Giga protocol for unlocking trustless parallel computation in blockchains

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Authors: Alberto Garoffolo, Dmytro Kaidalov, Roman Oliynykov, Daniele Di Tullio, Mariia Rodinko
Cited by: 1
References: 11

Abstract

In this paper, we introduce GIGA, a SNARK-based protocol that enables trustless parallel execution of transactions, processing non-conflicting operations concurrently, while preserving security guarantees and state consistency. The protocol organizes transactions into non-conflicting batches which are executed and proven in parallel, distributing execution across multiple decentralized entities. These batch proofs are recursively aggregated into a single succinct proof that validates the entire block. As a result, the protocol both distributes the execution workload and removes redundant re-execution from the network, significantly improving blockchain throughput while not affecting decentralization. Performance estimates demonstrate that, under the same system assumptions (e.g., consensus, networking, and virtual machine architecture) and under high degrees of transaction parallelism (i.e., when most transactions operate on disjoint parts of the state), our protocol may achieve over a 10000x throughput improvement compared to popular blockchain architectures that use sequential execution models, and over a 500x improvement compared to blockchain architectures employing intra-node parallelization schemes. Furthermore, our protocol enables a significant increase in transaction computational complexity, unlocking a wide range of use cases that were previously unfeasible on traditional blockchain architectures due to the limited on-chain computational capacity. Additionally, we propose a reward mechanism that ensures the economic sustainability of the proving network, dynamically adjusting to computational demand while fostering competition among provers based on cost-efficiency and reliability.

Fields of Study & Subjects

Distributed systems and fault tolerance Blockchain Technology Applications and Security Cloud Computing and Resource Management

Publication details

Journal / source
Discover Computing
Publisher
Springer Science and Business Media LLC
Volume
29
Issue
1
Publication date
9 February 2026
Language
EN