Difference between revisions of "Monad"
m |
m |
||
Line 1: | Line 1: | ||
[[Ethereum (ETH)|Ethereum]]-compatible [[Layer One|L1]] with [[ | [[Ethereum (ETH)|Ethereum]]-compatible [[Layer One|L1]] with [[parallelization]] | ||
==Basics== | ==Basics== | ||
Line 42: | Line 42: | ||
===How it works=== | ===How it works=== | ||
* [https://www.onchaintimes.com/p/the-monad-deep-dive-the-most-anticipated From] influencer/researcher Thor (8-2-2024): | * From this [https://x.com/FourPillarsFP/status/1835634545045246055 report] (16-9-2024): | ||
''"Consensus - Monad BFT'' | |||
''Monad BFT is heavily influenced by [[HotStuff]] BFT, but it has devised a method of direct communication with other [[Node|nodes]] when experiencing poor network conditions. Unlike HotStuff, which went through three processes per round, Monad BFT focuses on reducing [[latency]] by going through only two processes per round. Additionally, when conducting votes, instead of cross-validation communication where vote data is propagated to all nodes except oneself, Monad BFT adopts a linear communication method where data is propagated only to the leader of the next round, improving blockchain throughput and latency. Lastly, through pipelining, Monad BFT has achieved consensus efficiency by introducing a method where all consensus processes are not handled in a single round, but are divided and processed over multiple rounds.'' | |||
''Execution - Transaction Parallel Execution'' | |||
''Monad uses optimistic concurrency in parallel processing of transactions. In simple terms, during parallel processing, it assumes all operations are valid, executes them first, and then re-executes if problems occur during the verification process. The reason Monad uses this approach is that they judged it to be more efficient to execute transactions and then re-execute based on information gathered when problems occur, rather than analyzing the relationships between transactions in advance.'' | |||
''Storage (Database) - Monad DB'' | |||
''In fact, parallel processing at the execution level is not such a difficult task. It has already been implemented many times, and various blockchains are doing parallel processing at the execution layer. The real important thing is "efficiency of parallel processing," and the answer to this lies in the storage method. Therefore, Monad is investing a great deal of time and effort into optimizing the DB. Monad DB does not use the Merkle Patricia structure that Ethereum has, but instead natively implements the Patricia tree structure on both disk and memory to reduce inefficiencies. Moreover, by supporting async I/O, it allows the [[CPU]] to process other transactions concurrently without waiting for the results of transaction inputs and outputs."'' | |||
*[https://www.onchaintimes.com/p/the-monad-deep-dive-the-most-anticipated From] influencer/researcher Thor (8-2-2024): | |||
''"Monad utilizes [[Parallelization|parallel]] execution which allows several transactions to be processed at the same time. It’s important to note that Monad [[Block|blocks]] still are a linearly ordered set of [[Transaction (Tx)|transactions]] just like on [[Ethereum (ETH)|Ethereum]].'' | ''"Monad utilizes [[Parallelization|parallel]] execution which allows several transactions to be processed at the same time. It’s important to note that Monad [[Block|blocks]] still are a linearly ordered set of [[Transaction (Tx)|transactions]] just like on [[Ethereum (ETH)|Ethereum]].'' |
Latest revision as of 15:11, 25 September 2024
Ethereum-compatible L1 with parallelization
Basics
- Based in:
- Started in / Announced on: 2022
- Testnet release:
- Mainnet release: "mainnet launch later this year" (14-2-2023)
History
- From influencer/researcher Thor (8-2-2024):
"Monad has been in development for roughly two years and is founded by Keone Hon, James Hunsaker and Eunice Giarta. Keone and James are the two technical co-founders and worked together for eight years at Jump Trading. Sitting at the same high frequency trading desk and competing against 20 other teams internally at Jump, Keone and James were able to consistently rank as one of the top performing desks over the years, facilitating more than $10 trillion dollars in notional trading volume per year. With this level of volume, and by conducting thousands of transactions per second, Keone and James experienced firsthand the difference a microsecond makes in execution.
After moving into crypto, Keone was working on Solana DeFi and James was building Pyth. They started building Monad in 2022 after realizing that it’s possible to implement a series of fundamental optimizations to the EVM, which have been standard in high performance computer science over the last 20 years, but have not yet been implemented to the EVM."
