Web3 Parallel Computing Track Overview: The Best Solution for Native Scalability?

1. Overview of Parallel Computing

The "Blockchain Trilemma" reveals the essential trade-offs in the design of blockchain systems: "security", "decentralization", and "scalability", indicating that it is challenging for blockchain projects to achieve "ultimate security, universal participation, and high-speed processing" simultaneously. Regarding the eternal topic of "scalability", the mainstream blockchain scaling solutions currently on the market can be categorized by paradigms, including:

• Implement enhanced scalability: elevate execution capabilities on the spot, such as parallel processing, GPU, and multi-core.
• State-isolated scaling: horizontal partitioning of state/Shard, such as sharding, UTXO, multi-subnets
• Off-chain outsourcing scaling: execute outside the chain, such as Rollup, Coprocessor, DA
• Decoupled structure expansion: modular architecture, collaborative operation, such as modular chains, shared sequencers, Rollup Mesh
• Asynchronous concurrent scaling: Actor model, process isolation, message-driven, such as agents, multi-threaded asynchronous chains

Blockchain scaling solutions include: on-chain parallel computing, Rollup, sharding, DA modules, modular structures, Actor systems, zk-proof compression, Stateless architecture, etc., covering multiple levels of execution, state, data, and structure. It is a complete scaling system of "multi-layer collaboration and modular combination." This article focuses on the mainstream scaling method based on parallel computing.

Intra-chain parallelism (, focusing on the parallel execution of transactions/instructions within the block. According to the parallel mechanism, its scalability can be divided into five major categories, each representing different performance pursuits, development models, and architectural philosophies. The granularity of parallelism becomes finer, the intensity of parallelism increases, the scheduling complexity also rises, and the complexity of programming and implementation difficulty increases.

• Account-level parallelism: Represents the Solana project
• Object-level parallelism: represents the Sui project
• Transaction-level: represents the projects Monad, Aptos
• Call-level / MicroVM parallelism: represents the project MegaETH
• Instruction-level parallelism: Represents the project GatlingX

The off-chain asynchronous concurrent model, represented by the Actor agent system (Agent / Actor Model), belongs to another paradigm of parallel computing. As a cross-chain/asynchronous messaging system (non-block synchronization model), each Agent operates as an independent "agent process," using asynchronous messaging in a parallel manner, driven by events and requiring no synchronized scheduling. Representative projects include AO, ICP, Cartesi, and others.

The well-known Rollup or sharding scalability solutions are system-level concurrency mechanisms and do not belong to 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 article, but we will still use them for comparative analysis of architectural concepts.

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2. EVM System Parallel Enhanced Chain: Breaking Performance Boundaries in Compatibility

The serial processing architecture of Ethereum has evolved through multiple rounds of scaling attempts, including sharding, Rollup, and modular architecture, but the throughput bottleneck at the execution layer has still not achieved a fundamental breakthrough. Meanwhile, EVM and Solidity remain the most developer-friendly and ecologically powerful smart contract platforms today. Therefore, EVM-based parallel enhancement chains, which balance ecological compatibility and improved execution performance, are becoming an important direction for the next round of scaling evolution. Monad and MegaETH are the most representative projects in this direction, respectively building EVM parallel processing architectures aimed at high concurrency and high throughput scenarios based on delayed execution and state decomposition.

) Analysis of Monad's Parallel Computing Mechanism

Monad is a high-performance Layer 1 blockchain redesigned for the Ethereum Virtual Machine (EVM), 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 a high-performance BFT protocol (MonadBFT) and a dedicated database system (MonadDB) to achieve 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 break down the execution process of the blockchain into multiple independent stages and process these stages in parallel, forming a three-dimensional pipeline architecture. Each stage runs on independent threads or cores, achieving cross-block concurrent processing, 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-Execution Asynchronous Decoupling

In traditional blockchains, transaction consensus and execution are usually synchronous processes, and this serial model severely limits performance scalability. Monad achieves asynchronous consensus layer, asynchronous execution layer, and asynchronous storage through "asynchronous execution". It significantly reduces block time and confirmation delays, making the system more resilient, processing flows more granular, and resource utilization more efficient.

Core Design:

• The consensus process (consensus layer) is only responsible for ordering transactions and does not execute contract logic.
• The execution process (execution layer) is triggered asynchronously after consensus is reached.
• Immediately enter the consensus process for the next block after consensus is reached, without waiting for execution to complete.

