Financing 225 million USD, can Monad become a leading L1 project?

Layer 1 blockchain Monad Labs has announced the completion of a $225 million financing round, led by Paradigm, with participation from Electric Capital, SevenX Ventures, IOSG Ventures, and Greenoaks. The project aims to challenge competitors like Solana and Sui. This transaction is reportedly the largest cryptocurrency financing deal so far in 2024.

In response, Monad founder Keone Hon stated that Monad's innovation comes from rebuilding Ethereum's blockchain from scratch, maintaining the ability to execute smart contracts while completing transactions at a faster speed, higher capacity, and lower cost. Monad will fully support EVM.
Shortly after, HTX Ventures announced a strategic investment in Monad Labs, and the collaboration will drive innovation in the Web3 ecosystem.
The following text will provide readers with a comprehensive introduction to the Monad project.

Addressing EVM's Performance Pain Points, Monad Achieves 10,000+ TPS with Outstanding Scalability

EVM has long been the pioneer of blockchain virtual machines and has become the most widely used virtual machine over the years, witnessing renowned innovations like Curve, Uniswap, and Maker. Despite EVM's dominance, performance deficiencies have led to the rise of AltVM (alternative virtual machines). Among AltVMs, Monad's advantages include its mainnet's 10,000 TPS and a strong community consensus culture.

It is reported that Monad will officially launch later this year, aiming to become a highly scalable single large L1 blockchain. It is both EVM-compatible and capable of processing over 10,000 transactions per second, with a block time of 1 second. This scalable performance is attributed to technologies such as parallel execution and Monad DB.
Monad achieves security and decentralization and raised $19 million in seed funding, led by Dragonfly, with participation from Placeholder, Shima Capital, Lemniscap, Cobie, and others.

Understanding Monad's Parallelization Technology Logic and Insights into the Future Evolution of the EVM L1 Track

Monad is building a parallel EVM L1 with complete bytecode compatibility. Monad's uniqueness lies not only in its parallel engine but also in the optimization engine built at the underlying level. Monad employs a unique holistic design approach that combines several key features, such as pipelining, asynchronous I/O, consensus execution separation, and MonadDB.
A key innovation in Monad's design is pipelining with a slight offset. The offset allows for the parallelization of more processes by running multiple instances simultaneously. Therefore, pipelining is used to optimize many functions, such as state access pipelining, transaction execution pipelining, internal pipelining of consensus and execution, and pipelining within the consensus mechanism itself.

Next, we will take a closer look at Monad's parallelization aspect, which is the technical core of the project.
In Monad, transactions are linearly ordered within a block, but the goal is to reach the final state faster by utilizing parallel execution. Monad's execution engine design employs an optimistic parallel algorithm. The Monad engine processes transactions simultaneously and then performs analysis to ensure that if the transactions were executed one after another, the same results would be achieved.
If there are any conflicts, re-execution is required. The parallel execution here is a relatively simple algorithm, but combining it with Monad's other key innovations makes this approach novel. It is worth noting that even if re-execution occurs, it is usually inexpensive because the inputs required for invalid transactions are almost always retained in the cache, making it a simple cache lookup. Re-execution is ensured to succeed because you have already executed previous transactions in the block.
Monad also improves performance by separating execution and consensus (similar to Solana and Sei) and through delayed execution. The idea is that if you relax execution conditions to complete execution before reaching consensus, you can run execution and consensus in parallel, thus adding extra time for both. Of course, Monad uses a deterministic algorithm to handle this situation to ensure that one does not run too far ahead and go out of control.

Developed Over Two Years and Set to Launch Later This Year, the Story of the Monad Team is Also Worth Reading

Monad has been in development for about two years, founded by Keone Hon, James Hunsaker, and Eunice Giarta. Keone and James are two technical co-founders who worked together at Jump Trading for eight years.
Sitting at the same high-frequency trading desk and competing with 20 other teams within Jump, Keone and James were able to consistently rank at the top for several years, facilitating over $100 trillion in nominal trading volume and executing thousands of trades per second. At this level of trading volume, Keone and James experienced firsthand the difference microseconds make in execution.
After entering the crypto space, Keone worked on Solana DeFi, while James was building Pyth. Realizing the potential for a series of fundamental optimizations to be applied to EVM, they began building Monad in 2022. These optimizations have become standards in high-performance computer science over the past 20 years but have not yet been applied to EVM. By introducing these components, a higher-performing EVM can be created to address many current scalability bottlenecks.