Earos price

PANews reported on June 4 that, according to The Block, Binance announced the launch of its first spot liquidity plan for altcoins only, aiming to meet the market's demand for greater diversity. The new Altcoin Liquidity Enhancement Program is designed to offer the most attractive altcoin market making rebates in the industry to attract small and mid-sized liquidity providers who want to focus on altcoin market making to complement the exchange's existing liquidity programs. According to the details of the plan, market makers only need to focus on altcoin trading pairs to participate, and it is no longer mandatory to participate in market making of mainstream currencies such as Bitcoin. There are two rebate tiers: 0.005% rebate for market makers with a monthly trading volume of 0.5% of the market, and 0.01% for those with a 1% market share. The first supported trading pairs include INIT/USDT, EOS/USDT, HYPER/USDT, PARTI/USDT, ICP/USDT, KERNEL/USDT, CFX/USDT, W/USDT, KMNO/USDT, IOTX/USDT, ONDO/USDT, TON/USDT, FIL/USDT, WCT/USDT, BABY/USDT, SXT/USDT, SYRUP/USDT and STO/USDT. Catherine Chen, head of VIP and institutional business at Binance, said that existing liquidity programs tend to favor large market makers, and the new program will help small and medium-sized market makers gain a competitive advantage in the altcoin market. Applicants need to meet the threshold of trading volume of more than $20 million in the last 30 days and demonstrate a high-quality liquidity delivery strategy. The program's eligibility review will begin on June 9, and rebate distribution will begin on June 17.

Author: Huang Shiliang, Lightning HSL   EOS changed its name, and it turned out to be called A, the A of abcd, and the first place in the alphabet in the exchange is EOS. I've always had a crush on EOS because for the first three months of the 350-day ultra-long-term ICO fundraising process, I was involved in the primary market in EOS's ICO and the secondary market arbitrage in the exchange, making a small amount of money. That was the easiest money I've ever made. EOS started its ICO on June 26, 2017 and ended on June 1, 2018, raising more than $4 billion in ETH and issuing 900 million EOS tokens. The ICO mechanism of EOS was still quite new at the time. EOS was initially ICO through a smart contract deployed on Ethereum, with tokens issued in two phases: the first phase was a one-time distribution of 200 million EOS five days before the ICO started (June 26-30, 2017); After that, it enters the second stage, which is the daily round issuance mechanism. Every day (every 23 hours), the EOS smart contract accepts users' ETH stakes, and distributes 2 million EOS for the day according to the proportion of ETH of all participants at the end of the round. This daily issuance phase lasted for a total of 350 days, with a total of 700 million EOS issued. Together with the 200 million in the first five days, a total of 900 million EOS will be issued, and another 100 million EOS will be reserved for the project party Block.one, forming a total issuance of 1 billion. EOS's ICO sold 900 million EOS-erc20 tokens and received $4.2 billion, totaling 7.2 million ETH coins. At that time, not many people in the industry studied how to operate the Ethereum contract, how to deposit into the contract, and how to claim the purchased tokens. At that time, the tools were rudimentary, unlike today's contracts and wallets, and the UI interface was very good. In 2017, the main wallet of Ethereum was MyEtherWallet, I have a good impression of this wallet, the private key file used is still a json file, and the contract used to operate the EOS ICO needs to configure various parameters by itself, which is better than the command line (DoS) operation. The current metamask wallet, imtoken, etc., with various contracts, are very perfect to visualize the UI of various operation commands, and users only need to click the button to complete all contract interaction actions. At that time, MyEtherWallet invested in EOS ICO, and every time it had to import the private key json file, select the contract, select the contract parameters and commands, and fill in the amount of ETH you want to inject into the contract, including the amount of gas, which is user-defined. Then it's time to claim (claim eos-erc20), and it's time to fill in a few parameters. At that time, very few people did these operations. I was initially curious, and I was very curious about EOS because I had played around 2015 with various bitshares. So I took a hard look at EOS's ICO on ETH. EOS is also directly traded on exchanges during the 350-day ultra-long-term ICO. That is, during the EOS ICO, the primary market and the secondary market are opened at the same time. However, prices in the primary and secondary markets are not synchronized. This creates a potential arbitrage space. At that time, I deposited ETH into the ETH ICO contract every day, claimed eos-erc20 when the time came, and then directly deposited it to the exchange and sold it. It's such a simple arbitrage, there is no hedging at all, there is no J8 strategy, just simply bet that the price of the primary market is cheaper than the secondary market, and you can always make money. This kind of money lasted very long, and I barely lost money once in the first three months, but then I started losing money in the next few months, and then after half a year I stopped doing it. Why did I dare to judge that EOS would be cheaper in the primary market at first? This is because there are not many people who can buy coins in ICO contracts. In the beginning, when I looked at the interaction addresses on the chain, it was less than 100 per day, and in the first three months, most of the time, it was 148 addresses, which I can remember. Then the addresses began to increase, and then the profit was gone. In this first-level and second-level gambling spread arbitrage game, I also observed the behavior of hackers on the chain attacking the chain, in order to make money. Because there is a mechanism to end the period every 23 hours, in the last few minutes after the end of the period, it is often possible to calculate the price in the primary market, because how much ETH in the contract is transparent, and then compare the price in the secondary market to know if there is arbitrage