byzantine clock synchronisation is almost as easy as consensus,” Journal of the ACM, vol. 66, no. 5. ACM, 2019.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 7201 |
C. Renggli, S. Ashkboos, M. Aghagolzadeh, D.-A. Alistarh, and T. Hoefler, “SparCML: High-performance sparse communication for machine learning,” in International Conference for High Performance Computing, Networking, Storage and Analysis, SC, Denver, CO, Unites States, 2019.
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2019 | Journal Article | IST-REx-ID: 7214 |
S. Aganezov, I. Zban, V. Aksenov, N. Alexeev, and M. C. Schatz, “Recovering rearranged cancer chromosomes from karyotype graphs,” BMC Bioinformatics, vol. 20. BMC, 2019.
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2019 | Conference Paper | IST-REx-ID: 7437 |
C. Yu et al., “Distributed learning over unreliable networks,” in 36th International Conference on Machine Learning, ICML 2019, Long Beach, CA, United States, 2019, vol. 2019–June, pp. 12481–12512.
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2019 | Conference Paper | IST-REx-ID: 6673 |
D.-A. Alistarh, G. Nadiradze, and N. Koval, “Efficiency guarantees for parallel incremental algorithms under relaxed schedulers,” in 31st ACM Symposium on Parallelism in Algorithms and Architectures, Phoenix, AZ, United States, 2019, pp. 145–154.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 7542 |
C. Wendler, D.-A. Alistarh, and M. Püschel, “Powerset convolutional neural networks,” presented at the NIPS: Conference on Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 927–938.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 6935 |
K.-T. Foerster, J. Korhonen, J. Rybicki, and S. Schmid, “Does preprocessing help under congestion?,” in Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, Toronto, ON, Canada, 2019, pp. 259–261.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 6676 |
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, and L. Zhu, “Why extension-based proofs fail,” in Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, Phoenix, AZ, United States, 2019, pp. 986–996.
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2019 | Conference Paper | IST-REx-ID: 6933 |
K. Censor-Hillel, M. Dory, J. Korhonen, and D. Leitersdorf, “Fast approximate shortest paths in the congested clique,” in Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, Toronto, ON, Canada, 2019, pp. 74–83.
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| arXiv
2018 | Journal Article | IST-REx-ID: 536 |
D.-A. Alistarh, J. Aspnes, V. King, and J. Saia, “Communication-efficient randomized consensus,” Distributed Computing, vol. 31, no. 6. Springer, pp. 489–501, 2018.
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2018 | 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 | Journal Article | IST-REx-ID: 6001
D.-A. Alistarh, W. Leiserson, A. Matveev, and N. Shavit, “ThreadScan: Automatic and scalable memory reclamation,” ACM Transactions on Parallel Computing, vol. 4, no. 4. Association for Computing Machinery, 2018.
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2018 | 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.
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| arXiv
2018 | Journal Article | IST-REx-ID: 43 |
J. Rybicki, E. Kisdi, and J. Anttila, “Model of bacterial toxin-dependent pathogenesis explains infective dose,” PNAS, vol. 115, no. 42. National Academy of Sciences, pp. 10690–10695, 2018.
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2018 | Journal Article | IST-REx-ID: 76 |
C. Lenzen and J. Rybicki, “Near-optimal self-stabilising counting and firing squads,” Distributed Computing. Springer, 2018.
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2018 | 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.
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2018 | Conference Paper | IST-REx-ID: 5962 |
D.-A. Alistarh, C. De Sa, and N. H. Konstantinov, “The convergence of stochastic gradient descent in asynchronous shared memory,” in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United Kingdom, 2018, pp. 169–178.
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2018 | Conference Paper | IST-REx-ID: 5963 |
D.-A. Alistarh, T. A. Brown, J. Kopinsky, and G. Nadiradze, “Relaxed schedulers can efficiently parallelize iterative algorithms,” in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United Kingdom, 2018, pp. 377–386.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 5965 |
D.-A. Alistarh, T. A. Brown, J. Kopinsky, J. Z. Li, and G. Nadiradze, “Distributionally linearizable data structures,” in Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, Vienna, Austria, 2018, pp. 133–142.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 5966 |
D.-A. Alistarh, S. K. Haider, R. Kübler, and G. Nadiradze, “The transactional conflict problem,” in Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, Vienna, Austria, 2018, pp. 383–392.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 5964 |
V. Aksenov, D.-A. Alistarh, and P. Kuznetsov, “Brief Announcement: Performance prediction for coarse-grained locking,” in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United Kingdom, 2018, pp. 411–413.
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2018 | 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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2018 | 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.
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2018 | 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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| arXiv
2018 | 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 Advances in Neural Information Processing Systems 31, Montreal, Canada, 2018, vol. Volume 2018, pp. 5973–5983.
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| arXiv
2017 | 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 | 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.
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2017 | 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.
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| arXiv
2017 | 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.
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