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Accelerating Blockchain Scalability: New Models for Parallel Transaction Execution in the EVM

Souradeep Das, Konpat Preechakul, Jonas Bäumer, Riddhi Patel, Jefferson Jinchuan Li

TL;DR

The paper tackles Ethereum's scalability bottleneck by enabling parallel transaction execution in the EVM, addressing the root limit of sequential processing rather than relying solely on Layer 2. It proposes three self-sufficient pillars—Gas Incentivization Mechanics, Method Access Boundaries, and Smart Access Lists—to orchestrate parallelism and reward efficient block construction. Using historical data and a greedy scheduling approach related to the Maximum Independent Set problem, the authors report that blocks containing approximately $109$ transactions can be grouped into about $32$ parallelizable groups, yielding throughput from $9.08$ to $14.04$ transactions per second ($1.54\times$ gain). The design includes sandboxed execution to handle incomplete access lists and dynamic adjustments to access boundaries, aiming for robust safety and adaptability. If adopted, this framework could substantially reduce fees and enable higher-throughput DeFi and smart-contract workloads on Ethereum.

Abstract

As the number of decentralized applications and users on Ethereum grows, the ability of the blockchain to efficiently handle a growing number of transactions becomes increasingly strained. Ethereums current execution model relies heavily on sequential processing, meaning that operations are processed one after the other, which creates significant bottlenecks to future scalability demands. While scalability solutions for Ethereum exist, they inherit the limitations of the EVM, restricting the extent to which they can scale. This paper proposes a novel solution to enable maximally parallelizable executions within Ethereum, built out of three self-sufficient approaches. These approaches include strategies in which Ethereum transaction state accesses could be strategically and efficiently predetermined, and further propose how the incorporation of gas based incentivization mechanisms could enforce a maximally parallelizable network.

Accelerating Blockchain Scalability: New Models for Parallel Transaction Execution in the EVM

TL;DR

The paper tackles Ethereum's scalability bottleneck by enabling parallel transaction execution in the EVM, addressing the root limit of sequential processing rather than relying solely on Layer 2. It proposes three self-sufficient pillars—Gas Incentivization Mechanics, Method Access Boundaries, and Smart Access Lists—to orchestrate parallelism and reward efficient block construction. Using historical data and a greedy scheduling approach related to the Maximum Independent Set problem, the authors report that blocks containing approximately transactions can be grouped into about parallelizable groups, yielding throughput from to transactions per second ( gain). The design includes sandboxed execution to handle incomplete access lists and dynamic adjustments to access boundaries, aiming for robust safety and adaptability. If adopted, this framework could substantially reduce fees and enable higher-throughput DeFi and smart-contract workloads on Ethereum.

Abstract

As the number of decentralized applications and users on Ethereum grows, the ability of the blockchain to efficiently handle a growing number of transactions becomes increasingly strained. Ethereums current execution model relies heavily on sequential processing, meaning that operations are processed one after the other, which creates significant bottlenecks to future scalability demands. While scalability solutions for Ethereum exist, they inherit the limitations of the EVM, restricting the extent to which they can scale. This paper proposes a novel solution to enable maximally parallelizable executions within Ethereum, built out of three self-sufficient approaches. These approaches include strategies in which Ethereum transaction state accesses could be strategically and efficiently predetermined, and further propose how the incorporation of gas based incentivization mechanisms could enforce a maximally parallelizable network.

Paper Structure

This paper contains 15 sections, 3 equations, 2 figures.

Table of Contents

  1. Introduction
  2. Related Works
  3. Approach
  4. Gas Incentivization Mechanics
  5. Method Access Boundaries
  6. Smart Access Lists
  7. Evaluation
  8. Question 1: To what degree transactions can be parallelized?
  9. Question 2: What is the sustainable degree of parallelization?
  10. Question 3: How much does parallelization improve throughput?
  11. Conclusion
  12. Python Code for Overlap Pairs and Group Generation
  13. Function to Generate Overlap Pairs
  14. Function to Generate Optimized Groups
  15. JavaScript Code for Storage Access Analysis

Figures (2)

  • Figure 1: On average, only 4 parallelizable groups are needed for 109 transactions within a block. This is a surprising result that demonstrates the significant potential of parallelization.
  • Figure 2: Initially, the number of groups required is small, but it quickly increases and oscillates between 20 and 50 groups. The median number of groups required is 32 for 109 transactions, demonstrating that our approach achieves approximately three times the efficiency of traditional sequential execution in the long term.