space. Therefore, a large amount of ETH will be deposited in the last few minutes, which may cause the first-level price to be more expensive. Then, in the last few minutes, hackers construct a terrifying transaction that consumes ETH gas, blocking the entire ETH chain and making it impossible for others to charge ETH into the eos ico contract. After I went through a failed top-up, I learned to be obedient, and every time I grabbed a share of the first level at the last time, I directly filled up the gas, what a waste of money. After losing a few gas losses, I stopped the game and let them compete, and I did my best. That arbitrage war for half a year did make a small amount of money, but blessings and misfortunes depended on each other, and many things were found to have left disasters in the next few years. Because EOS's ICO has a 23-hour period, the time of the claim changes in a 1-hour gradient every day, so the time to grab the first level and claim tokens changes constantly every day, so 1/3 of the time of the period occurs when I should sleep. But in order to make money, how can I sleep or sleep, what is 12 o'clock at night, 3 o'clock in the morning, all get up and do it. This thing, it's really okay to stay up late once or twice, it can last for a week, and it's troublesome. And it's not a simple matter of staying up late, because there is a huge amount of money profit, and every time you do it, you are either very excited or angry...... Of course, it's not just the body that is getting worse, but I think there will be worse effects later. I was working on a project with a small team. But when my brothers see my virtue every day, the boss is not motivated, and it is even more impossible for others to work hard. Looking back, there was still a chance to do this project at that time, but I did it blindly J8 and hurt my brothers. Later in 2018, several brothers took the initiative to leave. Come to think of it, I'm actually quite fragile, and I don't have the courage to lead the team anymore. Just this year, Musk entered politics with a high profile, and I thought that his company, including Tesla, X.com, and SpaceX, may suffer, which is a loss for the whole world. If the boss doesn't drive in person, the company will probably not do well. There was another by-product of this experience. It was 2017, at the height of the BTC scaling controversy, and I was a hardcore scaler at the time, but I liked to write articles expressing my support for scaling. Maybe it's because EOS arbitrage made money, I became inflated at the time, and because I didn't sleep well every day, I wrote articles and expressed my opinions in the group, which may be too arrogant and offended a lot. Later, he was cyberbullied. The experience of being cyberbullied made me very unbrave on the Internet. Until now, I feel that I am quite cowardly on the Internet, and I dare not curse anymore. There were two experiences at that time, which I remember very well. One time was when the team from RSK (Bitcoin's sidechain project) was coming to China to give a talk about the roadshow, because I had written a lot of articles about sidechains in the early years, and their team asked me to speak with them. I was very unceremoniously criticized on the phone for not being firm in scaling. Hey, I'm so big, I'm so stupid. The night before the phone call, at 3 a.m., I was still working on the EOS ICO, and I was so excited that I didn't sleep, and I didn't have the strength to talk well when I answered the phone. Another time a reporter from a newspaper called me and asked me about scaling, and I said with a bang, "Do you dare to do what I say, because I said a lot of things that are not good for the supporters of the small block." Hey, actually, I'm only talking about technology, maybe it's better. It was too inflated at the time, but I've always been a very humble person. Time flies, 8 years have passed since the EOS ICO, and the money earned has been lost, leaving only some memories.

Written by: Huang Shiliang EOS changed its name, and it turned out to be called A, the A of abcd, and the first place in the alphabet in the exchange is EOS. I've always had a crush on EOS because for the first three months of the 350-day ultra-long-term ICO fundraising process, I was involved in the primary market in EOS's ICO and the secondary market arbitrage in the exchange, making a small amount of money. That was the easiest money I've ever made. EOS started its ICO on June 26, 2017 and ended on June 1, 2018, raising more than $4 billion in ETH and issuing 900 million EOS tokens. The ICO mechanism of EOS was still quite new at the time. EOS was initially ICO through a smart contract deployed on Ethereum, with tokens issued in two phases: the first phase was a one-time distribution of 200 million EOS five days before the ICO started (June 26-30, 2017); After that, it enters the second stage, which is the daily round issuance mechanism. Every day (every 23 hours), the EOS smart contract accepts users' ETH stakes, and distributes 2 million EOS for the day according to the proportion of ETH of all participants at the end of the round. This daily issuance phase lasted for a total of 350 days, with a total of 700 million EOS issued. Together with the 200 million in the first five days, a total of 900 million EOS will be issued, and another 100 million EOS will be reserved for the project party Block.one, forming a total issuance of 1 billion. EOS's ICO sold 900 million EOS-erc20 tokens and received $4.2 billion, totaling 7.2 million ETH coins. At that time, not many people in the industry studied how to operate the Ethereum contract, how to deposit into the contract, and how to claim the purchased tokens. At that time, the tools were rudimentary, unlike today's contracts and wallets, and the UI interface was very good. In 2017, the main wallet of Ethereum was MyEtherWallet, I have a good impression of this wallet, the private key file used is still a json file, and the contract used to operate the EOS ICO needs to configure various parameters by itself, which is better than the command line (DoS) operation. The current metamask wallet, imtoken, etc., with various contracts, are very perfect to visualize the UI of various operation commands, and users only need to click the button to complete all contract interaction actions. At