EVM's sequential execution model creates an artificial bottleneck. Every transaction must be processed in a single, deterministic order, wasting idle CPU cycles while waiting for unrelated operations to complete.
Why Parallel Execution Demands a Language Like Move
Parallel execution is the next frontier for blockchain throughput. This analysis explains why the Ethereum Virtual Machine (EVM) is fundamentally ill-suited for it and how Move's explicit ownership semantics provide the necessary safety guarantees for chains like Aptos and Sui to scale.
Introduction: The Parallel Execution Bottleneck
EVM's sequential processing fundamentally limits throughput, making parallel execution a non-negotiable requirement for scaling.
Parallel execution demands deterministic concurrency. Unlike Solana's optimistic model, which requires runtime conflict resolution, a language like Move provides static data ownership guarantees. The compiler, not the runtime, proves transactions are independent.
The Aptos and Sui blockchains demonstrate this principle. By enforcing the Move language's resource model, they achieve theoretical throughputs orders of magnitude higher than EVM chains by executing thousands of non-conflicting transactions simultaneously.
Evidence: Solana's runtime overhead. Despite high throughput, Solana's parallel execution engine spends significant cycles on runtime conflict detection and rollback, a tax that Move's compile-time checks eliminate.
The Parallel Execution Arms Race
Parallel execution is the new performance frontier, but unlocking it requires a language that prevents the chaos of concurrent state access.
The Problem: The Shared Mutable State Nightmare
EVM's shared global state forces sequential execution to prevent non-determinism. Parallelizing it is like herding cats—you need complex, expensive dependency analyzers (like Solana's scheduler or Sei's parallelization) to guess which transactions conflict.
- Resource Contention: Every transaction is a potential conflict, limiting theoretical speedup.
- Wasted Cycles: Schedulers spend compute to detect conflicts that a better language could prevent.
The Solution: Move's Resource-Oriented Model
Move's type system treats assets as non-copyable, non-double-spendable resources stored in user accounts. This enables compile-time guarantees.
- Ownership by Reference: The compiler statically enforces that a resource has one owner or a known number of immutable references, eliminating read/write conflicts.
- Deterministic Parallelism: A runtime (like Aptos Block-STM or Sui's object-centric model) can safely execute transactions in parallel if they touch different resources.
Sui vs. Aptos: Two Flavors of Move Parallelism
Both use Move but architect parallelism differently, showcasing the language's flexibility.
- Sui's Object-Centric: Parallelizes per independent object. Ideal for high-throughput simple transfers and gaming (~297k TPS in benchmarks).
- Aptos Block-STM: Uses Software Transactional Memory for optimistic parallel execution of any transactions, then reconciles. Better for complex, interdependent DeFi operations.
The EVM's Uphill Battle: Fraud Proofs & State Diffs
EVM L2s (Arbitrum, Optimism, zkSync) are retrofitting parallelism, but face inherent language constraints. Their solutions are architectural workarounds.
- Monolithic vs. Modular: They offload execution to separate modules or use fraud/validity proofs over state diffs, adding latency and complexity.
- The Cost of Legacy: Achieving safe parallelism requires heavier client-side verification, moving further from the elegant 'static guarantee' model.
The Verdict: First-Principles Design Wins
Parallel execution isn't just about more cores; it's about a language that makes concurrent access safe by construction. Move was designed for this from day one.
- EVM Parallelism: A complex, bolt-on optimization with diminishing returns.
- Move Parallelism: A fundamental property, enabling linear scaling with cores. This is why Aptos, Sui, and Linera are betting their stack on it.
The Next Frontier: Parallel Intent Execution
The final boss is parallelizing complex user intents (like those in UniswapX or CowSwap). Move's model is uniquely suited for this.
- Composable Safety: Intents often involve multi-asset swaps across pools. Move's resource logic allows these composite operations to be broken into parallel sub-transactions safely.
- Beyond Simple Payments: This positions Move chains (Sui, Aptos) to capture the next wave of intent-based DeFi and on-chain gaming, where concurrency is the product.
The EVM's Fatal Flaw: Implicit, Global Mutability
EVM's shared storage model creates a sequential bottleneck that parallel execution cannot fix without a fundamental language redesign.
Implicit State Dependencies cripple parallelization. The EVM's global state is a single key-value store where any contract can write anywhere. This forces validators to assume all transactions conflict, executing them serially. Solidity offers no native syntax to declare which storage slots a function accesses.
Move's Resource Model solves this with explicit ownership. Assets are typed objects that cannot be copied or implicitly referenced. The Move Prover statically analyzes data flow, allowing Aptos and Sui to schedule non-conflicting transactions in parallel without runtime guesswork.
