Introduction

In the context of the rapid development of the digital economy, blockchain technology, as a representative of decentralized trust mechanisms, is gradually permeating sectors such as finance, supply chains, and healthcare. However, traditional blockchain systems, often based on single linear architectures, including Turing-complete blockchains like Ethereum, are increasingly unable to meet the growing market demand. They face serious challenges in scalability and transaction processing speed. Blockchain parallelization technology has emerged to address these issues, aiming to enable the concurrent processing of multiple transactions.

Parallel Execution Model for Blockchain Smart Contract Transaction (Source: jos.org）

Parallelized blockchain introduces a design of parallel processing within the blockchain, allowing multiple transactions or smart contracts to be processed simultaneously rather than sequentially. This mechanism enables the blockchain network to handle more transactions at the same time, significantly increasing throughput and reducing transaction latency, thus becoming a core solution for meeting large-scale application demands.

This article delves into the core principles of blockchain parallelization, analyzing its advantages and challenges in practical applications. It showcases the exploration and practice of leading projects in parallelization technology, aiming to provide valuable insights for the future development of blockchain technology.

Technical Implementation Strategies

Parallel execution, a technique that allows multiple tasks to run simultaneously, has been widely applied in fields like data processing and graphics rendering. Introducing this concept into blockchain systems effectively reduces transaction processing times and addresses the growing computational power demands.

There are various methods for implementing parallel processing. Some blockchain projects focus on the parallel execution of smart contracts, while others target parallelization in transaction verification and state updates. However, each method faces specific technical challenges as it seeks to improve network efficiency, with the implementation details depending on the chosen approach.

Parallel execution versus traditional execution paths (Source: foresightnews.pro）

State Access / Optimistic Model

Most blockchains with parallel execution capabilities rely on two popular methods: the state access method and the optimistic model.

The state access method is a strategic approach that proactively identifies which transactions can access specific parts of the blockchain state, thus allowing the blockchain to designate independent transactions. In contrast, the optimistic model assumes that all transactions are independent, only verifying this assumption retrospectively and making adjustments if necessary.

In the state access model, transaction execution typically uses an optimistic concurrency control strategy, assuming that transactions do not conflict. Rollbacks occur only when conflicts actually arise. This method enhances transaction throughput and improves user experience, although it requires a precisely designed conflict detection mechanism to ensure data consistency and system security.

Sharding Architecture

Sharding is one of the most common solutions for parallelizing blockchains. Its core idea is to divide the blockchain network into multiple shards, allowing each shard to independently process transactions and data. This design significantly improves network processing capacity and scalability, addressing the performance bottleneck of traditional blockchains. Current projects that utilize sharding technology include Ethereum 2.0, Zilliqa, NEAR Protocol, and QuarkChain. These projects effectively address blockchain scalability issues through sharding, enhancing network efficiency.

When applied to blockchain applications, sharding technology is typically implemented in the following three methods:

As we can see, sharding technology can effectively partition transactions. Although each sharding method has its own advantages in improving scalability, they all face the common challenge of cross-shard communication. Continuous refinement of data consistency algorithms is necessary to ensure the system’s overall performance.

Taking TON’s Dynamic Sharding as an Example

In a sharded blockchain architecture, TON (The Open Network) stands out due to its “dynamic sharding” design. Using the “Infinite Sharding Paradigm” (ISP), TON can adjust the number of shards flexibly to accommodate real-time network demands, achieving efficient shard management. This architecture demonstrates significant performance potential, enabling TON to maintain high performance while handling large transaction volumes and addressing the scalability issues that traditional blockchains face.

TON’s sharding structure is composed of four levels of chains:

1. AccountChain: A transaction chain linked to a specific account. Typically a virtual concept, the AccountChain provides an independent transaction record for each account, ensuring chained ordering and state consistency under specific rules.
2. ShardChain: A collection of multiple AccountChains, primarily responsible for processing transactions and data. The independence of each ShardChain allows each shard to maintain its transaction state independently.
3. WorkChain: Composed of multiple ShardChains with customizable rules. For example, a WorkChain based on EVM can be created to support specific smart contract environments. The flexibility of WorkChains allows users to tailor the chain structure for specific needs, though their creation requires a strict governance process.
4. MasterChain: The core chain of the TON network, providing finality for all ShardChains. Once the block hash of a ShardChain is merged into the MasterChain block, it becomes immutable.

TON’s unique sharding structure supports parallel processing across multiple chains, with efficient coordination achieved through the MasterChain (Source: OKX)

In practice, TON dynamically adjusts the number of shards to respond to changes in network load. The number of ShardChains increases or decreases automatically depending on the current load, allowing the network to operate efficiently: when the load increases, TON refines the shards to handle more transactions; when the load decreases, shards merge to conserve resources. Through the Infinite Sharding Paradigm, TON can support an almost unlimited number of shards, theoretically reaching 2 to the power of 60 WorkChains. Additionally, TON adapts by automatically creating more shards in regions experiencing increased transaction frequency, improving processing efficiency.

