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121 Publications


2019 | Conference Paper | IST-REx-ID: 7542 | OA
Wendler, Chris, Dan-Adrian Alistarh, and Markus Püschel. “Powerset Convolutional Neural Networks,” 32:927–38. Neural Information Processing Systems Foundation, 2019.
[Published Version] View | Download Published Version (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6935 | OA
Foerster, Klaus-Tycho, Janne Korhonen, Joel Rybicki, and Stefan Schmid. “Does Preprocessing Help under Congestion?” In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, 259–61. ACM, 2019. https://doi.org/10.1145/3293611.3331581.
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2019 | Conference Paper | IST-REx-ID: 6676 | OA
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Why Extension-Based Proofs Fail.” In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 986–96. ACM Press, 2019. https://doi.org/10.1145/3313276.3316407.
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2019 | Conference Paper | IST-REx-ID: 6933 | OA
Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.” In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, 74–83. ACM, 2019. https://doi.org/10.1145/3293611.3331633.
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2018 | Journal Article | IST-REx-ID: 536 | OA
Alistarh, Dan-Adrian, James Aspnes, Valerie King, and Jared Saia. “Communication-Efficient Randomized Consensus.” Distributed Computing. Springer, 2018. https://doi.org/10.1007/s00446-017-0315-1.
[Published Version] View | Files available | DOI
 

2018 | Conference Paper | IST-REx-ID: 7116 | OA
Grubic, Demjan, Leo Tam, Dan-Adrian Alistarh, and Ce 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, 145–56. OpenProceedings, 2018. https://doi.org/10.5441/002/EDBT.2018.14.
[Published Version] View | Files available | DOI
 

2018 | Journal Article | IST-REx-ID: 6001
Alistarh, Dan-Adrian, William Leiserson, Alexander Matveev, and Nir Shavit. “ThreadScan: Automatic and Scalable Memory Reclamation.” ACM Transactions on Parallel Computing. Association for Computing Machinery, 2018. https://doi.org/10.1145/3201897.
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2018 | Conference Paper | IST-REx-ID: 7812 | OA
Polino, Antonio, Razvan Pascanu, and Dan-Adrian Alistarh. “Model Compression via Distillation and Quantization.” In 6th International Conference on Learning Representations, 2018.
[Published Version] View | Files available | arXiv
 

2018 | Conference Paper | IST-REx-ID: 397
Arbel Raviv, Maya, and Trevor A Brown. “Harnessing Epoch-Based Reclamation for Efficient Range Queries,” 53:14–27. ACM, 2018. https://doi.org/10.1145/3178487.3178489.
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2018 | Journal Article | IST-REx-ID: 43 | OA
Rybicki, Joel, Eva Kisdi, and Jani Anttila. “Model of Bacterial Toxin-Dependent Pathogenesis Explains Infective Dose.” PNAS. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1721061115.
[Submitted Version] View | Files available | DOI | WoS
 

2018 | Journal Article | IST-REx-ID: 76 | OA
Lenzen, Christoph, and Joel Rybicki. “Near-Optimal Self-Stabilising Counting and Firing Squads.” Distributed Computing. Springer, 2018. https://doi.org/10.1007/s00446-018-0342-6.
[Published Version] View | Files available | DOI | WoS
 

2018 | Conference Paper | IST-REx-ID: 85 | OA
Gilad, Eran, Trevor A Brown, Mark Oskin, and Yoav Etsion. “Snapshot Based Synchronization: A Fast Replacement for Hand-over-Hand Locking,” 11014:465–79. Springer, 2018. https://doi.org/10.1007/978-3-319-96983-1_33.
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2018 | Conference Paper | IST-REx-ID: 5962 | OA
Alistarh, Dan-Adrian, Christopher De Sa, and Nikola 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, 169–78. ACM Press, 2018. https://doi.org/10.1145/3212734.3212763.
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2018 | Conference Paper | IST-REx-ID: 5961
Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine Learning.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 487–88. ACM Press, 2018. https://doi.org/10.1145/3212734.3212798.
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2018 | Conference Paper | IST-REx-ID: 5963 | OA
Alistarh, Dan-Adrian, Trevor A Brown, Justin Kopinsky, and Giorgi Nadiradze. “Relaxed Schedulers Can Efficiently Parallelize Iterative Algorithms.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 377–86. ACM Press, 2018. https://doi.org/10.1145/3212734.3212756.
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2018 | Conference Paper | IST-REx-ID: 5965 | OA
Alistarh, Dan-Adrian, Trevor A Brown, Justin Kopinsky, Jerry Z. Li, and Giorgi Nadiradze. “Distributionally Linearizable Data Structures.” In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, 133–42. ACM Press, 2018. https://doi.org/10.1145/3210377.3210411.
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2018 | Conference Paper | IST-REx-ID: 5966 | OA
Alistarh, Dan-Adrian, Syed Kamran Haider, Raphael Kübler, and Giorgi Nadiradze. “The Transactional Conflict Problem.” In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, 383–92. ACM Press, 2018. https://doi.org/10.1145/3210377.3210406.
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2018 | Conference Paper | IST-REx-ID: 5964 | OA
Aksenov, Vitaly, Dan-Adrian Alistarh, and Petr Kuznetsov. “Brief Announcement: Performance Prediction for Coarse-Grained Locking.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 411–13. ACM Press, 2018. https://doi.org/10.1145/3212734.3212785.
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2018 | Conference Paper | IST-REx-ID: 6031
Stojanov, Alen, Tyler Michael Smith, Dan-Adrian Alistarh, and Markus Puschel. “Fast Quantized Arithmetic on X86: Trading Compute for Data Movement.” In 2018 IEEE International Workshop on Signal Processing Systems, Vol. 2018–October. IEEE, 2018. https://doi.org/10.1109/SiPS.2018.8598402.
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2018 | Conference Paper | IST-REx-ID: 7123 | OA
Alistarh, Dan-Adrian, James Aspnes, and Rati Gelashvili. “Space-Optimal Majority in Population Protocols.” In Proceedings of the 29th Annual ACM-SIAM Symposium on Discrete Algorithms, 2221–39. ACM, 2018. https://doi.org/10.1137/1.9781611975031.144.
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