Parallelization
Basics
"In many computing systems, operations are executed sequentially. This means that a second operation will only start after the first one is completed, and so on.
In blockchain transactions, this means processing each transaction in a block one after the other, known as sequential execution. Each transaction necessitates validation from the entire network, resulting in substantial energy consumption and a heightened workload for validators.
This sequential execution of transactions is one of the main bottlenecks to the Ethereum Virtual Machine (EVM) engine’s throughput. Sequential execution bloats the mempool resulting in high transaction costs, mooning gas fees, and a fractured user experience. It impedes the creation of scalable and cost-efficient dApps.
Parallel execution breaks from this sequential model enabling multiple operations to co-occur. It permits the simultaneous processing of multiple transactions allowing the network to achieve increased throughput — reducing the likelihood of congestion during periods of high demand. This enhances the network’s efficiency and scalability for blockchain dApps, significantly improving the user experience."
Blockchain Examples
The pioneer of parallelization was Solana, which got copycats like Aptos, Sei and Sui. This got followed up by EVM type protocols such as Solana based Neon and standalone L1 Monad.