that time, MyEtherWallet invested in EOS ICO, and every time it had to import the private key json file, select the contract, select the contract parameters and commands, and fill in the amount of ETH you want to inject into the contract, including the amount of gas, which is user-defined. Then it's time to claim (claim eos-erc20), and it's time to fill in a few parameters. At that time, very few people did these operations. I was initially curious, and I was very curious about EOS because I had played around 2015 with various bitshares. So I took a hard look at EOS's ICO on ETH. EOS is also directly traded on exchanges during the 350-day ultra-long-term ICO. That is, during the EOS ICO, the primary market and the secondary market are opened at the same time. However, prices in the primary and secondary markets are not synchronized. This creates a potential arbitrage space. At that time, I deposited ETH into the ETH ICO contract every day, claimed eos-erc20 when the time came, and then directly deposited it to the exchange and sold it. It's such a simple arbitrage, there is no hedging at all, there is no J8 strategy, just simply bet that the price of the primary market is cheaper than the secondary market, and you can always make money. This kind of money lasted very long, and I barely lost money once in the first three months, but then I started losing money in the next few months, and then after half a year I stopped doing it. Why did I dare to judge that EOS would be cheaper in the primary market at first? This is because there are not many people who can buy coins in ICO contracts. In the beginning, when I looked at the interaction addresses on the chain, it was less than 100 per day, and in the first three months, most of the time, it was 148 addresses, which I can remember. Then the addresses began to increase, and then the profit was gone. In this first-level and second-level gambling spread arbitrage game, I also observed the behavior of hackers on the chain attacking the chain, in order to make money. Because there is a mechanism to end the period every 23 hours, in the last few minutes after the end of the period, it is often possible to calculate the price in the primary market, because how much ETH in the contract is transparent, and then compare the price in the secondary market to know if there is arbitrage space. Therefore, a large amount of ETH will be deposited in the last few minutes, which may cause the first-level price to be more expensive. Then, in the last few minutes, hackers construct a terrifying transaction that consumes ETH gas, blocking the entire ETH chain and making it impossible for others to charge ETH into the eos ico contract. After I went through a failed top-up, I learned to be obedient, and every time I grabbed a share of the first level at the last time, I directly filled up the gas, what a waste of money. After losing a few gas losses, I stopped the game and let them compete, and I did my best. That arbitrage war for half a year did make a small amount of money, but blessings and misfortunes depended on each other, and many things were found to have left disasters in the next few years. Because EOS's ICO has a 23-hour period, the time of the claim changes in a 1-hour gradient every day, so the time to grab the first level and claim tokens changes constantly every day, so 1/3 of the time of the period occurs when I should sleep. But in order to make money, how can I sleep or sleep, what is 12 o'clock at night, 3 o'clock in the morning, all get up and do it. This thing, it's really okay to stay up late once or twice, it can last for a week, and it's troublesome. And it's not a simple matter of staying up late, because there is a huge amount of money profit, and every time you do it, you are either very excited or angry...... Of course, it's not just the body that is getting worse, but I think there will be worse effects later. I was working on a project with a small team. But when my brothers see my virtue every day, the boss is not motivated, and it is even more impossible for others to work hard. Looking back, there was still a chance to do this project at that time, but I did it blindly J8 and hurt my brothers. Later in 2018, several brothers took the initiative to leave. Come to think of it, I'm actually quite fragile, and I don't have the courage to lead the team anymore. Just this year, Musk entered politics with a high profile, and I thought that his company, including Tesla, X.com, and SpaceX, may suffer, which is a loss for the whole world. If the boss doesn't drive in person, the company will probably not do well. There was another by-product of this experience. It was 2017, at the height of the BTC scaling controversy, and I was a hardcore scaler at the time, but I liked to write articles expressing my support for scaling. Maybe it's because EOS arbitrage made money, I became inflated at the time, and because I didn't sleep well every day, I wrote articles and expressed my opinions in the group, which may be too arrogant and offended a lot. Later, he was cyberbullied. The experience of being cyberbullied made me very unbrave on the Internet. Until now, I feel that I am quite cowardly on the Internet, and I dare not curse anymore. There were two experiences at that time, which I remember very well. One time was when the team from RSK (Bitcoin's sidechain project) was coming to China to give a talk about the roadshow, because I had written a lot of articles about sidechains in the early years, and their team asked me to speak with them. I was very unceremoniously criticized on the phone for not being firm in scaling. Hey, I'm so big, I'm so stupid. The night before the phone call, at 3 a.m., I was still working on the EOS ICO, and I was so excited that I didn't sleep, and I didn't have the strength to talk well when I answered the phone. Another time a reporter from a newspaper called me and asked me about scaling, and I said with a bang, "Do you dare to do what I say, because I said a lot of things that are not good for the supporters of the small block." Hey, actually, I'm only talking about technology, maybe it's better. It was too inflated at the time, but I've always been a very humble person. Time flies, 8 years have passed since the EOS ICO, and the money earned has been lost, leaving only some memories.