Audits & Exploits
- Bug bounty program can be found [insert here].
Bugs/Exploits
Governance
Admin Keys
DAO
Notable Governance Votes
Treasury
Token
Launch
Token Allocation
Inflation
Utility
Burns
Other Details
Coin Distribution
Technology
- Whitepaper or docs can be found [insert here].
- Code can be viewed [insert here].
- Consensus mechanism: MonadBFT
- Algorithm:
- Virtual Machine: EVM
- Development language used: The Monad client is built with a focus on performance and is written from scratch in C++ and Rust.
Transaction Details
How it works
- From this report (16-9-2024):
"Consensus - Monad BFT
Monad BFT is heavily influenced by HotStuff BFT, but it has devised a method of direct communication with other nodes when experiencing poor network conditions. Unlike HotStuff, which went through three processes per round, Monad BFT focuses on reducing latency by going through only two processes per round. Additionally, when conducting votes, instead of cross-validation communication where vote data is propagated to all nodes except oneself, Monad BFT adopts a linear communication method where data is propagated only to the leader of the next round, improving blockchain throughput and latency. Lastly, through pipelining, Monad BFT has achieved consensus efficiency by introducing a method where all consensus processes are not handled in a single round, but are divided and processed over multiple rounds.
Execution - Transaction Parallel Execution
Monad uses optimistic concurrency in parallel processing of transactions. In simple terms, during parallel processing, it assumes all operations are valid, executes them first, and then re-executes if problems occur during the verification process. The reason Monad uses this approach is that they judged it to be more efficient to execute transactions and then re-execute based on information gathered when problems occur, rather than analyzing the relationships between transactions in advance.
Storage (Database) - Monad DB
In fact, parallel processing at the execution level is not such a difficult task. It has already been implemented many times, and various blockchains are doing parallel processing at the execution layer. The real important thing is "efficiency of parallel processing," and the answer to this lies in the storage method. Therefore, Monad is investing a great deal of time and effort into optimizing the DB. Monad DB does not use the Merkle Patricia structure that Ethereum has, but instead natively implements the Patricia tree structure on both disk and memory to reduce inefficiencies. Moreover, by supporting async I/O, it allows the CPU to process other transactions concurrently without waiting for the results of transaction inputs and outputs."
- From influencer/researcher Thor (8-2-2024):
"Monad utilizes parallel execution which allows several transactions to be processed at the same time. It’s important to note that Monad blocks still are a linearly ordered set of transactions just like on Ethereum.
Monad uses optimistic execution which means that the chain will start executing transactions before earlier transactions in the block have completed. To avoid errors and incorrect execution, the state of transactions are merged sequentially in the blocks to ensure correctness."
Fees
Upgrades
Staking
Validator Stats
Liquidity Mining
Scaling
Interoperability
Monad announced a day one partnership with Layerzero.
Other Details
Oracle Method
Their Other Projects
Roadmap
- Can be found [Insert link here].
Revenue
Usage
Projects that use or built on it
Competition
Pros and Cons
Pros
Cons
- One co-founder, James Hunsaker, a former Jump employee is a SEC whistleblower (11-4-2024) who was part of Jump during the Terra era.
Team, Funding and Partners
Team
- Full team can be found [here].
- Monad Labs, both founders come from Jump Trading (15-2-2024).
- Keone Hon; co-founder & CEO
- Eunice Giarta and James Hunsaker
Funding
- Announced a $225M fundraise (9-4-2024) with participation of Paradigm, Electric Capital, Coinbase Ventures, Greenoaks, Egirl Capital, Rune Christensen, Robinson Burkey, Mert Mumtaz, Bryan Pellegrino, Eric Wall, Luca Netz, Saquon Barkley, Ansem, Hsaka, Inversebrah and others.
- From Techcrunch (14-2-2023);
"Raised $19 million in seed funding led by Dragonfly Capital. The round included 70 participants, including Placeholder Capital, Lemniscap, Shima Capital and Finality Capital, as well as angel investors like AngelList co-founder Naval Ravikant. The capital will be used to double the team to about 24 in the next several months, Giarta said."
Partners
(:
Knowledge empowers all and will help us get closer to the decentralized world we all want to live in!
Making these free wiki pages is fun but takes a lot of effort and time.
If you have enjoyed reading, tips are appreciated :) This will help us to keep expanding this archive of information.