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Source: TradingView

Source: TheTie

Parallel Ethereum Virtual Machine (Parallel EVM) is an enhanced iteration of the conventional Ethereum Virtual Machine (EVM) employed on the Ethereum blockchain. The key distinction between Parallel EVM and the standard EVM lies in their transaction processing and smart contract execution methods.
In the standard EVM, transactions and smart contracts follow a sequential execution, creating a linear progression. While this straightforward approach may lead to bottlenecks, such as a surge in demand for inscriptions resulting in increased transaction volume, causing delays and heightened gas fees, Parallel EVM effectively addresses and mitigates these issues. Parallel EVM effectively addresses these issues by introducing parallel processing, enabling concurrent execution of multiple transactions, provided they are independent of each other's outcomes. This capability aims to overcome scalability limitations inherent in the standard EVM.
Source: Cryptoeq
- A block is proposed in the current state, State0
- State0 is then broken into four different transactions which are grouped together and processed in parallel by different validators on the network: State1, State2, State3, and State4
- Each state maintains its own set of read operations (readSet) and write operations (writeSet) that represent the transactional history within that state. As transactions progress and execute concurrently, these distinct readSets and writeSets coalesce, working collaboratively to contribute to the final state. The coordination and merging of these sets are crucial in achieving the consistent and accurate end-state across parallel transactions
Within the realm of parallelized EVMs, two primary approaches have emerged: deterministic and speculative parallel execution. The deterministic method uses predefined transaction ordering to prevent conflicts, ensuring a structured and conflict-free execution process. Conversely, speculative scheduling adopts a dynamic approach, running transactions in parallel and addressing conflicts as they arise. These methodologies provide developers with flexibility in selecting the most suitable parallelization strategy for their applications.
While the EVM is fundamental for computations and data storage on the Ethereum blockchain, its sequential transaction ordering has limited scalability. Parallel EVM seeks to overcome this limitation by adopting parallel processing, enhancing the efficiency and scalability of transaction processing and smart contract execution on the Ethereum network. Despite the belief that Directed Acyclic Graph (DAG) technology solves scalability issues present in the standard EVM, there are key differences between these competing technologies.
In comparison to parallelized EVMs, DAGs offer an alternative route to achieving scalability. Unlike traditional blockchains that linearly chain blocks, DAG structures link transactions in a graph format, allowing for the concurrent addition of multiple transactions, resulting in increased transaction speed and scalability.

Source: Central Blockchain Council
While this DAG graphic visually resembles a similar flow of transactions to a parallel EVM, it lacks inherent support for smart contracts and decentralized applications to the same extent as Ethereum. Parallelized EVMs strike a balance by retaining Ethereum's smart contract capabilities while enhancing scalability and efficiency through parallel processing.
This unique combination makes parallelized EVMs well-suited for complex decentralized applications demanding both smart contract functionality and high transaction throughput. Additionally, parallelized EVMs maintain compatibility with the existing Ethereum ecosystem, crucial for developers and users entrenched in Ethereum-based applications. This compatibility facilitates a smoother transition and integration for existing decentralized applications, a challenge often faced in DAG-based systems.
In the expansive landscape of the digital asset ecosystem, numerous teams and chains are introducing competing parallel EVM technologies. Among these, Block-STM and Polygon’s Parallel Blocks stand out as notable players, especially considering that leaders by market cap, such as tokens Aptos and Polygon, aim to implement these technologies to enhance network productivity and speed.
Block-STM:
Below is a paraphrased excerpt from the Block-STM white paper:
Block-STM is a parallel execution engine for smart contracts built around the principles of Software Transactional Memory. The goal of this technology is to accelerate the in-memory execution of transactions via parallelism. STM libraries aim to instrument memory access to detect conflicts. STM libraries with optimistic concurrency control record memory accesses, validate every transaction post execution, and abort and re-execute transactions when validation surfaces a conflict. This leads to a final outcome that is equivalent to the sequential execution of transactions in the present order in which they appear in the block.
Source: Block-STM (arxiv.org).
When the Aptos team implemented Block-STM into their open-source codebase, they compared the system with each block containing 10k transactions with the number of accounts determining the number of conflicts (2 accounts is close to sequential). In scenarios of low conflicting transactions, Block STM demonstrates a 16x improvement in speed compared to sequential execution when employing 32 threads. In situations with high conflicting transactions, Block-STM achieves a speedup of over 8x.
Source: Aptos Labs
Parallel Aware Blocks
In contrast to the original design of Block-STM, the Polygon researchers implemented a minimal metadata approach. Instead of encountering conflicts and requiring re-execution by multiple nodes, their approach involves first reading and writing all transactions on the Polygon chain. These transactions are then recorded in a DAG, enabling the validation process to check for dependencies and take note of them. This minimal metadata approach involves appending information about dependencies to the block, reducing redundancy and computational overhead.
The ongoing parallel EVM efforts have not yet increased capacity, but Polygon is actively laying the groundwork for this enhancement. The subsequent phase of the initiative aims to parallelize block building, enhancing efficiency for validators in constructing blocks and consequently increasing overall capacity.
Another important consideration is the introduction of the concept of making block building 'parallel-aware.' This implies that it may become feasible to include more transactions in a block if Block-STM determines their independence, allowing parallel execution.
While the focus is on highlighting Aptos and Polygon, it is noteworthy that numerous projects are either implementing variations of Block-STM or introducing their own parallel EVM technology. The chart below provides insights into other frequently mentioned players in the parallel EVM space, highlighting key distinctions in implemented technologies and their expected transactions per second (TPS).

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