1. Introduction: Expansion is an eternal proposition, and parallelism is the ultimate battlefield Since the birth of Bitcoin, the blockchain system has always faced an unavoidable core problem: scaling. Bitcoin processes less than 10 transactions per second, and Ethereum struggles to break through the performance bottleneck of tens of TPS (transactions per second), which is particularly cumbersome in the traditional Web2 world, which is often tens of thousands of TPS. More importantly, this is not a simple problem that can be solved by "adding servers", but a systemic limitation deeply embedded in the underlying consensus and structural design of the blockchain - that is, the impossible triangle of the blockchain where "decentralization, security, and scalability" cannot be combined. Over the past decade, we've seen countless expansion attempts rise and fall. From the Bitcoin scaling war to the Ethereum sharding vision, from state channels and plasma to rollups and modular blockchains, from off-chain execution in Layer 2 to structural refactoring of Data Availability, the entire industry has embarked on a path of scaling full of engineering imagination. As the most widely accepted scaling paradigm, rollup has achieved the goal of significantly increasing TPS while reducing the execution burden of the main chain and preserving the security of Ethereum. But it doesn't touch the real limits of the blockchain's underlying "single-chain performance", especially at the execution level, which is the throughput of the block itself – is still limited by the ancient processing paradigm of on-chain serial computation. Because of this, in-chain parallel computing has gradually entered the industry's field of vision. Different from off-chain scaling and cross-chain distribution, intra-chain parallelism attempts to completely reconstruct the execution engine while maintaining the single-chain atomicity and integrated structure, and upgrades the blockchain from a single-threaded mode of "serial execution of one transaction by one" to a high-concurrency computing system of "multi-threading + pipeline + dependency scheduling" under the guidance of modern operating system and CPU design. Such a path may not only achieve a hundredfold increase in throughput, but also may become a key prerequisite for the explosion of smart contract applications. In fact, in the Web2 computing paradigm, single-threaded computing has long been eliminated by modern hardware architectures, and replaced by an endless stream of optimization models such as parallel programming, asynchronous scheduling, thread pools, and microservices. Blockchain, as a more primitive and conservative computing system with extremely high requirements for certainty and verifiability, has never been able to make full use of these parallel computing ideas. This is both a limitation and an opportunity. New chains such as Solana, Sui, and Aptos are the first to start this exploration by introducing parallelism at the architectural level. Emerging projects such as Monad and MegaETH have further elevated on-chain parallelism to breakthroughs in deep mechanisms such as pipeline execution, optimistic concurrency, and asynchronous message-driven, showing characteristics that are getting closer and closer to modern operating systems. It can be said that parallel computing is not only a "performance optimization method", but also a turning point in the paradigm of blockchain execution model. It challenges the fundamental patterns of smart contract execution and redefines the basic logic of transaction packaging, state access, call relationships, and storage layout. If rollup is "moving transactions to off-chain execution", then on-chain parallelism is "building supercomputing cores on-chain", and its goal is not to simply improve throughput, but to provide truly sustainable infrastructure support for future Web3 native applications (high-frequency trading, game engines, AI model execution, on-chain social, etc.). After the rollup track gradually tends to be homogeneous, intra-chain parallelism is quietly becoming the decisive variable of the new cycle of Layer 1 competition. Performance is no longer just "faster", but the possibility of being able to support an entire heterogeneous application world. This is not only a technical race, but also a paradigm battle. The next generation of sovereign execution platforms in the Web3 world is likely to emerge from this intra-chain parallel wrestling. 2. Panorama of expansion paradigm: five types of routes, each with its own emphasis Capacity expansion, as one of the most important, sustained and difficult topics in the evolution of public chain technology, has given birth to the emergence and evolution of almost all mainstream technology paths in the past decade. Starting from the battle over the block size of Bitcoin, this technical competition on "how to make the chain run faster" finally divided into five basic routes, each of which cuts into the bottleneck from a different angle, with its own technical philosophy, landing difficulty, risk model and applicable scenarios. The first route is the most straightforward on-chain scaling, which means increasing the block size, shortening the block time, or improving the processing power by optimizing the data structure and consensus mechanism. This approach has been the focus of the Bitcoin scaling debate, giving rise to "big block" forks such as BCH and BSV, and also influencing the design ideas of early high-performance public chains such as EOS and NEO. The advantage of this kind of route is that it retains the simplicity of single-chain consistency, which is easy to understand and deploy, but it is also very easy to touch the systemic upper limit such as centralization risk, rising node operating costs, and increased synchronization difficulty, so it is no longer the mainstream core solution in today's design, but has become more of an auxiliary collocation of other mechanisms. The second type of route is off-chain scaling, which is represented by state channels and sidechains. The basic idea of this type of path is to move most of the transaction activity off-chain, and only write the final result to the main chain, which acts as the final settlement layer. In terms of technical philosophy, it is close to the asynchronous architecture of Web2 - try to leave heavy transaction processing at the periphery, and the main chain does minimal trusted verification. Although this idea can theoretically be infinitely scalable, the trust model, fund security, and interaction complexity of off-chain transactions limit its application. For example, although Lightning Network has a clear positioning of financial scenarios, the scale of the ecosystem has never exploded. However, multiple sidechain-based designs, such as Polygon POS, not only have high throughput, but also expose the disadvantages of difficult inheritance of the security of the main chain. The third type of route is the most popular and widely deployed Layer 2 rollup route. This method does not directly change the main chain itself, but scales through the mechanism of off-chain execution and on-chain verification. Optimistic Rollup and ZK Rollup have their own advantages: the former is fast to implement and highly compatible, but it has the problems of challenge period delay and fraud proof mechanism; The latter has strong security and good data compression capabilities, but it is complex to develop and lacks EVM compatibility. No matter what type of rollup it is, its essence is to