Why Parallel Execution is Non-Negotiable for Next-Gen dApps

Sui's core innovation is its object-centric data model, allowing transactions affecting independent objects to be processed simultaneously. This bypasses the global state contention of account-based models.

• Key Benefit: Achieves 120k+ TPS in controlled benchmarks by eliminating unnecessary ordering.
• Key Benefit: Native support for complex on-chain assets and DeFi primitives without serialization bottlenecks.

Aptos uses Block-STM, a software transactional memory runtime that optimistically executes all transactions in parallel and then re-executes conflicts.

• Key Benefit: Developer-friendly; requires no explicit state access declarations, maintaining EVM-like semantics.
• Key Benefit: Proven scaling; handles 30k+ TPS in real-world stress tests, making it a direct competitor to Solana.

Solana's Sealevel runtime is a hardware-optimized parallel engine. It requires transactions to declare state read/write sets upfront, enabling deterministic scheduling across GPU cores.

• Key Benefit: Hardware-saturating throughput; architecture is designed to max out modern SSD and GPU capabilities.
• Key Benefit: Sub-second finality and ~$0.001 average fees create a viable environment for high-frequency on-chain applications.

Monad is building a fully parallelized EVM L1 from the ground up, combining a parallel execution engine with a novel consensus and storage architecture.

• Key Benefit: Full EVM bytecode compatibility means seamless migration for existing dApps like Uniswap and Aave.
• Key Benefit: Pipelined processing separates execution, consensus, and storage, targeting 10k+ TPS while reducing hardware requirements.

Ethereum processes transactions one at a time, creating a massive bottleneck. This serial execution limits throughput to ~15-30 TPS, causing network congestion and volatile, high gas fees during peak demand.

• Consequence: Makes high-frequency trading, gaming, and social dApps economically and technically infeasible.
• Consequence: Cedes the entire performance-sensitive application layer to competing L1s and L2s.

Ethereum L2s like Arbitrum Stylus and Polygon zkEVM are integrating parallel execution engines to offer Ethereum security with Solana-like throughput.

• Key Benefit: Preserves Ethereum's security and liquidity while breaking its performance ceiling.
• Key Benefit: Creates a clear scaling path: parallel L2s for execution, Ethereum L1 for settlement and data availability.

Ethereum's single-threaded execution serializes all transactions, creating artificial congestion and high fees. This is the root cause of poor UX and limited scalability for DeFi and gaming.

• Throughput Ceiling: Limits chains to ~10-100 TPS, regardless of consensus speed.
• Resource Waste: Idle compute while unrelated transactions (e.g., Uniswap vs. NFT mint) wait in line.
• Cost Inflation: Peak demand turns gas auctions into a winner-take-all fee market.

Sei v2 implements a parallelized EVM by using optimistic concurrency control, allowing independent transactions to execute simultaneously while maintaining compatibility.

• Deterministic Parallelism: Uses a dependency checker to run non-conflicting tx in parallel, achieving ~80% parallelization rate.
• EVM Bytecode Compatible: Developers deploy existing Solidity/Vyper contracts with zero code changes.
• Orderbook-First Design: Native infrastructure for high-frequency DEXs like Astroport and Kryptonite.

Solana's architecture, via the Sealevel runtime, is parallel by default. Transactions explicitly state required accounts, enabling the scheduler to execute non-overlapping sets concurrently.

• State-Level Concurrency: The runtime schedules at the account level, not the chain level.
• Hardware Maximization: Designed to saturate modern multi-core servers, pushing ~3k-5k real TPS.
• Ecosystem Mandate: Forces all high-performance dApps (e.g., Jupiter, Drift, Tensor) to be parallel-aware from day one.

Monad is building a new EVM-compatible L1 from the ground up, separating execution from consensus with pipelining and async execution to achieve massive parallelism.

• Pipelined Stages: Overlaps consensus, execution, and storage I/O to eliminate idle hardware cycles.
• MonadDB: A custom state store using succinct proofs for fast read/writes, removing the storage bottleneck.
• Deferred Execution: Allows the runtime to speculatively execute transactions before final consensus, similar to Aptos and Sui.

Parallel execution enables a new paradigm: intent-based architectures where users declare outcomes, not transactions. Solvers compete in parallel to fulfill them.

• Solvers in Parallel: Protocols like UniswapX, CowSwap, and Across run complex routing logic off-chain, submitting only final settlements.
• MEV Capture: Parallel block building (e.g., Flashbots SUAVE) allows searchers to explore more complex, profitable bundles.
• User Abstraction: Removes the need for users to manually sequence transactions across dApps.

