Utilizing Parallelism in Smart Contracts on Decentralized Blockchains by Taming Application-Inherent Conflicts
Péter Garamvölgyi, Yuxi Liu, Dong Zhou, Fan Long, Ming Wu
Abstract
Traditional public blockchain systems typically had very limited transaction throughput because of the bottleneck of the consensus protocol itself. With recent advances in consensus technology, the performance limit has been greatly lifted, typically to thousands of transactions per second. With this, transaction execution has become a new performance bottleneck. Exploiting parallelism in transaction execution is a clear and direct way to address this and to further increase transaction throughput. Although some recent literature introduced concurrency control mechanisms to execute smart contract transactions in parallel, the reported speedup that they can achieve is far from ideal. The main reason is that the proposed parallel execution mechanisms cannot effectively deal with the conflicts inherent in many blockchain applications. In this work, we thoroughly study the historical transaction execution traces in Ethereum. We observe that application-inherent conflicts are the major factors that limit the exploitable parallelism during execution. We propose to use partitioned counters and special commutative instructions to break up the application conflict chains in order to maximize the potential speedup. When we evaluated the maximum parallel speedup achievable, these techniques doubled this limit to an 18x overall speedup compared to serial execution, thus approaching the optimum. We also propose OCC-DA, an optimistic concurrency control scheduler with deterministic aborts, which makes it possible to use OCC scheduling in public blockchain settings.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext ac5678b0-9082-4429-b19a-0c12da87bb73Cited by top-tier papers7
- Vegeta: Enabling Parallel Smart Contract Execution in Leaderless BlockchainsTianjing Xu, Yongqi Zhong, Yiming Zhang, Ruofan Xiong et al.NSDI 2025 · 9 citations
- Spectrum: Speedy and Strictly-Deterministic Smart Contract Transactions for Blockchain LedgersZhihao Chen, Tianji Yang, Yixiao Zheng, Zhao Zhang et al.VLDB 2024 · 7 citations
- MHOT: Height-Optimized Authenticated Data Structure for Blockchain State CommitmentSipeng Xie, Qianhong Wu, Minghang Li, Qiyuan Gao et al.USENIX Security 2026 · 2 citations
- Remora: Scale-out Deterministic Execution for Smart ContractsZhengqing Liu, Alberto Sonnino, Igor Zablotchi, Eleftherios Kokoris-Kogias et al.VLDB 2026 · 1 citation
- Seer: Accelerating Blockchain Transaction Execution by Fine-Grained Branch PredictionShijie Zhang, Ru Cheng, Xinpeng Liu, Jiang Xiao et al.VLDB 2025
Builds on3
- Prism: Deconstructing the Blockchain to Approach Physical LimitsVivek Kumar Bagaria, Sreeram Kannan, David Tse, Giulia Fanti et al.CCS 2019 · 256 citations
- A Decentralized Blockchain with High Throughput and Fast ConfirmationChenxing Li, Peilun Li, Dong Zhou, Zhe Yang et al.USENIX ATC 2020 · 172 citations
- OHIE: Blockchain Scaling Made SimpleHaifeng Yu, Ivica Nikolic, Ruomu Hou, Prateek SaxenaS&P 2020 · 166 citations
Related papers
- Toward High-Performance Blockchain System by Blurring the Line between Ordering and ExecutionDonghyeon Ryu, Chanik ParkSC 2024 · 6 citations
- ParallelEVM: Operation-Level Concurrent Transaction Execution for EVM-Compatible BlockchainsHaoran Lin, Hang Feng, Yajin Zhou, Lei WuEuroSys 2025 · 6 citations
- Revisiting OCC in Permissioned Blockchain via Fast Re-ExecutionMingrui Cao, Bin Cao, Weihao Peng, Mugen PengINFOCOM 2026
- Crystality: A Programming Model for Smart Contracts on Parallel EVMsHao Wang, Minghao Pan, Jiaping WangPPoPP 2025 · 5 citations
- A Transactional Perspective on Execute-order-validate BlockchainsPingcheng Ruan, Dumitrel Loghin, Quang-Trung Ta, Meihui Zhang et al.SIGMOD 2020 · 117 citations