outsource execution power, while keeping data and verification on the main chain, achieving a relative balance between decentralization and high performance. The rapid growth of projects such as Arbitrum, Optimism, zkSync, and StarkNet proves the feasibility of this path, but it also exposes medium-term bottlenecks such as excessive reliance on data availability (DA), high costs, and fragmented development experience. The fourth type of route is the modular blockchain architecture that has emerged in recent years, such as Celestia, Avail, EigenLayer, etc. The modular paradigm advocates the complete decoupling of the core functions of the blockchain - execution, consensus, data availability, and settlement - by multiple specialized chains to complete different functions, and then combine them into a scalable network with a cross-chain protocol. This direction is strongly influenced by the modular architecture of the operating system and the concept of cloud computing composability, which has the advantage of being able to flexibly replace system components and greatly improve efficiency in specific areas such as DA. However, the challenges are also very obvious: the cost of synchronization, verification, and mutual trust between systems after module decoupling is extremely high, the developer ecosystem is extremely fragmented, and the requirements for medium- and long-term protocol standards and cross-chain security are much higher than those of traditional chain design. In essence, this model no longer builds a "chain", but builds a "chain network", which puts forward an unprecedented threshold for the overall architecture understanding and operation and maintenance. The last type of route, which is the focus of the subsequent analysis in this paper, is the intra-chain parallel computing optimization path. Unlike the first four types of "horizontal splitting", which mainly carry out "horizontal splitting" from the structural level, parallel computing emphasizes "vertical upgrading", that is, the concurrent processing of atomic transactions is realized by changing the architecture of the execution engine within a single chain. This requires rewriting the VM scheduling logic and introducing a complete set of modern computer system scheduling mechanisms, such as transaction dependency analysis, state conflict prediction, parallelism control, and asynchronous calling. Solana is the first project to implement the concept of parallel VM into a chain-level system, which realizes multi-core parallel execution through transaction conflict judgment based on the account model. The new generation of projects, such as Monad, Sei, Fuel, MegaETH, etc., further try to introduce cutting-edge ideas such as pipeline execution, optimistic concurrency, storage partitioning, and parallel decoupling to build high-performance execution cores similar to modern CPUs. The core advantage of this direction is that it does not need to rely on the multi-chain architecture to achieve a breakthrough in the throughput limit, and at the same time provides sufficient computing flexibility for the execution of complex smart contracts, which is an important technical prerequisite for future application scenarios such as AI Agent, large-scale chain games, and high-frequency derivatives. Looking at the above five types of scaling paths, the division behind them is actually the systematic trade-off between performance, composability, security, and development complexity of blockchain. Rollup is strong in consensus outsourcing and secure inheritance, modularity highlights structural flexibility and component reuse, off-chain scaling attempts to break through the bottleneck of the main chain but the trust cost is high, and intra-chain parallelism focuses on the fundamental upgrade of the execution layer, trying to approach the performance limit of modern distributed systems without destroying the consistency of the chain. It is impossible for each path to solve all problems, but it is these directions that together form a panorama of the Web3 computing paradigm upgrade, and also provide developers, architects, and investors with extremely rich strategic options. Just as the operating system has shifted from single-core to multi-core and databases have evolved from sequential indexes to concurrent transactions, the expansion of Web3 will eventually move towards a highly parallel execution era. In this era, performance is no longer just a chain speed race, but a comprehensive embodiment of the underlying design philosophy, depth of architecture understanding, software and hardware collaboration, and system control. And intra-chain parallelism may be the ultimate battlefield of this long-term war. 3. Parallel Computing Classification Graph: Five Paths from Account to Instruction In the context of the continuous evolution of blockchain scaling technology, parallel computing has gradually become the core path for performance breakthroughs. Different from the horizontal decoupling of the structure layer, network layer or data availability layer, parallel computing is a deep mining at the execution layer, which is related to the lowest logic of the operation efficiency of the blockchain, and determines the response speed and processing capacity of a blockchain system in the face of high concurrency and multi-type complex transactions. Starting from the execution model and reviewing the development of this technology lineage, we can sort out a clear classification map of parallel computing, which can be roughly divided into five technical paths: account-level parallelism, object-level parallelism, transaction-level parallelism, virtual machine-level parallelism, and instruction-level parallelism. These five types of paths, from coarse-grained to fine-grained, are not only the continuous refinement process of parallel logic, but also the path of increasing system complexity and scheduling difficulty. The earliest account-level parallelism is the paradigm represented by Solana. This model is based on the decoupling design of account and state, and determines whether there is a conflicting relationship by statically analyzing the set of accounts involved in the transaction. If two transactions access a set of accounts that do not overlap with each other, they can be executed concurrently on multiple cores. This mechanism is ideal for dealing with well-structured transactions with clear inputs and outputs, especially for programs with predictable paths such as DeFi. However, its natural assumption is that account access is predictable and state dependence can be statically inferred, which makes it prone to conservative execution and reduced parallelism in the face of complex smart contracts (such as dynamic behaviors such as chain games and AI agents). In addition, the cross-dependency between accounts also makes parallel returns severely weakened in certain high-frequency trading scenarios. Solana's runtime is highly optimized in this regard, but its core scheduling strategy is still limited by account granularity. Further refinement on the basis of the account model, we enter the technical level of object-level parallelism. Object-level parallelism introduces semantic abstraction of resources and modules, with concurrent scheduling in more fine-grained units of "state objects". Aptos and Sui are important explorators in this direction, especially the latter, which defines the ownership and variability of resources at compile time through the Move language's linear type system, allowing the runtime to precisely