The Gas Cost Fallacy is the wrong optimization. EVM chains like Monad optimize gas metering for speed, but this treats the symptom. The root cause is the language's permissionless mutability, which makes dependency analysis a heuristic game for sequencers like Arbitrum Nitro.
Evidence: Aptos' Block-STM scheduler achieves 160k TPS in benchmarks by leveraging Move's static guarantees. Ethereum L2s using optimistic parallelization, like Monad, introduce complex rollback logic and cannot guarantee the same deterministic speedup.
Language-Level Design Trade-Offs
Comparing core language design choices that determine the feasibility and efficiency of parallel transaction execution, using Move as the benchmark for native support.
| Core Feature / Constraint | Move (Aptos/Sui) | EVM (Ethereum, L2s) | WASM (Solana, NEAR) |
|---|---|---|---|
Explicit Resource Ownership | |||
Static, Bytecode-Verifiable Data Access | |||
Global State Partitioning via Object ID | |||
Native Asset Primitive (Coin) | |||
Deterministic Execution Guarantee | |||
Dynamic State Access via MPT | |||
Transaction Dependency Auto-Detection | |||
Typestate System for Invariants |
Counterpoint: Can't We Just Fix the EVM?
The EVM's design is fundamentally incompatible with safe, high-throughput parallel execution.
The EVM's state model is inherently ambiguous. Solidity's dynamic storage pointers and delegatecall create opaque, non-deterministic access patterns, making it impossible for a parallel scheduler to safely pre-determine transaction conflicts.
Retrofitting is a performance dead end. Projects like Monad and Reth implement optimistic parallelization, but they require complex runtime analysis and still face reversion overhead, unlike Move's compile-time guarantees.
Move's resource semantics are the fix. Its linear type system and explicit acquires keyword allow the compiler to generate a precise access list, enabling deterministic, conflict-free scheduling without runtime guesswork.
Evidence: Sui and Aptos demonstrate this, achieving deterministic parallel execution where EVM Layer 2s like Arbitrum and Optimism remain fundamentally sequential at the execution layer.
Key Takeaways for Builders
Parallel execution is not just about hardware; it's a software architecture problem. Here's why your language choice is the primary bottleneck.
The Race Condition Nightmare
Naive parallelization in dynamic languages like Solidity leads to non-deterministic state conflicts, forcing serial execution and killing performance.\n- Move's linear types ensure an asset can only have one owner at a time, making data dependencies explicit.\n- The compiler statically proves which transactions are independent, enabling safe parallelization without runtime guesswork.
Aptos & Sui's Throughput Proof
These L1s demonstrate Move's production-scale advantage, achieving 160k+ TPS in controlled environments versus Ethereum's ~15 TPS.\n- Deterministic execution from the type system eliminates re-execution and complex conflict resolution seen in Solana's runtime.\n- Native resource-oriented model maps directly to parallel execution units, unlike EVM's shared global state.
The Verifier-First Security Model
Move shifts security guarantees from runtime to compile-time, which is critical for parallel systems where bugs are non-reproducible.\n- Bytecode verifier enforces resource rules before deployment, preventing entire classes of exploits (reentrancy, overflow).\n- This creates a hardened execution environment where parallel threads cannot corrupt each other's state, a foundational requirement for high-frequency DeFi.
EVM's Inherent Serial Mindset
The EVM's stack-based architecture and unlimited mutable storage were designed for a single-threaded world, creating insurmountable friction for parallelization.\n- Projects like Monad and Sei must build complex parallel EVMs with custom state access lists, a $100M+ engineering effort.\n- Move provides this natively, making Sui's object-centric and Aptos's fine-grained storage models trivial to implement.
The Composability Paradox
Parallel execution can fragment liquidity and break atomic composability. Move's design turns this into a feature.\n- Explicit data declarations allow the runtime to identify composable transactions (touching same object) and execute them atomically.\n- This enables high-throughput, complex settlements (e.g., AMM swaps with staking rewards) that are impossible in serially-constrained systems without Layer 2 batching.
Future-Proofing for Heterogeneous Hardware
The end-state is multi-core, multi-machine execution. Move's abstraction is ready; most languages are not.\n- Resource-oriented programming cleanly maps to sharded and heterogeneous hardware architectures (GPUs, FPGAs).\n- Building on the EVM today means your $1B+ protocol will require a costly, insecure rewrite when parallel hardware becomes standard, as seen in traditional high-frequency trading.
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