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Documents authored by Fedorov, Alexander

Document
DOI: 10.4230/LIPIcs.DISC.2025.3
An Almost-Logarithmic Lower Bound for Leader Election with Bounded Value Contention

Authors: Dan Alistarh, Faith Ellen, and Alexander Fedorov

Published in: LIPIcs, Volume 356, 39th International Symposium on Distributed Computing (DISC 2025)

Abstract
We investigate the step complexity of the Leader Election problem (and implementing the corresponding test-and-set object) in asynchronous shared memory, where processes communicate through registers supporting atomic read and write and must coordinate so that a single process becomes the leader. Determining tight step complexity bounds for solving this problem is one of the key open problems in the theory of shared memory distributed computing. The best known algorithm is a randomized tournament-tree, which has worst-case expected step complexity O(log N) for N processes. There are provably no deterministic wait-free algorithms, and only restricted lower bounds are known for obstruction-free and randomized wait-free algorithms. We introduce a new lower bound that establishes an Ω((log N)/(log log N + log Q)) step complexity for any obstruction-free Leader Election algorithm, where N is the number of processes, and 2 ≤ Q ≤ N is a bound on the value contention, which we define as the maximum number of different values that processes can be simultaneously poised to write to the same register in any execution of the algorithm. Our result is strictly stronger than previous bounds based on write contention. In particular, it implies new lower bounds on step complexity that depend on register size.
Cite as

Dan Alistarh, Faith Ellen, and Alexander Fedorov. An Almost-Logarithmic Lower Bound for Leader Election with Bounded Value Contention. In 39th International Symposium on Distributed Computing (DISC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 356, pp. 3:1-3:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{alistarh_et_al:LIPIcs.DISC.2025.3,
  author =	{Alistarh, Dan and Ellen, Faith and Fedorov, Alexander},
  title =	{{An Almost-Logarithmic Lower Bound for Leader Election with Bounded Value Contention}},
  booktitle =	{39th International Symposium on Distributed Computing (DISC 2025)},
  pages =	{3:1--3:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-402-4},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{356},
  editor =	{Kowalski, Dariusz R.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2025.3},
  URN =		{urn:nbn:de:0030-drops-248204},
  doi =		{10.4230/LIPIcs.DISC.2025.3},
  annote =	{Keywords: Leader Election, Test-and-Set, Shared Memory, Lower Bounds}
}
Document
Brief Announcement
DOI: 10.4230/LIPIcs.DISC.2023.35
Brief Announcement: BatchBoost: Universal Batching for Concurrent Data Structures

Authors: Vitaly Aksenov, Michael Anoprenko, Alexander Fedorov, and Michael Spear

Published in: LIPIcs, Volume 281, 37th International Symposium on Distributed Computing (DISC 2023)

Abstract
Batching is a technique that stores multiple keys/values in each node of a data structure. In sequential search data structures, batching reduces latency by reducing the number of cache misses and shortening the chain of pointers to dereference. Applying batching to concurrent data structures is challenging, because it is difficult to maintain the search property and keep contention low in the presence of batching. In this paper, we present a general methodology for leveraging batching in concurrent search data structures, called BatchBoost. BatchBoost builds a search data structure from distinct "data" and "index" layers. The data layer’s purpose is to store a batch of key/value pairs in each of its nodes. The index layer uses an unmodified concurrent search data structure to route operations to a position in the data layer that is "close" to where the corresponding key should exist. The requirements on the index and data layers are low: with minimal effort, we were able to compose three highly scalable concurrent search data structures based on three original data structures as the index layers with a batched version of the Lazy List as the data layer. The resulting BatchBoost data structures provide significant performance improvements over their original counterparts.
Cite as

Vitaly Aksenov, Michael Anoprenko, Alexander Fedorov, and Michael Spear. Brief Announcement: BatchBoost: Universal Batching for Concurrent Data Structures. In 37th International Symposium on Distributed Computing (DISC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 281, pp. 35:1-35:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{aksenov_et_al:LIPIcs.DISC.2023.35,
  author =	{Aksenov, Vitaly and Anoprenko, Michael and Fedorov, Alexander and Spear, Michael},
  title =	{{Brief Announcement: BatchBoost: Universal Batching for Concurrent Data Structures}},
  booktitle =	{37th International Symposium on Distributed Computing (DISC 2023)},
  pages =	{35:1--35:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-301-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{281},
  editor =	{Oshman, Rotem},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2023.35},
  URN =		{urn:nbn:de:0030-drops-191612},
  doi =		{10.4230/LIPIcs.DISC.2023.35},
  annote =	{Keywords: Concurrency, Synchronization, Locality}
}
Document
DOI: 10.4230/LIPIcs.OPODIS.2019.15
In Search of the Fastest Concurrent Union-Find Algorithm

Authors: Dan Alistarh, Alexander Fedorov, and Nikita Koval

Published in: LIPIcs, Volume 153, 23rd International Conference on Principles of Distributed Systems (OPODIS 2019)

Abstract
Union-Find (or Disjoint-Set Union) is one of the fundamental problems in computer science; it has been well-studied from both theoretical and practical perspectives in the sequential case. Recently, there has been mounting interest in analyzing this problem in the concurrent scenario, and several asymptotically-efficient algorithms have been proposed. Yet, to date, there is very little known about the practical performance of concurrent Union-Find. This work addresses this gap. We evaluate and analyze the performance of several concurrent Union-Find algorithms and optimization strategies across a wide range of platforms (Intel, AMD, and ARM) and workloads (social, random, and road networks, as well as integrations into more complex algorithms). We first observe that, due to the limited computational cost, the number of induced cache misses is the critical determining factor for the performance of existing algorithms. We introduce new techniques to reduce this cost by storing node priorities implicitly and by using plain reads and writes in a way that does not affect the correctness of the algorithms. Finally, we show that Union-Find implementations are an interesting application for Transactional Memory (TM): one of the fastest algorithm variants we discovered is a sequential one that uses coarse-grained locking with the lock elision optimization to reduce synchronization cost and increase scalability.
Cite as

Dan Alistarh, Alexander Fedorov, and Nikita Koval. In Search of the Fastest Concurrent Union-Find Algorithm. In 23rd International Conference on Principles of Distributed Systems (OPODIS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 153, pp. 15:1-15:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{alistarh_et_al:LIPIcs.OPODIS.2019.15,
  author =	{Alistarh, Dan and Fedorov, Alexander and Koval, Nikita},
  title =	{{In Search of the Fastest Concurrent Union-Find Algorithm}},
  booktitle =	{23rd International Conference on Principles of Distributed Systems (OPODIS 2019)},
  pages =	{15:1--15:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-133-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{153},
  editor =	{Felber, Pascal and Friedman, Roy and Gilbert, Seth and Miller, Avery},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2019.15},
  URN =		{urn:nbn:de:0030-drops-118012},
  doi =		{10.4230/LIPIcs.OPODIS.2019.15},
  annote =	{Keywords: union-find, concurrency, evaluation, benchmarks, hardware transactional memory}
}
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