The Rise of Parallel EVM: An Overview
Introduction:
Parallel computing is emerging as a key sector in the competition among next-generation public chains. Whether it’s early pioneers like Solana or Aptos, which introduced the Block-STM through the Move language ecosystem, or EVM-compatible chains like Monad and Sei, which focus on enhancing transaction processing capabilities, parallel EVM chains are thriving everywhere.
In this article, we will explore the how Parallel EVM has grown in popularity.
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The operation mechanism of parallel EVM mainly enhances transaction processing capacity by simultaneously executing transactions on multiple processors. This mechanism can be implemented in several ways, including message passing, shared memory, and optimistic parallel models. The goal of parallel EVM is to address the performance bottlenecks that traditional EVM faces when processing large volumes of transactions.
Genesis: Solana and Block-STM
Parallel mechanisms have long existed, with Solana being the first mainstream public chain to implement them on a large scale. Solana primarily achieves parallelism through its Sealevel technology. Sealevel allows Solana VM to process tens of thousands of contracts simultaneously, thus improving execution efficiency.
Solana’s Sealevel technology combines Proof of History (PoH) and Proof of Stake (PoS) to achieve parallel transaction processing. It enables Solana to handle multiple transactions simultaneously, thereby increasing network throughput and security.
Solana’s program library supports automatic identification of the accounts that need read-write access when submitting transactions, enabling parallel processing. This allows each order to be processed more efficiently for parallel execution across different processing units. Combined with the computational power of modern hardware, this technology significantly improves the performance of smart contracts and the overall efficiency of blockchain networks.
Move language’s Block-STM (Parallel Execution Engine for Software Transactional Memory) also accelerates smart contract processing through parallel mechanisms, developed based on the Diem project running on Aptos.
Specifically, Block-STM utilizes the principles of Software Transactional Memory (STM), where transactions within each block are assumed to have no dependencies, allowing these transactions to be executed concurrently on different processor threads. This not only improves processing speed but also effectively utilizes hardware resources such as multi-core processors.
Moreover, a key feature of Block-STM is its ability to dynamically detect and resolve potential conflict issues. During execution, if certain transactions violate the predefined order or have data dependencies, the system automatically adjusts the execution order or takes other measures to ensure the consistency and correctness of results.
Block-STM’s design enables it to be compatible with existing blockchains without the need to modify them or adopt new technologies by miner/validator nodes, benefiting all nodes, whether in validation or transaction blocking.
In summary, Block-STM effectively improves the processing speed of smart contracts through pre-sorted parallel execution mechanisms while maintaining the consistency and determinism of execution results. The application of this technology not only enhances the performance of blockchain networks but also provides new possibilities for the future development of blockchain technology.
EVM Compatibility & Highlight Projects
The combination of parallel mechanisms and EVM has given rise to a series of innovative projects, the core of which is to provide parallel execution capabilities without changing EVM compatibility. Highlight projects include:
Monad: Dedicated to solving the scalability issues of traditional EVM, a Layer 1 blockchain that adopts parallel execution strategies to improve processing capacity and efficiency.
Sei: Sei V2 is a significant upgrade to the Sei network, aiming to be the first fully parallel EVM, offering backward compatibility with EVM smart contracts and employing optimistic parallelization technology.
Neon: Neon is a Layer 2 solution that brings EVM into the Solana ecosystem, aiming to enhance its overall performance by integrating the Solana ecosystem with EVM.
Artela: Artela utilizes parallel functionality and combines it with elastic computing to achieve dynamic block space, allowing DApps to maximize the advantages of parallel execution.
Sei V2: Utilizing Optimistic Parallelization Technology
Among them, the Sei V2 version is crucial. Sei V2 significantly improves the network’s ability to process large transactions through optimized parallel processing mechanisms. This optimization includes improved scheduling algorithms and technologies to effectively manage and execute parallel tasks while maintaining the correctness of transactions. Additionally, it adopts optimistic parallelization technology, an optimistic approach to transaction processing that allows transactions to be executed without full confirmation, thus improving transaction speed and efficiency.
Sei V2’s optimistic parallelization technology primarily works based on optimistically assuming that all transactions can be processed in parallel, allowing the blockchain to execute multiple transactions concurrently without explicit dependencies among them. When potential transaction conflicts exist, meaning there might be unrecognized dependencies between transactions, Sei V2 employs specific strategies to handle these conflicts. Specifically, Sei V2 tracks the storage portions involved in each transaction and reorders and executes transactions involving different storage portions to ensure data consistency and integrity.
Furthermore, while optimistic parallelization technology itself does not require developers to define any dependencies, it still effectively manages and resolves issues arising from transaction conflicts. Under this mechanism, the idealized TPS can reach over 1000.
Monad: Asynchronous Execution
Monad optimizes the transaction processing using parallel technology, mainly by decomposing the Ethereum Virtual Machine (EVM) into multiple independent components and processing these components in parallel. This approach allows other transactions to be prepared or queued for processing while one transaction is being executed, thus significantly improving transaction processing speed (TPS).
Specifically, in Monad’s parallel EVM mechanism, all pending transactions are first divided into different zones or groups in order to effectively manage and process large amounts of transaction data for subsequent parallel processing. Then, efficient scheduling algorithms are used to manage transactions within these zones or groups. This scheduling algorithm ensures that transactions within each zone or group receive reasonable processing time, thus achieving optimal resource allocation and utilization.
Ideally, Monad’s TPS can reach 10,000 transactions, with the potential to reach 400,000 TPS when combined with hardware acceleration. Moreover, Monad retains full compatibility with EVM bytecode and Ethereum RPC API, allowing developers to seamlessly migrate their applications to Monad.
Neon: Bridging Solana and EVM
Neon EVM leverages the advantages of the Solana network, such as low fees, high transaction speeds, and parallel transaction execution capabilities, enabling DApps developed in Solidity and Vyper languages to run directly on the Solana network.
To achieve resource coordination and optimization, Neon EVM adopts the concepts of elastic computing and elastic block space. Elastic computing allows the network to dynamically allocate and adjust computing resources based on demand and load, while elastic block space adjusts block size dynamically according to the number of transactions and data size in the network.
Neon EVM effectively manages and executes parallel tasks while maintaining the correctness and order of transactions through optimized algorithms, including optimizing scheduling strategies for smart contracts to reduce errors and conflicts introduced by parallel execution.
Artela: Elastic Computing + Parallel EVM
Artela’s parallel EVM mechanism design primarily focuses on improving the scalability and performance of blockchain networks. Artela achieves this goal by introducing parallel EVM and elastic computing.
Firstly, Artela’s parallel EVM mechanism allows multiple transactions to be processed concurrently, rather than the traditional sequential processing method. This parallel processing significantly improves transaction efficiency and throughput. Additionally, Artela combines elastic block space, a mechanism for dynamically adjusting block sizes, to adapt to changes in network load and transaction volume, further optimizing network performance.
In conclusion, the development of parallel EVM has followed a long path of parallelization before the transformation of EVM. The parallel EVM route is not exclusive to Layer 2 on Ethereum but instead exhibits a more universal appeal, with any L1/L2 network capable of adapting its mechanisms to parallel EVM.
Throughout this historical process, Solana and Move’s Block-STM have undergone both theoretical and practical explorations, subsequently absorbed by other projects to give birth to innovations such as Neon, Monad, Artela, and Sei V2, among many others.