control resource access conflicts. Compared with account-level parallelism, this method is more versatile and scalable, can cover more complex state read and write logic, and naturally serves highly heterogeneous scenarios such as games, social networking, and AI. However, object-level parallelism also introduces higher language barriers and development complexity, and Move is not a direct replacement for Solidity, and the high cost of ecological switching limits the popularity of its parallel paradigm. Further transaction-level parallelism is the direction explored by the new generation of high-performance chains represented by Monad, Sei, and Fuel. Instead of treating states or accounts as the smallest unit of parallelism, the path is built around a dependency graph around the entire transaction itself. It treats transactions as atomic units of operation, builds transaction graphs (Transaction DAGs) through static or dynamic analysis, and relies on schedulers for concurrent flow execution. This design allows the system to maximize mining parallelism without having to fully understand the underlying state structure. Monad is particularly eye-catching, combining modern database engine technologies such as Optimistic Concurrency Control (OCC), parallel pipeline scheduling, and out-of-order execution, bringing chain execution closer to the "GPU scheduler" paradigm. In practice, this mechanism requires extremely complex dependency managers and conflict detectors, and the scheduler itself may also become a bottleneck, but its potential throughput capacity is much higher than that of the account or object model, making it the most theoretical force in the current parallel computing track. Virtual machine-level parallelism, on the other hand, embeds concurrent execution capabilities directly into the underlying instruction scheduling logic of the VM, striving to completely break through the inherent limitations of EVM sequence execution. As a "super virtual machine experiment" within the Ethereum ecosystem, MegaETH is trying to redesign the EVM to support multi-threaded concurrent execution of smart contract code. The underlying layer allows each contract to run independently in different execution contexts through mechanisms such as segmented execution, state segmentation, and asynchronous invocation, and ensures eventual consistency with the help of a parallel synchronization layer. The most difficult part of this approach is that it must be fully compatible with the existing EVM behavior semantics, and at the same time transform the entire execution environment and gas mechanism to smoothly migrate the Solidity ecosystem to a parallel framework. The challenge is not only the depth of the technology stack, but also the acceptance of significant protocol changes to Ethereum's L1 political structure. But if successful, MegaETH promises to be a "multi-core processor revolution" in the EVM space. The last type of path is instruction-level parallelism, which is the most fine-grained and has the highest technical threshold. The idea is derived from the out-of-order execution and instruction pipelines of modern CPU design. This paradigm argues that since every smart contract is eventually compiled into bytecode instructions, it is entirely possible to schedule and analyze each operation and rearrange it in parallel in the same way that a CPU executes an x86 instruction set. The Fuel team has initially introduced an instruction-level reorderable execution model in its FuelVM, and in the long run, once the blockchain execution engine implements predictive execution and dynamic rearrangement of instruction dependents, its parallelism will reach the theoretical limit. This approach may even take blockchain-hardware co-design to a whole new level, making the chain a true "decentralized computer" rather than just a "distributed ledger". Of course, this path is still in the theoretical and experimental stage, and the relevant schedulers and security verification mechanisms are not yet mature, but it points to the ultimate boundary of the future of parallel computing. In summary, the five paths of account, object, transaction, VM, and instruction constitute the development spectrum of intra-chain parallel computing, from static data structure to dynamic scheduling mechanism, from state access prediction to instruction-level rearrangement, each step of parallel technology means a significant increase in system complexity and development threshold. But at the same time, they also mark a paradigm shift in the computing model of blockchain, from the traditional full-sequence consensus ledger to a high-performance, predictable, and dispatchable distributed execution environment. This is not only a catch-up with the efficiency of Web2 cloud computing, but also a deep conception of the ultimate form of "blockchain computer". The selection of parallel paths for different public chains will also determine the bearer limit of their future application ecosystems, as well as their core competitiveness in scenarios such as AI Agent, chain games, and on-chain high-frequency trading. Fourth, the two main tracks are explained: Monad vs MegaETH Among the multiple paths of parallel computing evolution, the two main technical routes with the most focus, the highest voice, and the most complete narrative in the current market are undoubtedly the "building parallel computing chain from scratch" represented by Monad and the "parallel revolution within EVM" represented by MegaETH. These two are not only the most intensive R&D directions for current cryptographic primitive engineers, but also the most decisive polar symbols in the current Web3 computer performance race. The difference between the two lies not only in the starting point and style of the technical architecture, but also in the ecological objects they serve, the migration cost, the execution philosophy and the future strategic path behind them. They represent a parallel paradigm competition between "reconstructionism" and "compatibilityism", and have profoundly influenced the market's imagination of the final form of high-performance chains. Monad is a "computational fundamentalist" through and through, and its design philosophy is not designed to be compatible with existing EVMs, but rather to redefine the way blockchain execution engines run under the hood, drawing inspiration from modern databases and high-performance multi-core systems. Its core technology system relies on mature mechanisms in the database field such as Optimistic Concurrency Control, Transaction DAG Scheduling, Out-of-Order Execution, and Pipelined Execution, aiming to increase the transaction processing performance of the chain to the order of millions of TPS. In the Monad architecture, the execution and ordering of transactions are completely decoupled, and the system first builds a transaction dependency graph, and then hands it over to the scheduler for parallel execution. All transactions are treated as atomic units of transactions, with explicit read-write sets and snapshots of state, and schedulers execute optimistically based on dependency graphs, rolling back and re-executing when conflicts occur. This mechanism is extremely complex in terms of technical implementation, requiring the construction of an execution stack similar to that of a modern database transaction manager, as well as the introduction of mechanisms such as multi-level caching, prefetching, parallel validation, etc., to compress the latency of final state commit, but it can theoretically