Monad and Parallel EVM

Intro

Introduction to Parallel EVM

An Example

Differences Between Sharding and Parallel EVM

Intro

The parallel EVM project Monad, which has received substantial funding, is generating a lot of buzz. Today, let's briefly discuss parallel EVM.

Introduction to Parallel EVM

Parallel EVM (Ethereum Virtual Machine) is a method to enhance the speed and efficiency of the Ethereum network by executing multiple transactions simultaneously. The traditional EVM is the core of Ethereum, responsible for running smart contracts and processing transactions. In a traditional EVM, transactions are executed in sequence. This means that at any given time, only one transaction can be processed.

This creates bottlenecks, especially under high network load. Parallel EVM addresses this issue by changing this serial processing mode. It allows multiple transactions to be executed in parallel. This can significantly increase transaction throughput and reduce transaction delays and gas costs. Parallel EVM can be implemented in several ways:

Sharding: Dividing the Ethereum network into multiple sections, each processing its own transactions independently.

Optimization algorithms: Improving the underlying code of the EVM to handle parallel transactions more efficiently.

Hybrid solutions: Combining the benefits of sharding and optimization algorithms.

Parallel EVM is still in the development stage, but it is considered one of the crucial directions for Ethereum's future development. Many projects are working on developing their own parallel EVM solutions, such as:

Neon: Introducing EVM to the Solana ecosystem via L2 Neon EVM.

Optimism: Implementing L2 parallel EVM using Optimistic Rollups.

Arbitrum: Implementing L2 parallel EVM using Optimistic Rollups.

zkSync: Implementing L2 parallel EVM using zk-Rollups.

Parallel EVM is expected to solve the scalability issues Ethereum currently faces and pave the way for broader applications.

Here are some benefits of parallel EVM:

Increased transaction throughput: Parallel EVM can significantly enhance the Ethereum network's transaction handling capacity.

Reduced transaction delay: Parallel EVM can shorten transaction confirmation times.

Lower gas costs: Parallel EVM can reduce transaction costs.

Enhanced scalability: Parallel EVM can support more users and applications.

Parallel EVM also presents some challenges, such as:

Technical complexity: The development and implementation of parallel EVM are technically challenging.

Security: Parallel EVM needs to ensure network security while processing transactions in parallel.

Consistency: Parallel EVM must ensure that all parallel processed transactions eventually reach consensus.

Despite these challenges, parallel EVM is still seen as a significant opportunity for Ethereum's future development. With continuous technological advancements, parallel EVM is expected to overcome these challenges and bring more robust performance and broader application prospects to Ethereum.

An Example

In simple terms, parallel EVM is like adding more "highways" to the Ethereum network, allowing more "vehicles" (transactions) to pass through simultaneously, thus improving network throughput and efficiency.

For example:

Suppose you need to prepare food for a party. The traditional way is for one person to handle all steps, from buying ingredients to cooking, which can take a long time.

Parallel EVM is like inviting your friends to help out. Each person handles different steps, such as one shopping for ingredients, another preparing utensils, one cutting vegetables, and another cooking. As everyone completes their tasks simultaneously, overall efficiency greatly improves, and the food can be prepared quickly.

In the Ethereum network, transactions are like the "food" that needs to be processed. The traditional EVM processes transactions one by one by a "chef" (miner), which can lead to network congestion and transaction delays.

Parallel EVM allows multiple "chefs" to process transactions simultaneously, just like your friends helping out. This can significantly increase network throughput, shorten transaction confirmation times, reduce gas costs, and support more users and applications.

Of course, the technical implementation of parallel EVM is much more complex and faces some challenges, requiring further research and refinement. However, overall, parallel EVM is one of the important directions for Ethereum's future development and holds great promise.

Differences Between Sharding and Parallel EVM

Both parallel EVM and sharding are solutions proposed by Ethereum to enhance scalability, but there are some key differences between them.

Parallel EVM focuses on improving the transaction processing capacity within a single shard. It can be achieved by optimizing the underlying EVM code or using parallel processing technologies. For example, Neon implements parallel EVM by introducing EVM to the Solana ecosystem through L2 Neon EVM.

Sharding focuses on dividing the Ethereum network into multiple sections, each independently processing its own transactions. This can effectively distribute the network load across multiple nodes, thereby increasing overall throughput. For instance, Optimism and Arbitrum both use Optimistic Rollups to implement L2 sharding.

In summary, parallel EVM is like enhancing the capacity of a single "highway," while sharding is like adding more "highways."

The following table summarizes the main differences between parallel EVM and sharding:

Feature | Parallel EVM | Sharding
Focus | Transaction processing capacity within a single shard | Overall network transaction processing capacity
Implementation | Optimizing EVM underlying code or using parallel processing technologies | Dividing the network into multiple sections
Advantages | Increased transaction throughput, reduced gas costs | Increased transaction throughput, reduced gas costs, supports more users and applications
Challenges | Technical complexity, security, consistency | Technical complexity, security, consistency, cross-shard transactions

Overall, parallel EVM and sharding are complementary technologies that can be combined to achieve optimal scalability. In the future, Ethereum may adopt both techniques to address its scalability issues.