The dynamic sharding design heavily relies on cross-chain communication. For this, TON introduced the hypercube routing algorithm. Based on high-dimensional topology, this algorithm assigns a unique identifier to each WorkChain node, enabling information transfer between chains via the shortest path, meeting routing needs in a large-scale sharded environment. Furthermore, TON developed “Instant Hypercube Routing,” which leverages the Merkle Trie root node to provide proof of routing, simplifying complex cross-chain messaging and enhancing communication efficiency.

Combining with PoS Consensus Mechanism

Compared to the traditional Proof of Work (PoW) mechanism, the Proof of Stake (PoS) mechanism selects nodes with more tokens to participate in consensus, reducing the concentration of computing power and minimizing competition and energy consumption among miners. This enhances efficiency while ensuring system security and decentralization. Ethereum 2.0’s combination of PoS and sharding is a classic example of this technology.

Specifically, Ethereum 2.0 divides the network into multiple shards and uses the PoS consensus mechanism to assign tasks among multiple validators, with each validator responsible for verifying transactions within one shard, significantly increasing throughput. PoS also reduces the risk of any single validator gaining excessive control by randomly selecting validators, enhancing the decentralized nature of the blockchain network. Regarding security, each shard’s validation is managed by different node groups, so an attacker would need to control multiple shards to launch an attack, making it harder to carry out a 51% attack. This multi-layered protection mechanism improves network security.

Similarly, NEAR Protocol [2] also combines PoS and sharding technology. Through its “Nightshade” protocol, NEAR integrates PoS consensus in a parallelized blockchain design, increasing efficiency while allowing each shard to maintain only its part of the state. This not only ensures global network consistency but also enhances system security.

Computation-Based Parallelism

Computation-based parallel execution is a relatively new concept that aims to optimize blockchain processing efficiency by breaking down complex computational tasks into smaller units for parallel execution. Although this innovative model has not yet gained widespread adoption, its potential revolutionary impact is noteworthy.

In practice, complex computations are distributed to different nodes for parallel execution, and the results are aggregated after each node completes its calculations. This approach improves computational efficiency, reduces transaction latency, and is well-suited for computation-intensive applications. However, implementing this method presents several challenges, such as ensuring communication efficiency between nodes and achieving final consistency of computational results.

Two Prominent Case Studies

In the evolution of blockchain technology, Ethereum 2.0 and Polkadot emerge as two pioneering examples. These projects are at the forefront of addressing critical challenges in the blockchain space—namely, scalability, security, and sustainability. Let’s delve into a detailed analysis of these two groundbreaking cases.

Ethereum 2.0

Ethereum 2.0 (Eth2) is a major upgrade to the Ethereum 1.0 network that aims to enhance scalability, security, and sustainability. Parallel execution is a key component in achieving these goals.

By transitioning from the Proof of Work (PoW) mechanism to Proof of Stake (PoS), Ethereum 2.0 introduces sharding, dividing the entire blockchain network into smaller “shards.” Each shard can independently process and verify transactions, significantly increasing overall throughput. Additionally, Ethereum 2.0 allows each shard to maintain its own independent state, further boosting parallel execution efficiency and reducing the load on the main chain, thereby enabling more efficient transaction processing. Lastly, Ethereum 2.0 incorporates an efficient cross-shard communication mechanism to ensure data consistency and interaction between different shards, which is essential for supporting complex decentralized applications [3].

Through parallel processing, Ethereum 2.0 is expected to greatly increase transaction processing speed, effectively addressing the growing user demand and diverse application scenarios, particularly in sectors like DeFi and NFTs. In summary, by introducing parallel execution, Ethereum 2.0 not only achieves a technical breakthrough but also establishes a stronger foundation for the growth of decentralized applications, advancing the adaptability of the Ethereum network in the future.

Illustration of Ethereum 2.0 data sharding (Source: sohu.com)

Polkadot

Polkadot is an innovative multi-chain network protocol designed to enable interoperability and scalability between blockchains. As a heterogeneous multi-chain architecture, Polkadot consists of a centralized “Relay Chain” and multiple independent “Parachains.” Each Parachain can have its own governance and economic model, allowing different blockchains to communicate and share data efficiently.

Polkadot’s design leverages a shared security mechanism, ensuring that all Parachains benefit from the security provided by the Relay Chain, thus reducing the security burden on each individual Parachain. Additionally, Polkadot employs parallel execution technology, allowing multiple Parachains to process transactions simultaneously, significantly increasing the network’s overall throughput. This parallel processing capability enables Polkadot to handle growing transaction demands effectively, especially in DeFi, NFT, and other complex application scenarios [4].

