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Aptos Labs built the parallel execution design that other chains went on to adopt

Aptos Labs created Block-STM, the dynamic parallel execution engine now adopted by Polygon, Sei, Starknet and others. Here is how it works and why it matters.

Aptos Labs built the parallel execution design that other chains went on to adopt

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Sequential transaction execution has long been one of blockchain's most stubborn bottlenecks. Executing a block one transaction at a time does not scale. Long transactions stall everything behind them, so latency and throughput collapse under load. The question facing every high-performance chain has been how to fix that without breaking the deterministic guarantees that make blockchains trustworthy.

Two Approaches, One Winner

One solution asks developers to declare upfront every piece of storage a transaction might touch, allowing a scheduler to run non-overlapping transactions side by side. The problem is that those declared access lists tend to be conservative, holding back work that could have safely run in parallel.

@AptosLabs took a different path. @Aptos executes blocks with Block-STM, a multi-threaded, in-memory engine that combines software transactional memory with a collaborative scheduler. It uses the consensus order as the serial baseline, executes transactions in parallel, and re-executes only the ones that aborted because of a conflict. Critically, developers do not declare access lists. They write ordinary Move, and the engine parallelizes whatever does not conflict.

Block-STM is a parallel execution engine for smart contracts, built around the principles of Software Transactional Memory. Transactions are grouped in blocks, and every execution of the block must yield the same deterministic outcome. Block-STM enforces that the outcome is consistent with executing transactions according to a preset order, leveraging this order to dynamically detect dependencies and avoid conflicts during speculative transaction execution.

An Engine Other Chains Have Since Adopted

The broader industry has taken note. Block-STM is the dynamic-parallelism engine originally built by Aptos Labs. Polygon, Sei, Starknet, and other chains have adopted the same approach.

Block-STM has been adopted for execution on the Polygon PoS chain, where it is already live on mainnet. The proposer uses Block-STM to execute transactions in parallel and includes a DAG in the block to allow deterministic and safe parallel execution at validators. SeiGiga has also adopted Block-STM. On the Ethereum Layer 2 side, StarkWare engineers led the implementation of a variant of Block-STM for Starknet v0.13.2.

The value of parallelism extends far beyond the Aptos ecosystem. Chains like @SeiNetwork have implemented solutions based on Block-STM's design that aim to improve concurrent execution performance. @0xPolygon's adoption has had tangible results: according to the Aptos Foundation, Block-STM's rollout on Polygon PoS was cited as a primary reason the chain processed more than 15 million transactions per day without disruption.

The spread of Block-STM across competing ecosystems is a notable marker of where blockchain infrastructure is heading. What began as @AptosLabs' internal execution engine has effectively become a reference design for any chain serious about throughput.

Sources:
Aptos Documentation: Block-STM Execution
Aptos Foundation: Ecosystem Leading the Way with Parallelism
Starknet: Parallel Execution and v0.13.2

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Author

Crypto Rich profile photoCrypto Rich

Rich has been researching cryptocurrency and blockchain technology for eight years and has served as a senior analyst at BSCN since its founding in 2020. He focuses on fundamental analysis of early-stage crypto projects and tokens and has published in-depth research reports on over 200 emerging protocols. Rich also writes about broader technology and scientific trends and maintains active involvement in the crypto community through X/Twitter Spaces, and leading industry events.

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Aptos Labs built the parallel execution design that other chains went on to adopt | BSCN Breaking News