push the throughput limit to heights that are not imagined by the current chain. More importantly, Monad has not given up on interoperability with the EVM. It uses an intermediate layer similar to "Solidity-Compatible Intermediate Language" to support developers to write contracts in Solidity syntax, and at the same time perform intermediate language optimization and parallelization scheduling in the execution engine. This design strategy of "surface compatibility and bottom refactoring" not only retains the friendliness of Ethereum ecological developers, but also liberates the underlying execution potential to the greatest extent, which is a typical technical strategy of "swallowing the EVM and then deconstructing it". This also means that once Monad is launched, it will not only become a sovereign chain with extreme performance, but also an ideal execution layer for Layer 2 rollup networks, and even a "pluggable high-performance core" for other chain execution modules in the long run. From this point of view, Monad is not only a technical route, but also a new logic of system sovereignty design, which advocates the "modularization-performance-reusability" of the execution layer, so as to create a new standard for inter-chain collaborative computing. Unlike Monad's "new world builder" stance, MegaETH is a completely opposite type of project, which chooses to start from the existing world of Ethereum and achieve a significant increase in execution efficiency with minimal change costs. MegaETH does not overturn the EVM specification, but rather seeks to build the power of parallel computing into the execution engine of the existing EVM, creating a future version of the "multi-core EVM". The rationale lies in a complete refactoring of the current EVM instruction execution model with capabilities such as thread-level isolation, contract-level asynchronous execution, and state access conflict detection, allowing multiple smart contracts to run simultaneously in the same block, and eventually merge state changes. This model requires developers to achieve significant performance gains from the same contract deployed on the MegaETH chain without changing existing Solidity contracts, using new languages or toolchains. This "conservative revolution" path is extremely attractive, especially for the Ethereum L2 ecosystem, as it provides an ideal pathway to painless performance upgrades without the need to migrate syntax. The core breakthrough of MegaETH lies in its VM multi-threaded scheduling mechanism. Traditional EVMs use a stacked, single-threaded execution model, where each instruction is executed linearly and state updates must occur synchronously. MegaETH breaks this pattern and introduces an asynchronous call stack and execution context isolation mechanism, so as to achieve simultaneous execution of "concurrent EVM contexts". Each contract can invoke its own logic in a separate thread, and all threads will uniformly detect and converge the state through the Parallel Commit Layer when the state is finally submitted. This mechanism is very similar to the JavaScript multithreading model of modern browsers (Web Workers + Shared Memory + Lock-Free Data), which retains the determinism of the behavior of the main thread and introduces a high-performance scheduling mechanism that is asynchronous in the background. In practice, this design is also extremely friendly to block builders and searchers, and can optimize Mempool sorting and MEV capture paths according to parallel strategies, forming a closed loop of economic advantages at the execution layer. More importantly, MegaETH chooses to be deeply bound to the Ethereum ecosystem, and its main landing place in the future is likely to be an EVM L2 Rollup network, such as Optimism, Base, or Arbitrum Orbit chain. Once adopted on a large scale, it can achieve nearly 100 times performance improvement on top of the existing Ethereum technology stack without changing contract semantics, state model, gas logic, invocation methods, etc., which makes it an attractive technology upgrade direction for EVM conservatives. The MegaETH paradigm is: as long as you're still doing things on Ethereum, then I'll let your computing performance skyrocket. From the perspective of realism and engineering, it is easier to implement than Monad, and it is more in line with the iterative path of mainstream DeFi and NFT projects, making it a candidate for ecological support in the short term. In a sense, the two routes of Monad and MegaETH are not only two implementations of parallel technology paths, but also a classic confrontation between "refactoring" and "compatibility" in the blockchain development route: the former pursues a paradigm breakthrough and reconstructs all the logic from virtual machines to underlying state management to achieve ultimate performance and architectural plasticity; The latter pursues incremental optimization, pushing traditional systems to the limit while respecting existing ecological constraints, thereby minimizing migration costs. There are no absolute advantages or disadvantages between the two, but they serve different developer groups and ecosystem visions. Monad is more suitable for building new systems from scratch, chain games that pursue extreme throughput, AI agents, and modular execution chains. MegaETH, on the other hand, is more suitable for L2 projects, DeFi projects, and infrastructure protocols that want to achieve performance upgrades with minimal development changes. They are like high-speed trains on a new track, redefined from the track, the power grid to the car body, just to achieve unprecedented speed and experience; Another example is installing turbines on existing highways, improving lane scheduling and engine structure, allowing vehicles to go faster without leaving the familiar road network. The two may end up in the same way: in the next phase of modular blockchain architectures, Monad could become an "execution-as-a-service" module for Rollups, and MegaETH could become a performance acceleration plugin for mainstream L2s. The two may eventually converge to form the two wings of the high-performance distributed execution engine in the future Web3 world. 5. Future opportunities and challenges of parallel computing As parallel computing moves from paper-based design to on-chain implementation, the potential it unlocks is becoming more concrete and measurable. On the one hand, we have seen that new development paradigms and business models have begun to redefine "on-chain performance": more complex chain game logic, more realistic AI agent life cycle, more real-time data exchange protocol, more immersive interactive experience, and even on-chain collaborative Super App operating system are all changing from "can we do it" to "how well we can do it". On the other hand, what really drives the transition to parallel computing is not only the linear improvement of system performance, but also the structural change of developers' cognitive boundaries and ecological migration costs. Just as the introduction of the Turing-complete contract mechanism by Ethereum gave birth to the multi-dimensional explosion of DeFi, NFT and DAO, the "asynchronous reconstruction between state and instruction" brought about by parallel computing is also giving birth to a new on-chain world model, which is not only a revolution in execution efficiency, but also a hotbed of fission innovation in product structure. First of all, from the perspective of opportunities, the most direct benefit is the "lifting of