Polkadot’s Cross-Chain Message Passing (XCMP) mechanism enables seamless interaction between different Parachains, providing developers with greater scope for innovation. Through XCMP, developers can create interconnected decentralized applications, further promoting the ecosystem’s growth.

Polkadot interoperability structure (Source: What is Polkadot? A Brief Introduction - ImmuneBytes)

Feature Comparison

Ethereum 2.0 VS. Polkadot (Table source: Gate Learn)

Alternative Solutions

Addressing blockchain scalability challenges remains a key area of research. In addition to parallel execution technology, several alternative solutions for scalability are worth exploring.

Layer 2 Solutions

Layer 2 (L2) solutions are specifically designed to expand blockchain capacity. At their core, they provide an independent execution layer, typically consisting of two parts: a network for processing transactions and smart contracts deployed on the underlying blockchain. The smart contracts handle disputes and relay consensus results from the L2 network to the main chain for validation and confirmation.

Layer 2 solutions offer distinct advantages and technical features. First, they significantly improve scalability since transactions don’t need to be individually confirmed on the main chain. L2 can handle a higher transaction volume, alleviating congestion on Layer 1 networks (such as Ethereum and Bitcoin), and substantially reducing transaction fees through off-chain processing. Although most operations occur off-chain, L2 still relies on the security of the main chain, ensuring that final transaction results are both trustworthy and immutable.

Common L2 solutions include state channels, Rollups, and Plasma. State channels allow multiple participants to interact off-chain frequently, submitting the final state to the blockchain only at the end; Bitcoin’s Lightning Network is a typical example. Rollups, currently the most widely adopted L2 solution, are split into Optimistic Rollups and zk-Rollups: Optimistic Rollups assume transactions are valid unless contested, while zk-Rollups use zero-knowledge proofs to ensure transaction accuracy when data is submitted. Plasma is a framework allowing the creation of multi-layer subchains, each capable of handling numerous transactions.

Layer 2 solutions overview (Source: blackmountainig.com)

Improving Consensus Mechanisms

Improving consensus mechanisms is also an effective approach to enhance blockchain scalability. This involves introducing more efficient consensus algorithms (such as Proof of Stake (PoS) and Byzantine Fault Tolerance (BFT)) to increase transaction processing speed. Compared to the traditional Proof of Work (PoW), these new consensus mechanisms are faster in transaction confirmation and significantly reduce energy consumption, aligning better with sustainable development requirements.

Furthermore, these mechanisms accelerate the consensus process by determining block generators based on factors such as the tokens held by validator nodes. However, despite the many advantages of improved consensus mechanisms, transitioning from existing mechanisms to new ones often comes with technical challenges and risks, especially compatibility issues and system instability during the transition period. Some consensus mechanisms may also lead to power centralization, creating a “rich get richer” phenomenon, potentially threatening the core principle of blockchain decentralization. Nevertheless, for blockchain networks with high requirements for transaction processing efficiency and energy consumption, improving consensus mechanisms remains a worthwhile scalability solution to explore.

PoW vs. PoS consensus mechanisms (Source: blog.csdn.net）

Optimizing Block Parameters

Optimizing block parameters involves adjusting key parameters like block size and block time to improve blockchain processing capacity and responsiveness. This approach offers quick performance improvements, is relatively simple to implement, and has low implementation costs, making it well-suited to scenarios requiring a rapid response, such as handling surges in traffic or short-term spikes in transactions.

However, relying solely on parameter adjustments often has limited impact, and balancing network performance with stability is essential. Excessive or extreme parameter changes may cause network congestion or conflicts in the consensus mechanism. Therefore, block parameter optimization is typically suited for scenarios with short-term performance demands, such as swiftly responding to market changes.

Each scalability solution is best suited for different use cases. When choosing the appropriate scalability solution, decision-makers should ensure that the selected solutions can complement each other, providing the industry with a more flexible and efficient scalability path.

Solution Comparison

Comparison of Different Scaling Solutions (Table Source: Gate Learn)

Summary of Advantages

Increased Throughput

Compared to traditional sequential processing models, parallel chain networks can achieve transaction processing speeds (TPS) up to 100 times greater than sequential processing. For instance, Solana’s SeaLevel architecture [6] can handle over 50,000 TPS under optimal conditions. While actual speed may vary with network demand, this performance far exceeds that of traditional blockchains.

Effective horizontal scalability has become essential with the rapid growth in network traffic. Parallelized blockchains introduce multi-threaded parallel processing, giving blockchain networks the capacity to scale with increasing user demand. This is particularly beneficial in high-frequency transaction applications like gaming and supply chains, where parallel design enables decentralized task processing to maintain system stability and response speed, meeting the throughput demands of large-scale applications.

