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What's the Deal with MegaETH?

The upcoming Vitalik-backed L2 wants to be the 'real-time Ethereum.' What's its plan?
Jack Inabinet Jack Inabinet Jul 3, 20244 min read
What's the Deal with MegaETH?

MegaETH, an upcoming L2 branded as the “real-time Ethereum” boasting sub-millisecond latency and capable of processing over 100k transactions per seco nd (TPS), just announced that it has received $20M in seed funding at a $100M+ valuation!

The star-studded raise was led by Dragonfly Capital and includes notable angle participation from Ethereum founder Vitalik Buterin, Consensys founder Joe Lubin, Lido/Flashbots strategy lead Hasu, prolific crypto trader Cobie, and EigenLayer founder Sreeram Kannan.

The big names involved have attracted some major attention to the upstart chain.

Today, we’re discussing how MegaETH is innovating on contemporary Ethereum Virtual Machine (EVM) blockchain implementations to provide industry-leading performance capabilities and decentralization guarantees.

⭐️ What Makes MegaETH Special

High performance alt L1s require their nodes to perform identical tasks without specialization, imposing a fundamental tradeoff between performance and decentralization. In comparison, MegaETH takes advantage of Ethereum’s L2s technology to create differentiated roles for nodes with varying hardware requirements.

MegaETH decouples the task of transaction processing from full nodes and creates three major roles for infrastructure operators: sequencers, provers, and full nodes. Although actual block production becomes increasingly centralized with MegaETH, flexible hardware requirements from node specialization ensures trustless block validation and could provide industry-leading decentralization guarantees.

A single active MegaETH sequencer will be responsible for ordering and executing user transactions, eliminating the consensus process during normal operations, and will pass state differences (i.e.; changes to the blockchain’s state) to full nodes via a peer-to-peer network, who then apply the state diffs to update their local state. Notably, MegaETH transactions are not re-executed by full nodes to verify block integrity; they instead validate blocks indirectly using proofs provided by the prover.

Source: MegaETH

Even the highest performance L2 in existence – BNB’s opBNB – imposes significant limitations on its applications. Despite a relatively high throughput target of 100M Gas per second, opBNB can only process 650 Uniswap swaps per second, compared to modern Web2 databases which can achieve an equivalent 1M TPS.

Further, these networks tend to have “long” block times above 1 second that are impractical for applications that require real-time performance, like high frequency trading.

Source: Paradigm

While blockchains have frequently turned to one-off solutions like parallelization in their pursuit of scale, enabling transactions touching different parts of state to be processed simultaneously on multiple CPU cores, the benefits of this specific approach are limited by the fact that many transactions contain dependencies, resulting in only modest boosts from parallelization for blockchain speed.

Addressing bottlenecks in isolation for any system often fails to yield significant improvement, as resolution of the initial limiting factor simply shifts the bottleneck to another component.

Instead of optimizing only a few components of its stack like competitors, MegaETH aims to identify the numerous problems plaguing existing blockchains and build a new system that fixes the litany of issues discovered simultaneously.

Such ambitions necessitate scaling node hardware to its limits while preserving decentralization (achieved through specialization) and require the creation of a system innately designed to approach the theoretical upper performance limit for a decentralized blockchain.

To this end, the MegaETH sequencer will store the entirety of its state in-memory and be the first blockchain to implement in-memory compute, a critical feature for high-performance Web2 applications that should enable MegaETH to accelerate state access by 1,000x compared to alternative solid state drive storage methods utilized by competitors.

Computation-intensive applications will receive a 100x boost to their performance on MegaETH thanks to a just-in-time (JIT) compiler that translates smart contract code into MegaETH’s “native machine code,” a set of instructions that a server’s CPU can directly interpret and execute, helping to increase smart contract speed and efficiency in execution.

Maintaining the Ethereum Merkle Patricia Trie (MPT), a core data structure that represents the current state of all assets and relevant information, is a major limiting factor for all EVM implementations, but MegaETH is creating a new state trie from scratch that will maintain full EVM compatibility while minimizing disk input/output operations and storing terabytes of state data.

Finally, MegaETH’s 100k transactions per second must be propagated to its network of full nodes; a highly efficient peer-to-peer protocol will pass state updates from the sequencer with low latency and high throughput, allowing full nodes with even a modest connection to remain synchronized at max update rates.

🧐 Closing Thoughts

The significant performance improvements targeted by MegaETH over contemporary EVM implementations should provide a major boost to L2 performance and could finally produce a decentralized blockchain capable of handling real-world adoption!

Although some contend that MegaETH is best suited as a competitor against an Ethereum ecosystem largely uninterested in scaling its base layer, the optimizations achieved by MegaETH are made possible solely through its ability to outsource security and censorship resistance to existing decentralized networks, like Ethereum and EigenLayer.


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Jack Inabinet

Written by Jack Inabinet

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Jack Inabinet is a Senior Analyst with a passion for exploring the bleeding edge of crypto and finance. Prior to joining Bankless, Jack worked as an analyst at HAL Real Estate where he conducted market research and financial analysis for commercial apartment development and acquisition activities in the Seattle region. He graduated from the University of Washington’s Michael G. Foster School of Business and remains based out of the Seattle area.

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