the application ceiling". Most of the current DeFi, gaming, and social applications are limited by state bottlenecks, gas costs, and latency, and cannot truly carry high-frequency interactions on the chain on a large scale. Taking chain games as an example, GameFi with real motion feedback, high-frequency behavior synchronization, and real-time combat logic almost does not exist, because the linear execution of traditional EVM cannot support the broadcast confirmation of dozens of state changes per second. With the support of parallel computing, through mechanisms such as transaction DAGs and contract-level asynchronous contexts, high-concurrency chains can be constructed, and deterministic execution results can be guaranteed through snapshot consistency, so as to achieve a structural breakthrough in the "on-chain game engine". Similarly, the deployment and operation of AI agents will also be substantially improved by parallel computing. In the past, we tended to run AI Agents off-chain and only upload their behavior results to on-chain contracts, but in the future, on-chain can support asynchronous collaboration and state sharing between multiple AI entities through parallel transaction scheduling, so as to truly realize the real-time autonomous logic of Agent on-chain. Parallel computing will be the infrastructure for this "behavior-driven contract", driving Web3 from a "transaction as an asset" to a new world of "interaction as an agent". Second, the developer toolchain and the virtual machine abstraction layer have also been structurally reshaped due to parallelization. The traditional Solidity development paradigm is based on a serial thinking model, where developers are accustomed to designing logic as a single-threaded state change, but in parallel computing architectures, developers will be forced to think about read/write set conflicts, state isolation policies, transaction atomicity, and even introduce architectural patterns based on message queues or state pipelines. This leap in cognitive structure has also given birth to the rapid rise of a new generation of tool chains. For example, parallel smart contract frameworks that support transactional dependency declarations, IR-based optimization compilers, and concurrent debuggers that support transaction snapshot simulation will all become hotbeds for infrastructure explosions in the new cycle. At the same time, the continuous evolution of modular blockchains has also brought an excellent landing path for parallel computing: Monad can be inserted into L2 Rollup as an execution module, MegaETH can be deployed as an EVM replacement for mainstream chains, Celestia provides data availability layer support, and EigenLayer provides a decentralized validator network, thus forming a high-performance integrated architecture from the underlying data to the execution logic. However, the advancement of parallel computing is not an easy road, and the challenges are even more structural and difficult to gnaw than the opportunities. On the one hand, the core technical difficulties lie in the "consistency guarantee of state concurrency" and the "transaction conflict handling strategy". Unlike off-chain databases, on-chain cannot tolerate arbitrary degree of transaction rollback or state retraction, and any execution conflicts need to be modeled in advance or precisely controlled during the event. This means that the parallel scheduler must have strong dependency graph construction and conflict prediction capabilities, and at the same time design an efficient optimistic execution fault tolerance mechanism, otherwise the system is prone to "concurrent failure retry storm" under high load, which not only increases but decreases, and even causes chain instability. Moreover, the current security model of the multi-threaded execution environment has not yet been fully established, such as the precision of the state isolation mechanism between threads, the new utilization of re-entrancy attacks in asynchronous contexts, and the gas explosion of cross-threaded contract calls, all of which are new problems that need to be solved. More insidious challenges arise from ecological and psychological aspects. Whether developers are willing to migrate to the new paradigm, whether they can master the design methods of parallel models, and whether they are willing to give up some readability and contract auditability for performance benefits are the key to whether parallel computing can form ecological potential energy. In the past few years, we have seen a number of chains with superior performance but lack developer support gradually fall silent, such as NEAR, Avalanche, and even some Cosmos SDK chains with far better performance than EVM, and their experience reminds us that without developers, there is no ecosystem; Without ecology, no matter how good the performance is, it is just a castle in the air. Therefore, parallel computing projects should not only make the strongest engine, but also make the most gentle ecological transition path, so that "performance is the out-of-the-box" rather than "performance is the cognitive threshold". Ultimately, the future of parallel computing is both a triumph for systems engineering and a test for eco-design. It will force us to re-examine "what is the essence of the chain": is it a decentralized settlement machine, or a globally distributed real-time state orchestrator? If the latter is the case, then the capabilities of state throughput, transaction concurrency, and contract responsiveness, which were previously regarded as "technical details of the chain", will eventually become the primary indicators that define the value of the chain. The parallel computing paradigm that truly completes this transition will also become the most core and most compounding infrastructure primitives in this new cycle, and its impact will go far beyond a technical module, and may constitute a turning point in the overall computing paradigm of Web3. 6. Conclusion: Is parallel computing the best path for Web3 native scaling? Of all the paths that explore the boundaries of Web3 performance, parallel computing is not the easiest to implement, but it may be the closest to the essence of blockchain. It does not migrate off-chain, nor does it sacrifice decentralization in exchange for throughput, but tries to reconstruct the execution model itself in the atomicity and determinism of the chain, from the transaction layer, contract layer, and virtual machine layer to the root of the performance bottleneck. This "native to the chain" scaling method not only retains the core trust model of the blockchain, but also reserves sustainable performance soil for more complex on-chain applications in the future. Its difficulty lies in the structure, and its charm lies in the structure. If modular refactoring is the "architecture of the chain", then parallel computing refactoring is the "soul of the chain". This may not be a shortcut to the customs clearance, but it is likely to be the only sustainable positive solution in the long-term evolution of Web3. We're witnessing an architectural transition from single-core CPUs to multi-core/threaded OSs, and the appearance of Web3-native operating systems may be hidden in these in-chain parallel experiments.

💡Information Upbit will suspend #EOS and related token trading and deposit/withdrawal services in June 2025 to support #token swap and rebranding. #EOS will be renamed to Volta (code changed to A), focusing on #Web3 financial services, including wealth management and payments.