Artela White Paper Interpretation: Unique Parallel Execution Stack + Elastic Block Space

Author: ChainFeeds

In March of this year, the scalable L1 blockchain network Artela launched EVM++, an upgrade to the next-generation EVM execution layer technology. The first "+" in EVM++ stands for "Extensibility," which refers to the scalability achieved through Aspect technology, enabling developers to create on-chain custom programs in a WebAssembly (WASM) environment that can collaborate with the EVM, providing high-performance, customized application-specific extensions for dApps. The second "+" represents "Scalability," which significantly enhances the network's processing capacity and efficiency through parallel execution technology and the design of elastic block space.

WebAssembly (WASM) is an efficient binary code format that enables performance close to native execution speed in web browsers, making it particularly suitable for handling compute-intensive tasks such as AI and big data processing.

On June 21, Artela releaseda white paper detailing how it enhances blockchain scalability by developing a parallel execution stack and introducing elastic block space based on elastic computing.

The Importance of Parallel Processing

In traditional Ethereum Virtual Machine (EVM), all smart contract operations and state transitions must remain consistent across the entire network. This requires all nodes to execute the same transactions in the same order. Therefore, even if certain transactions do not actually depend on each other, they must be executed sequentially in the order they appear in the block, which is serial processing. This approach not only causes unnecessary waiting but is also inefficient.

Parallel processing allows multiple processors or computing cores to simultaneously execute multiple computational tasks or process data, significantly improving processing efficiency and reducing runtime, especially for complex or large-scale computational problems that can be broken down into multiple independent tasks. Parallel EVM is an extension or improvement of the traditional Ethereum Virtual Machine, capable of executing multiple smart contracts or contract function calls simultaneously, significantly increasing the throughput and efficiency of the entire network. Additionally, it can optimize the efficiency of single-threaded execution. The most direct advantage of parallel EVM is that it enables existing decentralized applications to achieve internet-level performance.

Artela Network and EVM++

Artela is an L1 that enhances the scalability and performance of EVM by introducing EVM++. EVM++ is an upgrade to the EVM execution layer technology, integrating the flexibility of EVM with the high-performance characteristics of WASM. This enhanced virtual machine supports parallel processing and efficient storage, allowing more complex and performance-demanding applications to run on Artela. EVM++ not only supports traditional smart contracts but also allows for the dynamic addition and execution of high-performance modules on-chain, such as AI agents, which can operate as on-chain co-processors or directly participate in on-chain games, creating truly programmable NPCs.

Artela ensures that the computational capacity of network nodes can flexibly scale according to demand through its parallel execution design. Additionally, validator nodes support horizontal scaling, allowing the network to automatically adjust the scale of computing nodes based on current load or demand. This scaling process is coordinated by an elastic protocol to ensure sufficient computational resources in the consensus network. By ensuring the scalability of computational power through elastic computing, Artela ultimately achieves elastic block space, allowing large dApps to request independent block space based on specific needs, which not only meets the need for expanding public block space but also ensures the performance and stability of large applications.

Detailed Explanation of Artela's Parallel Execution Architecture

1. Predictive Optimistic Execution

Predictive optimistic execution is one of Artela's core technologies and is a distinguishing feature compared to other parallel EVMs like Sei and Monad. Optimistic execution refers to a parallel execution strategy that assumes there are no conflicts between transactions at the initial state. In this mechanism, each transaction maintains a private version of the state, recording modifications but not finalizing them immediately. After the transaction execution is complete, a validation phase checks for conflicts caused by global state changes from other concurrent transactions. If a conflict is detected, the transaction is re-executed. Predictive refers to analyzing historical transaction data through specific AI models to predict the dependencies between upcoming transactions, i.e., which transactions may access the same data, and grouping them accordingly to arrange their execution order, thereby reducing execution conflicts and duplicate executions. In contrast, Sei relies on developer-defined transaction dependency files, while Monad uses compiler-level static analysis to generate transaction dependency files, neither of which possesses EVM equivalence or the adaptive capability of Artela's AI-based dynamic prediction model.

2. Async Preloading Technology

Async preloading technology aims to address input/output (I/O) bottlenecks caused by state access, with the goal of increasing data access speed and reducing waiting time during transaction execution. Before transaction execution, Artela preloads the required state data from slow storage (like hard drives) into fast storage (like memory) based on the predictive model. By preloading necessary data, it reduces I/O waiting time during execution. When data is preloaded and cached, multiple processors or execution threads can access this data simultaneously, further enhancing execution parallelism.

3. Parallel Storage

With the introduction of parallel execution technology, while transaction processing can be parallelized, if the read and write speeds of data cannot be improved synchronously, it will become a key factor limiting overall system performance, thus shifting the system's bottleneck to the storage layer. Solutions like MonadDB and SeiDB have begun to focus on optimizing the storage layer. Artela has developed parallel storage by borrowing and integrating various mature traditional data processing technologies, further enhancing the efficiency of parallel processing.

The parallel storage system is primarily designed to address two major issues: first, to achieve parallel processing of storage, and second, to improve the efficient recording of data states to the database. Common issues during data storage include data expansion during writing and increased pressure on database processing. To effectively address these issues, Artela adopts a separation strategy between State Commitment (SC) and State Storage (SS). This strategy divides storage tasks into two parts: one part is responsible for fast processing operations without retaining complex data structures to save space and reduce data duplication; the other part is responsible for recording all detailed data information. Additionally, to avoid performance impacts when processing large amounts of data, Artela employs a method of merging small data blocks into larger ones, reducing the complexity of data preservation.

4. Elastic Block Space (EBS)

Artela's Elastic Block Space (EBS) is designed based on the concept of elastic computing, capable of automatically adjusting the number of transactions a block can accommodate based on network congestion levels.

Elastic computing is a cloud computing service model that allows systems to automatically adjust the configuration of computing resources to accommodate changing load demands, primarily aimed at optimizing resource utilization and ensuring rapid provision of additional computing power when demand increases.

EBS dynamically adjusts block resources based on the specific needs of dApps, providing independent scaling block space for high-demand dApps, aiming to address the significant differences in performance requirements across different applications. The core advantage of EBS lies in its "predictable performance," meaning it can provide dApps with predictable TPS. Therefore, regardless of whether public block space is congested, dApps with independent block space will achieve stable TPS. Furthermore, if the contracts written by dApps support parallelism, they can achieve even higher TPS. It can be said that EBS provides a more stable environment compared to traditional blockchain platforms like Ethereum and Solana. These traditional platforms often experience performance degradation for dApps during network congestion, such as during inscription booms or peak DeFi activities, while Artela effectively addresses these issues through customized and optimized resource management.

In summary, Artela achieves high scalability and predictable network performance through its parallel execution stack and elastic block space. This parallel execution architecture accurately predicts transaction dependencies through AI models, reducing conflicts and duplicate executions. Additionally, large applications can secure dedicated processing power and resources as needed, ensuring stable performance even under high network load conditions. This enables the Artela network to support more complex application scenarios, such as real-time big data processing and complex financial transactions.