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

The "Blockchain Trilemma" reveals the essential trade-offs in the design of blockchain systems, namely that it is difficult for blockchain projects to simultaneously achieve "extreme security, universal participation, and high-speed processing." Regarding the eternal topic of "scalability," the mainstream blockchain scaling solutions currently on the market are categorized according to paradigms, including:

• Execute enhanced scalability: Improve execution capabilities on-site, 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 scalability: 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, Multithreaded Asynchronous Chains

Blockchain scalability 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 scalability system of "multi-layer collaboration and modular combination." This article focuses on introducing the mainstream scalability method based on parallel computing.

Intra-chain parallelism (, 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 higher.

• Account-level parallelism: Represents the Solana project
• Object-level parallelism: represents the project Sui
• 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 concurrency model, represented by the Actor 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 "intelligent agent process," utilizing asynchronous messaging in a parallel manner, event-driven, without the need for synchronous scheduling. Representative projects include AO, ICP, Cartesi, and others.

The well-known Rollup or sharding scaling solutions belong to system-level concurrency mechanisms and do not fall under on-chain parallel computation. They achieve scaling by "running multiple chains/execution domains in parallel" rather than enhancing the parallelism within a single block/virtual machine. Although such scaling solutions are not the focus of this article, we will still use them for comparative analysis of architectural concepts.

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) 2. EVM system parallel enhancement 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. Meanwhile, EVM and Solidity remain the most developer-friendly and ecosystem-strong 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, building EVM parallel processing architectures aimed at high concurrency and high throughput scenarios, respectively, from the perspectives of 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), achieving end-to-end optimization.

Pipelining: Multi-stage pipeline parallel execution mechanism

Pipelining is the basic concept of Monad parallel execution. 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 concurrent processing across blocks, 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 - Execute Asynchronously Decoupled

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." This significantly reduces block time and confirmation delay, making the system more resilient, processing more granular, and resource utilization higher.

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 the consensus is completed.
• Immediately enter the consensus process for the next block after the consensus is completed, without waiting for execution to finish.

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###" simultaneously to monitor whether transactions access the same state (e.g., read/write conflicts).
• If a conflict is detected, the 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 through deferred state writes and dynamic conflict detection during execution, resembling a performance version of Ethereum. Its maturity facilitates easy migration of the EVM ecosystem, serving as a parallel accelerator in the EVM world.

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)# Analysis of MegaETH's Parallel Computing Mechanism

Differentiating from the L1 positioning of Monad, MegaETH positions itself 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 on Ethereum, or as a modular component. 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 innovations proposed by MegaETH include: Micro-VM architecture + State Dependency DAG (Directed Acyclic Graph of State Dependencies) and a modular synchronization mechanism, which together construct a parallel execution system aimed at "in-chain threading."

Micro-VM architecture: Account as a thread

MegaETH introduces an execution model of "one micro virtual machine (Micro-VM) per account," which "threads" the execution environment, providing the smallest isolation unit for parallel scheduling. These VMs communicate through asynchronous messaging rather than synchronous calls, allowing a large number of VMs to execute and store independently, inherently parallel.

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 models which accounts are modified and which accounts are read as dependency relationships. Non-conflicting transactions can be executed in parallel, while transactions with dependencies will be scheduled serially or delayed 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, 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 holistic manner 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: completely abstracting accounts and contracts into independent VMs, and releasing extreme parallel potential through asynchronous execution scheduling. Theoretically, MegaETH's parallel limit is higher, but it is also more difficult to control complexity, resembling a super distributed operating system under the Ethereum philosophy.

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Monad and MegaETH have significantly different design philosophies compared to sharding: sharding horizontally divides the blockchain into multiple independent sub-chains (shards), with each sub-chain responsible for a portion of transactions and states, breaking the limitations of a single chain in network-layer scalability; while both Monad and MegaETH maintain the integrity of a single chain, horizontally scaling only at the execution layer, achieving performance breakthroughs through extreme parallel execution optimization within the single chain. The two represent vertical strengthening and horizontal expansion directions in the blockchain scaling path.

Projects like Monad and MegaETH focus primarily on optimizing throughput paths to enhance on-chain TPS as their core goal, achieving 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 a core parallel computing mechanism known as "Rollup Mesh." This architecture supports a multi-virtual machine environment (EVM and Wasm) through the collaborative work of the mainnet and special processing networks (SPNs), and integrates advanced technologies such as Zero-Knowledge Proofs (ZK) and Trusted Execution Environments (TEE).

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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 adopts an asynchronous processing approach, allowing each stage to proceed independently and in parallel, thereby 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 capability through parallel execution.
3. Special Purpose 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 SPN