
Monad APAC
852 posts

Monad APAC
@Monad_APAC
All you need to know about @monad for Asia Pacific



This week in the Monad ecosystem - Gas-sponsored transactions are live on @metamask, users can swap and interact with Monad on MetaMask seamlessly without needing gas - @blinqfi is now live on Monad. Real-time prediction markets with sub-second execution - MON is now supported on @Tangem cold wallets for secure storage - @packflipNFT is now live on Monad. Users can open digital packs (Pokémon & One Piece cards), trade them instantly, or redeem for physical cards - The World Baseball Classic is now live on @Levr_Bet, users can place leveraged bets on baseball games - Scroll Trading is live on Monad with @memetok_app, users can trade and make content for their favorite memecoins


क्या आप इस साल ETH Mumbai आ रहे हैं? अगर हाँ, तो Monad India Community Meetup - Mumbai Edition में हमारे साथ जुड़ें। नीचे रजिस्टर करें।👇


Can we get 100 people to say “Monad”?

This isn't true!! This is the beauty of RaptorCast. To recap, RaptorCast follows a two-level broadcast tree (with assignments of chunks to the first level weighted by stake) with erasure coding (with 2.5x redundancy factor). Let there be V validators, and let B be the size of the block in bytes. In RaptorCast's two-hop broadcast tree: - in the first hop, the leader sends roughly 2.5*B bytes of data, spread across all other validators, i.e. each validator on average gets 2.5*B/V - in the second hop, each validator sends the chunks that it receives to every other validator. So the total amount of data it needs to send out (on average) is 2.5*B/V * V = 2.5*B. For example, with 10k nodes with (for simplicity) equal stake weight, each validator is the first-hop validator for 2.5/10000 = 1/4000 of a block worth of chunks. Then in the second hop, each validator sends 1/4000 of a block worth of chunks to 10k other validators, i.e. it sends 2.5 blocks worth of data. The more immediate bottleneck for 10k validators is cryptography (certain operations in MonadBFT (our consensus) have costs that scale with number of votes) but there's active work being done there. But the point of this post is to say that, on the p2p layer, this problem is largely addressed by RaptorCast. We can have performance with decentralization. Longer blog post here: category.xyz/blogs/raptorca…








