Key Points
The Solana Virtual Machine (SVM) is the underlying software infrastructure that increases transaction throughput on the Solana blockchain and manages smart contract execution.
Unlike the Ethereum Virtual Machine (EVM), which runs on a sequential processing model and uses the Solidity language, the SVM uses parallel transaction processing and the Rust programming language.
In this article, we will explore what the Solana Virtual Machine is, how it works, and how it differs from the Ethereum Virtual Machine.
Introduction
Blockchains were initially used primarily as decentralized networks for processing transactions. However, with the advent of virtual machines, smart contracts can be built on blockchains, making blockchains a foundational layer for a variety of use cases and applications. The Ethereum Virtual Machine (EVM) and Solana Virtual Machine (SVM) are prime examples. In this article, we’ll explore what the SVM is, how it works, and how it differs from the EVM.
What is the Solana Virtual Machine (SVM)?
SVM is the execution environment for smart contracts on the Solana blockchain. The virtual machine can process thousands of transactions per second (TPS), improving the scalability of the network.
Ethereum was the first to create a blockchain virtual machine, or EVM, which has become the standard today. The EVM architecture inspired multiple blockchains such as BNB Smart Chain, Avalanche, and Tron, which developed systems that forked or were compatible with the EVM. The Solana Virtual Machine has emerged as a strong competitor to this well-known EVM.
How does the Solana VM work?
The Solana Virtual Machine (SVM) is like a powerful computer that runs on the Solana blockchain and processes user-created smart contracts. We can break down the mechanics of how the SVM works into a few different steps.
Validator nodes. Solana has a large number of validator nodes around the world. Each validator runs their own version of SVM, which means they can complete different tasks independently.
Prepare smart contracts. To run a smart contract, SVM first converts it into a language that the node can understand. This ensures that the smart contract can be executed correctly.
Run the smart contract. Once the smart contract is formatted correctly, it will start running. The smart contract will update the blockchain data on the SVM version of the specific node running the smart contract.
Achieve consensus. The updated blockchain version is shared with all other network nodes to achieve consensus.
Let’s imagine a scenario where a user uses a decentralized application (DApp) built on Solana to buy and sell digital art. When they buy a piece of art, a smart contract executes to update the ownership record on the blockchain. The smart contract runs through the SVM on one of the nodes, which checks the rules to ensure that the payment is legitimate and updates the blockchain data.
Parallel execution via SeaLevel
A distinctive feature of SVM is its ability to handle multiple smart contracts simultaneously. This is achieved through Parallel Transaction Processing. Essentially, SVM can execute multiple smart contracts in parallel, thereby increasing transaction throughput and efficiency.
SeaLevel is a component of SVM that handles potential conflicts in parallel execution, that is, conflicts that may arise when multiple transactions affect the same account state at the same time. For example, suppose two transactions are executed at the same time (one is to add funds to a wallet, and the other is to withdraw funds). If not handled properly, it may lead to calculation errors.
SeaLevel is designed to explicitly manage dependencies between transactions. Smart contracts on Solana explicitly specify which parts of the blockchain state each transaction will modify. This allows the system to identify transactions that can be run independently (affecting different parts of the state) and dependent transactions (affecting the same part of the state). Interrelated transactions are processed in order to prevent any conflicts, ensuring that each transaction is executed accurately without affecting the data and the overall performance of the blockchain.
SVM vs. EVM
Transaction Processing Model
SVM uses a parallel processing model that supports processing multiple transactions simultaneously, thereby increasing throughput and reducing latency. In contrast, EVM processes transactions sequentially, which may cause congestion when network usage is high.
programming language
SVM supports Rust, a language known for its efficiency and especially suitable for applications that require high performance and safety. In contrast, EVM uses Solidity, a language designed specifically for smart contract development.
Smart contract deployment and execution
Smart contracts on SVM are executed independently by each validator, which improves the efficiency of network operation. In contrast, EVM requires all nodes to reach a consensus on the results of smart contract execution, which may prolong processing time.
Challenges with SVMs
SVMs face various challenges. One of the main drawbacks is the complexity of maintaining system stability and security in a parallel processing environment. While efficient, this architecture requires additional coordination to prevent conflicts and ensure integrity when processing transactions affecting the same data simultaneously.
In addition, compared with Solidity and other programming languages for blockchain development, the Rust programming language requires more time and effort for new blockchain developers in the initial stage.
Conclusion
SVM is an execution environment on the Solana blockchain that focuses on efficiency in transaction processing and smart contract execution. SVM uses parallel transaction processing and the Rust programming language to improve transaction throughput and scalability. At the same time, SVM also faces some challenges, such as its Rust language requiring a lot of time and effort in the initial stage, and the inherent flaws of the parallel execution model. Nevertheless, the integration of SVM with emerging artificial intelligence technologies is expected to increase its future use and application.
Further reading
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