Solana parallel processing path (Source: blog.slerf.tools）

Reduced Latency

Parallel processing of independent transactions significantly reduces the delay from transaction submission to execution, which is highly valuable in real-time data processing. In scenarios requiring rapid response—such as decentralized finance (DeFi)—real-time transaction confirmation not only enhances user experience but also reduces transaction risks and system load pressure associated with delays.

For example, Sui’s parallel execution model introduces an innovative mechanism allowing simple transactions, which do not require complex consensus, to bypass the consensus mechanism, drastically shortening confirmation times. Compared to traditional serial processing, this parallel design supports real-time transaction execution, which is key to maintaining system stability and a smooth user experience.

As cross-chain communication protocols and new parallel execution technologies continue to evolve, blockchain networks will achieve more efficient operating modes. Low latency and high throughput will also become crucial indicators of market competitiveness.

Optimized Resource Utilization

In traditional blockchains, where transactions are processed sequentially, most of the time only one node performs operations while other nodes wait, leading to resource idleness. Parallel technology allows multiple validators and processor cores to work simultaneously, breaking the processing bottleneck of a single node and maximizing the efficiency of network resources.

This optimization of resource utilization not only eliminates “idle periods” during transaction processing but also significantly boosts overall network performance, especially under high-load conditions, enabling the network to handle more transaction requests with reduced latency.

Lower Transaction Costs

Unlike traditional sequential processing, parallel execution enables more flexible and efficient cross-market transaction execution through refined market management and optimized resource allocation, significantly reducing the computational load for smart contract execution and thus lowering gas fees. This design maximizes network resource use and avoids the waste of computational resources caused by single-task queuing.

With rational load distribution, resources are allocated efficiently, so validators and processing nodes don’t need to handle redundant data, resulting in a more economical blockchain transaction environment for developers and users.

Sei Network’s explanation of parallel execution on social media（Source: x）

Risk Analysis

Security Risks

Sharding divides the blockchain into multiple independent shards, which can allow attackers to focus efforts on a specific shard to gain control over it. If an attacker successfully captures a shard, they can manipulate transactions and data within it, posing a serious threat to the network’s overall security. This local control can lead to improper operations, data tampering, and possibly escalate attacks on other shards, compromising the integrity and trustworthiness of the entire blockchain.

Additionally, the security of cross-shard communication is crucial. If cross-shard communication is not secure, it may lead to data loss, tampering, or transmission errors, creating potential trust issues within the system.

Technical Complexity

Cross-shard transactions require coordinating state data across different shards to ensure atomicity of transactions. To prevent transaction failures due to delays or network issues, developers also need to optimize messaging and state synchronization mechanisms.

This challenge not only increases system design complexity but also requires new strategies within contract logic to handle potential errors and inconsistencies. Successfully executing cross-shard smart contracts depends not only on the underlying blockchain’s technical capabilities but also on implementing more complex strategies in contract design to ensure smooth and efficient execution in a sharded environment.

Lack of Interoperability

Current parallel blockchain technology lacks standardization, with different platforms adopting varying technologies and protocols. This diversity has led to significant differences in consensus mechanisms, data structures, and protocol layers. While this diversity has driven innovation, it has also significantly reduced interoperability between different blockchains, making cross-chain operations more complex and difficult.

The lack of interoperability not only restricts the free flow of assets between different blockchains but may also pose security risks, such as potential asset loss in cross-chain operations. Therefore, addressing the interoperability risks of parallel execution requires technological innovation and standardization and widespread cooperation within the industry to establish a more robust ecosystem.

Future Recommendations

Future research in parallelized blockchain should focus on optimizing cross-shard communication.

The industry should actively explore standardized protocols and interoperability frameworks to ensure data consistency and accurate transaction processing across shards to promote seamless system integration and resource sharing, thus enhancing synergy within the blockchain ecosystem. In addition, security remains a key aspect of sharding optimization, future research should develop stronger security models to protect against malicious attacks and incorporate emerging technologies such as zero-knowledge proofs and homomorphic encryption to enhance privacy and interoperability on-chain.

Regarding application expansion, there are already successful case studies to draw from. For example, Uniswap has significantly improved response capabilities through parallel processing, thus reducing transaction costs and optimizing cross-border payment processes. Different industries should explore diversified parallel chain applications to unlock their value across various domains. This would help lay a solid foundation for an efficient, transparent, and sustainable tech development environment, accelerating digital transformation and supporting a more efficient digital economy future.

References

1.https://foresightnews.pro/article/detail/34400
2.https://pages.near.org/papers/nightshade/
3.https://www.sohu.com/a/479352768_121118710
4..https://www.immunebytes.com/blog/what-is-polkadot-a-brief-introduction/
5.https://blackmountainig.com/overview-of-layer-2-scaling-solutions/
6.https://www.sealevel.com/