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Web3 Parallel Computing Panorama: Five Paradigms of EVM Chain Breaking Performance Boundaries
Web3 Parallel Computing Track Overview: The Best Solution for Native Scalability?
The "impossible triangle" of blockchain—"security", "decentralization", and "scalability"—reveals the essential trade-offs in the design of blockchain systems, meaning that it is difficult for blockchain projects to achieve "extreme security, universal participation, and high-speed processing" simultaneously. Regarding the eternal topic of "scalability", the mainstream blockchain scaling solutions currently on the market are categorized by paradigm, including:
Blockchain scaling solutions include: on-chain parallel computing, Rollup, sharding, DA modules, modular architecture, Actor systems, zk proof compression, Stateless architecture, etc., covering multiple levels of execution, state, data, and structure, forming a complete scaling system of "multi-layer collaboration and modular combination." This article focuses on the mainstream scaling method based on parallel computing.
In-chain parallel computing focuses on the parallel execution of transactions/instructions within the block. Based on the parallel mechanism, its scalability can be divided into five major categories, each representing different performance pursuits, development models, and architectural philosophies. The parallel granularity becomes finer, the parallel intensity increases, the scheduling complexity also rises, and the programming complexity and implementation difficulty become greater.
The off-chain asynchronous concurrency model, represented by the Actor system, belongs to another parallel computing paradigm. As a cross-chain/asynchronous messaging system, each Agent operates as an independent "agent process," using asynchronous messaging in a parallel manner, driven by events and without the need for synchronized scheduling. Representative projects include AO, ICP, Cartesi, etc.
The well-known Rollup or sharding scalability solutions belong to system-level concurrency mechanisms and do not fall under on-chain parallel computing. They achieve scalability by "running multiple chains/execution domains in parallel" rather than increasing the parallelism within a single block/virtual machine. Such scalability solutions are not the focus of this discussion, but we will still use them for a comparative analysis of architectural concepts.
2. EVM-based Parallel Enhanced Chain: Breaking Performance Boundaries in Compatibility
The development of Ethereum's serial processing architecture has gone through multiple rounds of scaling attempts, including sharding, Rollup, and modular architecture, but the throughput bottleneck of the execution layer has still not achieved a fundamental breakthrough. At the same time, EVM and Solidity remain the most developer-friendly and ecologically potent smart contract platforms today. Therefore, EVM-based parallel enhancement chains are becoming a key path that balances ecological compatibility and execution performance improvement, and are emerging as an important direction for the new round of scaling evolution. Monad and MegaETH are the most representative projects in this direction, building an EVM parallel processing architecture aimed at high concurrency and high throughput scenarios, from the perspectives of delayed execution and state decomposition, respectively.
Analysis of Monad's Parallel Computing Mechanism ###
Monad is a high-performance Layer 1 blockchain designed for the Ethereum Virtual Machine, based on the fundamental parallel concept of pipelining, with asynchronous execution at the consensus layer and optimistic parallel execution at the execution layer. In addition, at the consensus and storage layers, Monad introduces high-performance BFT protocols (MonadBFT) and dedicated database systems (MonadDB), achieving end-to-end optimization.
Pipelining: Multi-stage Pipeline Parallel Execution Mechanism
Pipelining is the basic concept of parallel execution in Monads. Its core idea is to decompose the execution process of the blockchain into multiple independent stages and parallelize the processing of these stages, forming a three-dimensional pipeline architecture. Each stage runs on independent threads or cores, achieving concurrent processing across blocks and ultimately improving throughput and reducing latency. These stages include: transaction proposal (Propose), consensus achievement (Consensus), transaction execution (Execution), and block submission (Commit).
Asynchronous Execution: Consensus - Asynchronous Decoupling
In traditional blockchains, transaction consensus and execution are typically synchronous processes, and this serial model severely limits performance scalability. Monad achieves asynchronous consensus layer, asynchronous execution layer, and asynchronous storage through "asynchronous execution." This significantly reduces block time and confirmation delay, making the system more resilient, the processing flow more segmented, and resource utilization higher.
