These days, a new Ethereum Layer 2 scaling project, MegaETH, has suddenly gained popularity. The main reason for its sudden popularity is probably its impressive lineup of investors, including Vitalik and a number of well-known venture capitalists.

About a month ago, a friend mentioned this project to me. At that time, there wasn't much information available about the project, which made it difficult to fully understand some details. Upon revisiting the project after its surge in popularity, I found that there is now much more detailed information available.

Two aspects of this project have left a deep impression on me:

First, it is the first to propose specific performance indicators for Ethereum Layer 2 scaling.

Second, its whitepaper provides a detailed list of the ways and means to scale blockchain (including Ethereum Layer 2), and provides experimental data to support some important details (such as performance bottlenecks).

Regarding the performance of Ethereum Layer 2 scaling, in my impression, at least in the past few years, although it has been an important indicator emphasized by various projects, many times the improvement in performance by various projects has mainly focused on specific aspects or methods.

For example, the OP series emphasizes using "error proof" to improve the performance of Layer 2 scaling, while the ZK series focuses on improving the efficiency of proof generation to enhance Layer 2 scaling performance. On top of this, some degree of centralization (such as the use of sorters) is implemented to achieve high performance.

After these projects went live, when it was found that their performance improvement was quite limited (far from what everyone had expected), these projects shifted their focus to other aspects, such as strengthening ecosystem development and supporting ecosystem projects.

Of course, I fully agree with the approach of these project teams focusing on ecosystem development and supporting ecosystem projects, and I believe it is necessary.

However, the emergence of MegaETH suddenly made me feel that the pursuit of performance by these Layer 2 scaling projects has gradually faded.

From the perspective of Ethereum, it seems that the extension of performance has gradually become an increase in the number of Layer 2 scaling solutions: as the number of Layer 2 scaling solutions increases, the number of transactions processed by Ethereum per unit of time naturally increases as well—this can indeed be considered a certain degree of performance improvement.

But this kind of performance improvement always feels a bit forced, lacking in hardcore elements.

The emergence of MegaETH has once again focused on hardcore technology for performance improvement, a style that seems to have been absent from this ecosystem for quite some time.

The detailed description of each technical detail in MegaETH's whitepaper gives me the feeling that it is worth reading for everyone. It is rare to see such a detailed listing of technical details in a project's whitepaper. It feels more like a comprehensive review article on various factors of current blockchain performance scaling.

For ordinary readers, they can ignore its technical details and explore and speculate on the project's ideas and plans based on its logic.

In short, after reading this whitepaper, readers can probably understand from which perspectives and by what means the project team intends to achieve the claimed 100,000 TPS for this Layer 2 scaling solution.

Of course, whether this goal can be achieved will depend on the actual products in the future.

In my opinion, the overall approach taken by this project is the classification of nodes, subdividing various functions of Layer 2 scaling to different nodes, allowing various types of nodes to use hardware with different performance according to their needs, so that each function in the entire system can reach the limit of its node hardware, thereby pushing the system's performance to the limit of the hardware.

This approach reminds me of an earlier plan by Vitalik regarding the classification of nodes in the future of Ethereum.

In that plan, Vitalik envisioned that future Ethereum nodes would also be classified:

Some nodes that need to efficiently process transactions and generate blocks would use high-performance hardware and need to stake 32 ETH;

While other nodes that only serve as block validators would use very ordinary hardware (even embedded devices) and only need to stake a small amount of ETH.

This not only meets the performance requirements of the Ethereum mainnet, but also ensures that the entire network is as decentralized as possible.

I wonder if it was this approach of MegaETH that resonated with Vitalik and led him to participate in this project?

Of course, I also have some questions about this project: for example, does it always use a specified approach for handling sorters, or does it use a sampling method to select from many candidates? This detail does not seem to be specifically addressed in the whitepaper. If it is the former, how does the system avoid single point of failure?

In summary, MegaETH has added a high-performance flagship project to the Ethereum Layer 2 scaling ecosystem, making the ecosystem more diverse, which is definitely of great value to the ecosystem.

As for the investment value of the project (if it launches a token), this is how I see it:

Projects like MegaETH require a large amount of funding for research and development, so it is difficult for such projects to not accept the participation of venture capital. This means that the value of this project (if it launches a token) will definitely take into account the interests of venture capital.

Furthermore, such projects belong to the blue-chip category: their value is clear, and their significance is obvious.

Therefore, such projects generally have a ceiling on the potential for (their tokens) to appreciate.

So in my opinion, the significance of MegaETH to the Ethereum, especially the Layer 2 scaling ecosystem, is far greater than its investment value.

Reference link:

MegaETH Whitepaper: https://megaeth.systems/research

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