Web3 Parallel Computing Depth Research Report: The Ultimate Path to Native Scalability

I. Introduction: Scalability is an eternal proposition, and parallelism is the ultimate battleground.

Since its inception, the blockchain system has faced the core issue of scalability. The performance bottlenecks of Bitcoin and Ethereum are difficult to overcome, contrasting sharply with traditional Web2 systems. This is not a problem that can be solved simply by adding more servers, but rather stems from systemic limitations in the underlying design of blockchain.

In the past decade, the industry has experienced various scaling attempts, from the Bitcoin scaling debate to Ethereum sharding, from state channels to Rollups. As the current mainstream scaling solution, Rollups have improved TPS, but have still not reached the true limits of "single-chain performance" at the blockchain's underlying level.

In-chain parallel computing is gradually coming into view. It attempts to completely reconstruct the execution engine while maintaining the atomicity of a single chain, upgrading the blockchain from a "single-threaded mode" to a "high-concurrency computing system." This could not only achieve hundreds of times the throughput improvement but also become the key to the explosion of smart contract applications.

In fact, Web2 has long widely adopted optimization models such as parallel programming and asynchronous scheduling. However, blockchain, as a more conservative computing system, has never fully utilized these ideas. New chains like Solana have taken the lead in introducing parallelism, while projects like Monad and MegaETH further explore mechanisms such as pipeline execution and optimistic concurrency.

It can be said that parallel computing is not only a performance optimization but also a paradigm shift in the blockchain execution model. It redefines the basic logic of transaction packaging, state access, and more. If Rollup is "moving execution off-chain", then on-chain parallelism is "building a supercomputing kernel", providing sustainable infrastructure for future Web3 applications.

After the Rollup track converges, on-chain parallelism is becoming a decisive variable in the competition for Layer 1 in the new cycle. This is not just a technological competition, but also a struggle for paradigms. The next generation of sovereign execution platforms in the Web3 world is likely to emerge from this contest.

II. Overview of Expansion Paradigms: Five Types of Routes, Each with Its Focus

As a core topic in the evolution of public chain technology, scalability has given rise to almost all mainstream technological paths over the past decade. This competition to "make the chain run faster" has ultimately differentiated into five basic routes, each with its own focus:

1. On-chain scaling: directly increasing block size, shortening block time, etc. Easy to implement but prone to centralization risks, currently mostly used as an auxiliary solution.

2. Off-chain scaling: such as state channels and sidechains. It can significantly improve throughput, but faces issues like trust models and fund security.

3. Layer2 Rollup: The most popular scaling solution currently. It achieves scaling through off-chain execution and on-chain verification.

4. Modular Blockchain: Decouples the core functions of the blockchain, allowing multiple specialized chains to perform different functions. Flexible but increases the synchronization costs between systems.

5. In-chain parallelism: Achieve concurrent processing of in-chain transactions by changing the execution engine architecture. The VM scheduling logic needs to be rewritten, introducing modern computer scheduling mechanisms.

These five types of paths reflect the trade-offs in performance, composability, security, and complexity in blockchain. Each solution has its pros and cons, collectively forming a panoramic view of the upgrade of the Web3 computing paradigm.

3. Classification Map of Parallel Computing: Five Major Paths from Account to Instruction

Parallel computing, as a depth optimization of the execution layer, can be divided into five technical paths:

1. Account-level parallelism: represented by Solana, based on account-state decoupling, to determine whether there are conflicts between transactions.

2. Object-level parallelism: Like Aptos and Sui, introduces a finer-grained "state object" concept for scheduling.

3. Transaction-level parallelism: Such as Monad, Sei, build a dependency graph around the entire transaction and perform concurrent pipelined execution.

4. Virtual Machine Level Parallelism: For example, MegaETH, embedding concurrency capabilities into the VM's underlying instruction scheduling logic.

5. Instruction-level parallelism: Drawing on the modern CPU out-of-order execution concept, scheduling analysis and parallel reordering are performed for each operation.

These five types of paths range from coarse-grained to fine-grained, reflecting the refinement of parallel logic and the increase in system complexity. They mark the transition of blockchain computing models from traditional consensus ledgers to high-performance distributed execution environments.

4. In-depth Analysis of Two Major Power Tracks: Monad vs MegaETH

The two main technical routes currently focused on by the market are Monad and MegaETH.

Monad adopts a "reconstructionist" approach, drawing inspiration from modern database systems to completely redefine the blockchain execution engine. Its core technologies include optimistic concurrency control, transaction DAG scheduling, etc., with the goal of achieving millions of TPS. Monad retains compatibility with Solidity, achieving "surface compatibility and underlying reconstruction" through an intermediate language layer.

MegaETH takes the "compatibilism" approach, attempting to implant parallel capabilities on the existing EVM foundation. It does not change the Solidity syntax but rather restructures the EVM instruction execution model, introducing thread-level isolation, asynchronous execution, and other mechanisms. This approach is more friendly to the Ethereum ecosystem and is expected to land first in L2 Rollup.

The two represent two approaches to parallel technology: Monad seeks paradigm breakthroughs, while MegaETH pursues incremental optimization. They are suitable for different developer groups and ecological visions, and may complement each other in the future modular blockchain architecture.

5. Future Opportunities and Challenges of Parallel Computing

Parallel computing brings new possibilities to Web3:

1. Application ceiling lifted: High-frequency interactive blockchain games and real-time AI Agents become possible.

2. Paradigm Shift in Development: Parallel thinking will change smart contract design patterns and give rise to new toolchains.

3. Modular Collaboration: Parallel computing can form a high-performance architecture with other modular components ( such as Celestia and EigenLayer ).

However, parallel computing also faces many challenges:

1. Technical challenges: Guarantees of state consistency, conflict handling strategies, etc. still need breakthroughs.

2. Security Risks: New attack surfaces in a multithreaded environment need to be addressed.

3. Ecological Migration: Whether developers are willing to adapt to new paradigms is key.

4. Cognitive Threshold: How to lower the usage threshold of parallel computing is key to its popularization.

6. Conclusion: Is parallel computing the best path for Web3 native scalability?

Parallel computing, although difficult to implement, may be the scalability path that is closest to the essence of blockchain. It fundamentally reconstructs the execution model while retaining the core trust model of the blockchain. This "native to the chain" scalability approach reserves sustainable performance space for future complex applications.

We are witnessing an architectural leap similar to the transition from single-core to multi-core OS. The reconstruction of parallel computing is not just about the "architecture of the chain", but also about the "soul of the chain". Although this is not a shortcut that yields results in the short term, it is likely the only sustainable right answer in the long-term evolution of Web3. The prototype of a Web3 native operating system may be hidden within these parallel experiments in the chains.