For next-gen dApps—from on-chain games with thousands of concurrent players to hyper-liquid CLOBs—sequential execution is a non-starter. The vanguard is clear.

• Gaming & Social: Parallel execution is the only way to support real-time, stateful interactions for millions.
• DeFi 2.0: Complex, multi-legged strategies (like those on dYdX or Aevo) require simultaneous price updates and liquidations.
• The Bottom Line: The next $100B protocol will be built on a parallel execution engine.

Sequential blockchains are a searcher's paradise. Without parallel execution, every transaction must be ordered, creating a single, predictable queue for front-running and sandwich attacks. This extracts ~$1B+ annually from users and distorts market efficiency.

• Predictable Ordering: Enables deterministic, low-risk MEV strategies.
• User Tax: Fees are inflated by bots competing for priority.
• Protocol Risk: DEXs like Uniswap and Curve become primary hunting grounds.

In a serial environment, one popular dApp can congest the entire chain. A single hot NFT mint or DeFi yield harvest on Aave or Compound creates network-wide gas spikes and >10s latency, blocking all other applications.

• Congestion Collapse: One app's success becomes the network's failure.
• Poor UX: Latency kills interactive apps like on-chain games.
• Stifled Innovation: Developers are forced to design for the lowest common throughput.

Serial execution underutilizes modern multi-core hardware. A validator's CPU sits >90% idle while processing transactions one-by-one, forcing the network to pay a massive premium for single-threaded performance instead of cheap, parallel compute.

• Hardware Mismatch: Architecture is antithetical to cloud and consumer hardware trends.
• Cost Inefficiency: Users pay for wasted capacity.
• Scalability Ceiling: Throughput is capped by single-core clock speed, not network capacity.

Non-parallel systems cannot resolve access conflicts intelligently. Two unrelated DeFi trades touching different pools (e.g., Uniswap V3 and Balancer) are forced to serialize, causing artificial contention. This limits theoretical throughput to <5k TPS regardless of hardware.

• False Conflicts: Unrelated transactions are blocked unnecessarily.
• Low Throughput: Theoretical max is orders of magnitude below physical limits.
• Wasted Blockspace: Empty slots due to artificial scheduling delays.

Ethereum's EVM processes transactions one-by-one, creating a predictable but slow queue. Solana's Sealevel runtime allows parallel execution but faces congestion from its monolithic scheduler. The next leap requires dynamic, fine-grained parallelism.

• Key Insight: True parallelism separates execution from consensus.
• Result: Enables 10-100x higher throughput without compromising decentralization.

These L1s bake parallelism into their state model. Aptos Block-STM uses software transactional memory for optimistic parallel execution. Sui's model treats assets as discrete objects, allowing non-conflicting transactions to be processed simultaneously.

• Key Benefit: Sub-second finality for user actions.
• Key Benefit: Eliminates gas fee wars for non-overlapping operations.

Parallel execution isn't just about speed; it's about cost and reliability. When a DeFi transaction doesn't compete with an unrelated NFT mint, its gas cost becomes stable.

• Key Benefit: Enables complex, multi-step dApps (e.g., on-chain games, perp DEXs) without unpredictable reverts.
• Key Benefit: ~90% reduction in failed transaction costs for high-frequency users.

Parallel execution forces a choice. Monolithic chains (Solana, Aptos, Sui) optimize for performance within a single state machine. Modular stacks (Ethereum + parallelized rollups) separate execution layers. The winner depends on your security and sovereignty needs.

• Key Insight: EVM parallelization (via Neon, Monad) is coming but adds complexity.
• Result: Builders must choose their parallelism layer as a first-principle decision.

Users don't care about consensus algorithms. They experience wallets that hang and transactions that fail. Parallel execution is the only path to sub-500ms feedback for on-chain actions, which is the baseline for mass adoption.

• Key Benefit: Enables consumer-grade UX for wallets and dApps.
• Key Benefit: Removes the 'blockchain wait' as a product design constraint.

Parallel execution exponentially increases state growth. Chains like Sui and Aptos require validators with hundreds of GB of RAM and high-end SSDs. This trades decentralization for performance, creating a new scaling trilemma.

• Key Insight: Throughput is meaningless without affordable state access.
• Result: Next-gen dApps must architect for state expiry or statelessness from day one.