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Documents authored by Sheffield, Nathan S.

Document
DOI: 10.4230/LIPIcs.ITCS.2025.79
Catalytic Communication

Authors: Edward Pyne, Nathan S. Sheffield, and William Wang

Published in: LIPIcs, Volume 325, 16th Innovations in Theoretical Computer Science Conference (ITCS 2025)

Abstract
The study of space-bounded computation has drawn extensively from ideas and results in the field of communication complexity. Catalytic Computation (Buhrman, Cleve, Koucký, Loff and Speelman, STOC 2013) studies the power of bounded space augmented with a pre-filled hard drive that can be used non-destructively during the computation. Presently, many structural questions in this model remain open. Towards a better understanding of catalytic space, we define a model of catalytic communication complexity and prove new upper and lower bounds. In our model, Alice and Bob share a blackboard with a tiny number of free bits, and a larger section with an arbitrary initial configuration. They must jointly compute a function of their inputs, communicating only via the blackboard, and must always reset the blackboard to its initial configuration. We prove several upper and lower bounds: 1) We characterize the simplest nontrivial model, that of one bit of free space and three rounds, in terms of 𝔽₂ rank. In particular, we give natural problems that are solvable with a minimal-sized blackboard that require near-maximal (randomized) communication complexity, and vice versa. 2) We show that allowing constantly many free bits, as opposed to one, allows an exponential improvement on the size of the blackboard for natural problems. To do so, we connect the problem to existence questions in extremal graph theory. 3) We give tight connections between our model and standard notions of non-uniform catalytic computation. Using this connection, we show that with an arbitrary constant number of rounds and bits of free space, one can compute all functions in TC⁰. We view this model as a step toward understanding the value of filled space in computation.
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Edward Pyne, Nathan S. Sheffield, and William Wang. Catalytic Communication. In 16th Innovations in Theoretical Computer Science Conference (ITCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 325, pp. 79:1-79:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{pyne_et_al:LIPIcs.ITCS.2025.79,
  author =	{Pyne, Edward and Sheffield, Nathan S. and Wang, William},
  title =	{{Catalytic Communication}},
  booktitle =	{16th Innovations in Theoretical Computer Science Conference (ITCS 2025)},
  pages =	{79:1--79:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-361-4},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{325},
  editor =	{Meka, Raghu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2025.79},
  URN =		{urn:nbn:de:0030-drops-227076},
  doi =		{10.4230/LIPIcs.ITCS.2025.79},
  annote =	{Keywords: Catalytic computation, Branching programs, Communication complexity}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2025.87
When to Give up on a Parallel Implementation

Authors: Nathan S. Sheffield and Alek Westover

Published in: LIPIcs, Volume 325, 16th Innovations in Theoretical Computer Science Conference (ITCS 2025)

Abstract
In the Serial Parallel Decision Problem (SPDP), introduced by Kuszmaul and Westover [SPAA'24], an algorithm receives a series of tasks online, and must choose for each between a serial implementation and a parallelizable (but less efficient) implementation. Kuszmaul and Westover describe three decision models: (1) Instantly-committing schedulers must decide on arrival, irrevocably, which implementation of the task to run. (2) Eventually-committing schedulers can delay their decision beyond a task’s arrival time, but cannot revoke their decision once made. (3) Never-committing schedulers are always free to abandon their progress on the task and start over using a different implementation. Kuszmaul and Westover gave a simple instantly-committing scheduler whose total completion time is 3-competitive with the offline optimal schedule, and proved two lower bounds: no eventually-committing scheduler can have competitive ratio better than ϕ ≈ 1.618 in general, and no instantly-committing scheduler can have competitive ratio better than 2 in general. They conjectured that the three decision models should admit different competitive ratios, but left upper bounds below 3 in any model as an open problem. In this paper, we show that the powers of instantly, eventually, and never committing schedulers are distinct, at least in the "massively parallel regime". The massively parallel regime of the SPDP is the special case where the number of available processors is asymptotically larger than the number of tasks to process, meaning that the work associated with running a task in serial is negligible compared to its runtime. In this regime, we show (1) The optimal competitive ratio for instantly-committing schedulers is 2, (2) The optimal competitive ratio for eventually-committing schedulers lies in [1.618, 1.678], (3) The optimal competitive ratio for never-committing schedulers lies in [1.366, 1.500]. We additionally show that our instantly-committing scheduler is also 2-competitive outside of the massively parallel regime, giving proof-of-concept that results in the massively parallel regime can be translated to hold with fewer processors.
Cite as

Nathan S. Sheffield and Alek Westover. When to Give up on a Parallel Implementation. In 16th Innovations in Theoretical Computer Science Conference (ITCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 325, pp. 87:1-87:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{sheffield_et_al:LIPIcs.ITCS.2025.87,
  author =	{Sheffield, Nathan S. and Westover, Alek},
  title =	{{When to Give up on a Parallel Implementation}},
  booktitle =	{16th Innovations in Theoretical Computer Science Conference (ITCS 2025)},
  pages =	{87:1--87:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-361-4},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{325},
  editor =	{Meka, Raghu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2025.87},
  URN =		{urn:nbn:de:0030-drops-227154},
  doi =		{10.4230/LIPIcs.ITCS.2025.87},
  annote =	{Keywords: Scheduling, Multi-Processor, Online-Algorithms}
}
Document
DOI: 10.4230/LIPIcs.AofA.2024.16
Matching Algorithms in the Sparse Stochastic Block Model

Authors: Anna Brandenberger, Byron Chin, Nathan S. Sheffield, and Divya Shyamal

Published in: LIPIcs, Volume 302, 35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2024)

Abstract
In sparse Erdős-Rényi graphs, it is known that a linear-time algorithm of Karp and Sipser achieves near-optimal matching sizes asymptotically almost surely, giving a law-of-large numbers for the matching numbers of such graphs in terms of solutions to an ODE [Jonathan Aronson et al., 1998]. We provide an extension of this analysis, identifying broad ranges of stochastic block model parameters for which the Karp-Sipser algorithm achieves near-optimal matching sizes, but demonstrating that it cannot perform optimally on general stochastic block model instances. We also consider the problem of constructing a matching online, in which the vertices of one half of a bipartite stochastic block model arrive one-at-a-time, and must be matched as they arrive. We show that, when the expected degrees in all communities are equal, the competitive ratio lower bound of 0.837 found by Mastin and Jaillet for the Erdős-Rényi case [Andrew Mastin and Patrick Jaillet, 2013] is achieved by a simple greedy algorithm, and this competitive ratio is optimal. We then propose and analyze a linear-time online matching algorithm with better performance in general stochastic block models.
Cite as

Anna Brandenberger, Byron Chin, Nathan S. Sheffield, and Divya Shyamal. Matching Algorithms in the Sparse Stochastic Block Model. In 35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 302, pp. 16:1-16:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{brandenberger_et_al:LIPIcs.AofA.2024.16,
  author =	{Brandenberger, Anna and Chin, Byron and Sheffield, Nathan S. and Shyamal, Divya},
  title =	{{Matching Algorithms in the Sparse Stochastic Block Model}},
  booktitle =	{35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2024)},
  pages =	{16:1--16:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-329-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{302},
  editor =	{Mailler, C\'{e}cile and Wild, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AofA.2024.16},
  URN =		{urn:nbn:de:0030-drops-204515},
  doi =		{10.4230/LIPIcs.AofA.2024.16},
  annote =	{Keywords: Matching Algorithms, Online Matching, Stochastic Block Model}
}
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