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DOI: 10.4230/LIPIcs.AFT.2025.29

Efficient Parallel Execution of Blockchain Transactions Leveraging Conflict Specifications

Authors: Parwat Singh Anjana, Matin Amini, Rohit Kapoor, Rahul Parmar, Raghavendra Ramesh, Srivatsan Ravi, and Joshua Tobkin

Published in: LIPIcs, Volume 354, 7th Conference on Advances in Financial Technologies (AFT 2025)

Abstract

Parallel execution of smart contract transactions in large multicore architectures is critical for higher efficiency and improved throughput. The main bottleneck for maximizing the throughput of a node through parallel execution is transaction conflict resolution: when two transactions interact with the same data, like an account balance, their order matters. Imagine one transaction sends tokens from account A to account B, and another tries to send tokens from account B to account C. If the second transaction happens before the first one, the token balance in account B might be wrong, causing the entire system to break. Conflicts like these must be managed carefully, or you end up with an inconsistent, unusable blockchain state. Traditional software transactional memory (STM) has been identified as a possible abstraction for the concurrent execution of transactions within a block, with Block-STM pioneering its application for efficient blockchain transaction processing on multicore validator nodes. This paper presents a parallel execution methodology that leverages conflict specification information of the transactions for block transactional memory (BTM) algorithms. Our experimental analysis, conducted over synthetic transactional workloads and real-world blocks, demonstrates that BTMs leveraging conflict specifications outperform their plain counterparts on both EVM and MoveVM. Our proposed BTM implementations achieve up to 1.75× speedup over sequential execution and outperform the state-of-the-art Parallel-EVM (PEVM) execution by up to 1.33× across synthetic workloads.

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Parwat Singh Anjana, Matin Amini, Rohit Kapoor, Rahul Parmar, Raghavendra Ramesh, Srivatsan Ravi, and Joshua Tobkin. Efficient Parallel Execution of Blockchain Transactions Leveraging Conflict Specifications. In 7th Conference on Advances in Financial Technologies (AFT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 354, pp. 29:1-29:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{anjana_et_al:LIPIcs.AFT.2025.29,
  author =	{Anjana, Parwat Singh and Amini, Matin and Kapoor, Rohit and Parmar, Rahul and Ramesh, Raghavendra and Ravi, Srivatsan and Tobkin, Joshua},
  title =	{{Efficient Parallel Execution of Blockchain Transactions Leveraging Conflict Specifications}},
  booktitle =	{7th Conference on Advances in Financial Technologies (AFT 2025)},
  pages =	{29:1--29:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-400-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{354},
  editor =	{Avarikioti, Zeta and Christin, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2025.29},
  URN =		{urn:nbn:de:0030-drops-247485},
  doi =		{10.4230/LIPIcs.AFT.2025.29},
  annote =	{Keywords: Blockchain, Smart Contract, Parallel Execution, Conflict Specifications}
}

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DOI: 10.4230/LIPIcs.DISC.2017.9

Cost of Concurrency in Hybrid Transactional Memory

Authors: Trevor Brown and Srivatsan Ravi

Published in: LIPIcs, Volume 91, 31st International Symposium on Distributed Computing (DISC 2017)

Abstract

State-of-the-art software transactional memory (STM) implementations achieve good performance by carefully avoiding the overhead of incremental validation (i.e., re-reading previously read data items to avoid inconsistency) while still providing progressiveness (allowing transactional aborts only due to data conflicts). Hardware transactional memory (HTM) implementations promise even better performance, but offer no progress guarantees. Thus, they must be combined with STMs, leading to hybrid TMs (HyTMs) in which hardware transactions must be instrumented (i.e., access metadata) to detect contention with software transactions. We show that, unlike in progressive STMs, software transactions in progressive HyTMs cannot avoid incremental validation. In fact, this result holds even if hardware transactions can read metadata non-speculatively. We then present opaque HyTM algorithms providing progressiveness for a subset of transactions that are optimal in terms of hardware instrumentation. We explore the concurrency vs. hardware instrumentation vs. software validation trade-offs for these algorithms. Our experiments with Intel and IBM POWER8 HTMs seem to suggest that (i) the cost of concurrency also exists in practice, (ii) it is important to implement HyTMs that provide progressiveness for a maximal set of transactions without incurring high hardware instrumentation overhead or using global contending bottlenecks and (iii) there is no easy way to derive more efficient HyTMs by taking advantage of non-speculative accesses within hardware.

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Trevor Brown and Srivatsan Ravi. Cost of Concurrency in Hybrid Transactional Memory. In 31st International Symposium on Distributed Computing (DISC 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 91, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{brown_et_al:LIPIcs.DISC.2017.9,
  author =	{Brown, Trevor and Ravi, Srivatsan},
  title =	{{Cost of Concurrency in Hybrid Transactional Memory}},
  booktitle =	{31st International Symposium on Distributed Computing (DISC 2017)},
  pages =	{9:1--9:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-053-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{91},
  editor =	{Richa, Andr\'{e}a},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2017.9},
  URN =		{urn:nbn:de:0030-drops-79958},
  doi =		{10.4230/LIPIcs.DISC.2017.9},
  annote =	{Keywords: Transactional memory, Lower bounds, Opacity}
}

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Efficient Parallel Execution of Blockchain Transactions Leveraging Conflict Specifications

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Cost of Concurrency in Hybrid Transactional Memory

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