The Future of State Management is Parallel, Not Serial

Ethereum's EVM is single-threaded. Every transaction must be processed in a strict, global order, creating a deterministic but slow execution model. This serial processing is the root cause of low throughput and high latency across L1s and L2s.

Parallel execution is the only viable scaling path. Modern compute uses thousands of cores; Solana's Sealevel runtime and Aptos' Block-STM prove this model works. The future is not faster single-core processors, but architectures that process unrelated transactions simultaneously.

The bottleneck is state access, not computation. The real challenge is managing concurrent reads and writes to shared state. Solutions like Monad's parallel EVM and Fuel's UTXO-based model attack this by redesigning state access patterns, not just adding more hardware.

Serial state execution is the bottleneck. Every transaction must be processed in a single, deterministic order to maintain consensus, which caps throughput at the speed of a single CPU core. This is why Solana's parallel runtime, Sealevel, was a breakthrough.

Parallel execution unlocks hardware scaling. Architectures like Aptos' Block-STM and Sui's object-centric model allow unrelated transactions to process simultaneously. This shifts the constraint from CPU speed to memory access and state contention.

The next frontier is parallel proving. Even with parallel execution, generating a single validity proof for the entire block re-serializes the workload. Projects like RiscZero and Succinct are developing parallel provers to solve this final bottleneck.

Evidence: Aptos' Block-STM demonstrates the principle, achieving up to 160k TPS in controlled benchmarks by reordering and executing transactions concurrently, a direct attack on the serial state management problem.

Serial execution is the bottleneck. EVM and most L1s process transactions sequentially, creating a single point of contention for state access that caps throughput and inflates fees.

Parallelization requires conflict detection. Protocols like Sui and Aptos use a Move VM to statically analyze transactions for overlapping state dependencies, allowing non-conflicting transactions to execute simultaneously.

Ethereum's path is optimistic parallelism. Arbitrum Stylus and Monad implement optimistic parallel execution, speculatively running transactions in parallel and using fraud proofs to resolve conflicts, achieving 10k+ TPS in benchmarks.

The future is modular parallelism. Execution layers like Fuel and Eclipse separate state access into independent shards or 'pipelines', enabling parallel processing that scales horizontally with core count.

Parallel execution fragments state access. Serial execution guarantees a single, linear state transition path. Parallel engines like Aptos Move or Sui require explicit dependency declaration, which breaks atomic composability for undeclared interactions.

The trade-off is explicit vs. implicit composability. Serial chains like Ethereum offer implicit, universal composability at the cost of throughput. Parallel systems demand developers explicitly define dependencies, sacrificing spontaneous composability for performance.

This creates a new class of MEV. Without a global ordering, cross-shard or cross-object arbitrage becomes a coordination game. Validators in systems like Solana or Monad can front-run dependent transactions across parallel threads.

Evidence: The rise of intent-based architectures (UniswapX, CowSwap) is a direct response. They abstract complexity by outsourcing routing, a pattern that will dominate in a parallelized, fragmented state landscape.