The Future of Scaling: A Panorama of Web3 Parallel Computing Tracks

Written by: 0xjacobzhao and ChatGPT The

"Blockchain Trilemma" of the 4o blockchain "security", "decentralization", and "scalability" reveal the essential trade-off in the design of blockchain systems, that is, it is difficult for blockchain projects to achieve "extreme security, everyone can participate, and high-speed processing" at the same time. In response to the eternal topic of "scalability", the mainstream blockchain scaling solutions in the market are divided according to paradigms, including:

• Execution-enhanced scaling: Improving execution capabilities in situ, such as parallelism, GPU, and multi-core

• State-isolated scaling: Horizontally split state/shard, such as sharding, UTXO, and multi-subnet

• Off-chain outsourced scaling: Putting execution off-chain, For example, Rollup, Coprocessor, DA

• structure decoupling scaling: modular architecture, collaborative operation, such as module chain, shared sequencer, Rollup Mesh

• asynchronous concurrent scaling: Actor model, process isolation, message-driven, such as agent, multi-threaded asynchronous chain

  The

  blockchain scaling solution includes: on-chain parallel computing, rollup, sharding, DA module, modular structure, actor system, zk proof compression, stateless architecture, etc., covering multiple levels of execution, state, data, and structure, and is a complete scaling system of "multi-layer collaboration and module combination". This article focuses on scaling methods that mainstream parallel computing.

  Intra-chain parallelism, which focuses on the parallel execution of intra-block transactions/instructions. According to the parallel mechanism, its scaling methods can be divided into five categories, each of which represents a different performance pursuit, development model and architecture philosophy, and the parallel granularity is getting finer and finer, the parallelism intensity is getting higher and higher, the scheduling complexity is getting higher and higher, and the programming complexity and implementation difficulty are also getting higher and higher.

  • Account-level: Represents the project Solana

  • Object-level: represents the project Sui

  • Transaction-level: represents the project Monad, Aptos

  • Call-level / MicroVM: Represents the project MegaETH

  • Instruction-level parallelism: Represents the project GatlingX

  The off-chain asynchronous concurrency model, represented by the Actor / Actor Model, belongs to another parallel computing paradigm, as a cross-chain/asynchronous message system (non-block synchronization model), each agent runs independently as an "agent process", asynchronous messages in parallel mode, event-driven, no synchronous scheduling, representative projects such as AO, ICP, Cartesi, etc.

  The well-known rollup or shard scaling scheme belongs to the system-level concurrency mechanism, not the intra-chain parallel computing. They achieve scaling by "running multiple chains/execution domains in parallel", rather than increasing parallelism within a single block/virtual machine. This type of scaling solution is not the focus of this article, but we will still use it to compare the similarities and differences in architectural concepts.