Core Design:
Optimistic Parallel Execution: Optimistic Parallel Execution
Traditional Ethereum uses a strict serial model for transaction execution to avoid state conflicts. In contrast, Monad adopts an "optimistic parallel execution" strategy, significantly increasing transaction processing speed.
Implementation mechanism:
Monad has chosen a compatible path: minimizing changes to EVM rules as much as possible, implementing parallelism by delaying state writes and dynamically detecting conflicts during execution, resembling a performance version of Ethereum. Its maturity facilitates the migration of the EVM ecosystem, making it a parallel accelerator in the EVM world.
Analysis of the parallel computing mechanism of MegaETH
Differentiated from the L1 positioning of Monad, MegaETH is positioned as a modular high-performance parallel execution layer compatible with EVM, which can serve as an independent L1 public chain or as an execution enhancement layer or modular component on Ethereum. Its core design goal is to deconstruct account logic, execution environment, and state into independently schedulable minimal units to achieve high concurrent execution and low-latency response capabilities within the chain. The key innovation proposed by MegaETH lies in: Micro-VM architecture + State Dependency DAG (Directed Acyclic Graph of State Dependencies) and a modular synchronization mechanism, collectively building a parallel execution system aimed at "in-chain threading".
Micro-VM Architecture: Account as Thread
MegaETH introduces an execution model of "one micro virtual machine per account," which threadizes the execution environment, providing the smallest isolation unit for parallel scheduling. These VMs communicate via asynchronous messaging instead of synchronous calls, allowing a large number of VMs to execute independently and store independently, resulting in natural parallelism.
State Dependency DAG: A scheduling mechanism driven by dependency graphs
MegaETH has built a DAG scheduling system based on account state access relationships. The system maintains a global dependency graph in real-time, modeling all account modifications and reads for each transaction as dependency relationships. Non-conflicting transactions can be executed directly in parallel, while dependent transactions will be scheduled and sorted in a serial or deferred manner according to topological order. The dependency graph ensures state consistency and non-repetitive writes during the parallel execution process.
Asynchronous Execution and Callback Mechanism
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In summary, MegaETH breaks the traditional EVM single-threaded state machine model by implementing micro virtual machine encapsulation on an account basis, scheduling transactions through a state dependency graph, and replacing synchronous call stacks with an asynchronous messaging mechanism. It is a parallel computing platform that is redesigned in a full-dimensional way from "account structure → scheduling architecture → execution process," providing a paradigm-level new approach for building the next generation of high-performance on-chain systems.
MegaETH has chosen a reconstruction path: thoroughly abstracting accounts and contracts into an independent VM, releasing extreme parallel potential through asynchronous execution scheduling. Theoretically, MegaETH's parallel limit is higher, but it is also more difficult to control the complexity, resembling a super distributed operating system under the Ethereum concept.
The design philosophies of Monad and MegaETH differ significantly from sharding: sharding horizontally divides the blockchain into multiple independent sub-chains, with each sub-chain responsible for part of the transactions and states, breaking the single-chain limitations for network layer scalability; whereas both Monad and MegaETH maintain the integrity of a single chain, only horizontally scaling at the execution layer, optimizing for extreme parallel execution within the single chain to break performance limits. The two represent vertical strengthening and horizontal expansion in the path of blockchain scalability.
Projects like Monad and MegaETH focus primarily on throughput optimization paths, aiming to enhance the on-chain TPS as a core goal. They achieve transaction-level or account-level parallel processing through delayed execution and micro virtual machine architecture. Pharos Network, as a modular, full-stack parallel L1 blockchain network, features a core parallel computing mechanism known as "Rollup Mesh." This architecture supports multi-virtual machine environments (EVM and Wasm) through the collaboration of the mainnet and special processing networks (SPNs), and integrates advanced technologies such as zero-knowledge proofs (ZK) and trusted execution environments (TEE).
Analysis of the Rollup Mesh Parallel Computing Mechanism:
In addition, Pharos has restructured the execution model from the bottom of the storage engine through multi-version Merkle trees, delta encoding, version addressing, and ADS sinking technology, launching the native blockchain high-performance storage engine Pharos Store, achieving high throughput, low latency, and strong verifiable on-chain processing.