Author: Delphi Digital, Translator: Golden Finance xiaozou

Parallel execution is often hailed as the key to blockchain scaling and mass adoption, potentially attracting “billions of users.”

1. Why should we care about state growth management?

Because it impacts the developer experience, the fees paid by users, and the rewards accumulated by validators, state growth management is a key consideration for all L1s.

For parallelized VMs, it is important to note that only transactions that do not update the same state can run in parallel. In order to avoid conflicts, transactions must be ordered sequentially, which means that if 50% of the transactions have the same state, parallel execution will only benefit the remaining 50% of independent transactions.

2. Two main types of parallel execution

Let's look at the two main types of parallel execution:

(1) Deterministic type

The VM tracks transaction dependencies on storage and balances by mapping them through predefined access lists to prevent state conflicts, as shown in Solana and Sui.

(2) Optimistic type

This type of parallel execution runs all transactions in parallel or sequentially, assuming that the transactions will not conflict. This approach does not require access lists, which simplifies the development process and has been adopted by public chains such as Monad, MegaETH, Aptos, and Sei.

3. Sequential execution of Ethereum

Running Ethereum validators requires at least 8GB of RAM and a 2.8 GHz quad-core CPU. However, the EVM’s use of a single core to execute transactions suggests that it is not fully hardware optimized.

The EVM cannot execute transactions in parallel mainly due to the following two factors:

  • It lacks a mechanism to identify transactions with shared state dependencies.

  • It uses RockDB and Merkle Patricia Trees to store state data, and concurrent reading and writing are more complicated.

Parallel execution alone is not enough to sustain network usage. State growth and state access are the next scaling bottleneck.

The benefits of parallel execution may be exaggerated because only a select number of transactions per block can be executed in parallel. This becomes very noticeable during network congestion, as overlapping dependencies reduce the speedup gain. The figure below shows that block 20000006 was 6 times faster, while block 20434947 was only 1.7 times faster.

Looking at data from Ghost, an evaluation of 100,000 blocks between 20M blocks and 20.1M blocks in early June 2024 shows that blocks with minimal sequential dependencies execute faster when processed in parallel.

4. State growth and state access issues

The state of the blockchain includes accounts, account balances, nonces, and contract information. With the frequent transactions and the emergence of new contracts, especially in a complex system like ETH, the chain state continues to expand.

5. Economic Focus of State Management

Public chains such as Solana, Sui or Aptos use mechanisms such as state rent to provide economic incentives for optimal state growth management. They prevent validators and users from paying higher storage costs by charging users storage fees during transactions.

6. Technical focus of state management

Most technical approaches revolve around efficient database structures that support asynchronous read and write operations using a more optimal Merkle tree structure.

Delphi Digital researcher Muhammad Yusuf put it this way: Parallelization is a settled problem. Chains will compete to support more powerful setups and faster virtual machines. But to really achieve long-term results, strong state growth and admission management mechanisms are needed.”