NEMO: Faster Parallel Execution for Highly Contended Blockchain Workloads (Full version)

2025-10-16

AI Summary

Blockchain execution layers suffer from severe performance bottlenecks under high-contention workloads, where existing optimistic and pessimistic concurrency control frameworks exhibit substantial throughput degradation. This paper introduces NEMO—the first execution engine that unifies optimistic concurrency control with an object-oriented data model. NEMO innovatively designs a greedy commit rule, fine-grained dependency resolution, statically derivable read/write hints, and a priority-aware scheduler—jointly optimizing commit logic, dependency modeling, access prediction, and scheduling decisions. Experimental evaluation on 16 threads demonstrates that NEMO achieves 42% higher throughput than the state-of-the-art Block-STM and 61% higher than a pessimistic baseline, significantly reducing costly re-execution overhead under contention. By rethinking concurrency control through object-centric abstractions and proactive coordination, NEMO establishes a new paradigm for high-performance blockchain execution.

Technology Category

• Search and Optimization: Distributed Search
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications

Abstract

Following the design of more efficient blockchain consensus algorithms, the execution layer has emerged as the new performance bottleneck of blockchains, especially under high contention. Current parallel execution frameworks either rely on optimistic concurrency control (OCC) or on pessimistic concurrency control (PCC), both of which see their performance decrease when workloads are highly contended, albeit for different reasons. In this work, we present NEMO, a new blockchain execution engine that combines OCC with the object data model to address this challenge. NEMO introduces four core innovations: (i) a greedy commit rule for transactions using only owned objects; (ii) refined handling of dependencies to reduce re-executions; (iii) the use of incomplete but statically derivable read/write hints to guide execution; and (iv) a priority-based scheduler that favors transactions that unblock others. Through simulated execution experiments, we demonstrate that NEMO significantly reduces redundant computation and achieves higher throughput than representative approaches. For example, with 16 workers NEMO's throughput is up to 42% higher than the one of Block-STM, the state-of-the-art OCC approach, and 61% higher than the pessimistic concurrency control baseline used.

Problem

• Addressing performance bottlenecks in blockchain execution layers
• Improving throughput for highly contended blockchain workloads
• Reducing redundant computation in parallel transaction execution

Innovation

• Combines OCC with object data model
• Uses greedy commit rule for owned objects
• Employs priority-based scheduler for transactions