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.

Execution mechanism:

• Monad will optimistically execute all transactions in parallel, assuming that most transactions have no state conflicts.
• Run a "Conflict Detector (Conflict Detector###)" simultaneously to monitor whether transactions access the same state (such as read/write conflicts).
• If a conflict is detected, conflicting transactions will be serialized and re-executed to ensure state correctness.

Monad has chosen a compatible path: minimizing changes to EVM rules, achieving parallelism during execution by delaying state writes and dynamically detecting conflicts. It resembles a performance version of Ethereum, with good maturity that facilitates EVM ecosystem migration, serving as a parallel accelerator in the EVM world.

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) Parallel computational analysis of MegaETH

Unlike 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 isolate and 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 innovations proposed by MegaETH are: Micro-VM architecture + State Dependency DAG (Directed Acyclic Graph of State Dependencies) and a modular synchronization mechanism, collectively constructing a parallel execution system aimed at "in-chain threading."

Micro-VM Architecture: Account as Thread

MegaETH introduces an execution model of "one Micro-VM per account", which "threads" the execution environment, providing the smallest isolation unit for parallel scheduling. These VMs communicate via Asynchronous Messaging, rather than synchronous calls, allowing a large number of VMs to execute and store independently, thus enabling natural parallelism.

State Dependency DAG: Dependency Graph Driven Scheduling Mechanism

MegaETH has built a DAG scheduling system based on account state access relationships, which maintains a global dependency graph in real-time. Each transaction modifies certain accounts and reads from others, all modeled as dependencies. Non-conflicting transactions can be executed directly in parallel, while transactions with dependencies will be scheduled in a serial or delayed 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 at the account level, 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 from the "account structure → scheduling architecture → execution process" across all dimensions, providing a paradigm-level new idea for building the next generation of high-performance on-chain systems.

MegaETH has chosen a reconstruction path: completely abstracting accounts and contracts into an independent VM, releasing extreme parallel potential through asynchronous execution scheduling. Theoretically, MegaETH has a higher parallel limit, but it is also more challenging to control complexity, resembling a super distributed operating system under the Ethereum philosophy.

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The design concepts of Monad and MegaETH are quite different from sharding: sharding horizontally divides the blockchain into multiple independent sub-chains (shards), with each sub-chain responsible for part of the transactions and state, breaking the limitations of a single chain for network layer scalability; whereas both Monad and MegaETH maintain the integrity of a single chain, only horizontally scaling at the execution layer, achieving performance breakthroughs through extreme parallel execution optimization within the single chain. The two represent two directions in the blockchain scaling path: vertical reinforcement and horizontal expansion.

Projects like Monad and MegaETH focus on throughput optimization paths, aiming to enhance on-chain TPS as the core objective. They achieve transaction-level or account-level parallel processing through Deferred Execution and Micro-VM architecture. Pharos Network, as a modular, full-stack parallel L1 blockchain network, has its 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:

1. Full Lifecycle Asynchronous Pipelining: Pharos decouples the various stages of a transaction (such as consensus, execution, storage) and uses asynchronous processing, allowing each stage to operate independently and in parallel, thus improving overall processing efficiency.
2. Dual VM Parallel Execution: Pharos supports two virtual machine environments, EVM and WASM, allowing developers to choose the appropriate execution environment based on their needs. This dual VM architecture not only enhances the flexibility of the system but also improves transaction processing capacity through parallel execution.
3. Special Processing Networks (SPNs): SPNs are key components in the Pharos architecture, similar to modular sub-networks specifically designed to handle certain types of tasks or applications. Through SPNs, Pharos can achieve dynamic resource allocation and parallel task processing, further enhancing the system's scalability and performance.
4. Modular Consensus & Restaking: Pharos introduces a flexible consensus mechanism that supports various consensus models (such as PBFT, PoS, PoA) and achieves secure sharing and resource integration between the mainnet and SPNs through the Restaking protocol.

In addition, Pharos has reconstructed the execution model from the underlying storage engine using technologies such as multi-version Merkle trees, Delta Encoding, Versioned Addressing, and ADS Pushdown, launching the native blockchain high-performance storage engine Pharos Store, achieving high throughput, low latency, and strong scalability.