> For the complete documentation index, see [llms.txt](https://bitroot.gitbook.io/bitroot/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://bitroot.gitbook.io/bitroot/parallel-architecture-and-technical-principles.md). # Parallel Architecture and Technical Principles ## **Key Modules** * **Consensus Module**: Handles the consensus mechanism to achieve consistency among nodes. * **Network Module**: Manages communication and data transmission between nodes. * **EVM Module**: Executes Ethereum Virtual Machine (EVM) transactions and manages states. * **Parallel Execution Engine**: Utilizes optimistic parallelism to improve transaction processing efficiency. * **Storage**: Adopts database-backed state sharding for significantly enhanced read/write performance.
## **Architecture Analysis**

Layer	Module/Function	Detailed description
Application layer	DApp (Solidity/Rust)	Interacts with users through smart contracts and provides decentralized application services
Execution layer	Parallel scheduler	Provides the ability to execute transactions in parallel and improves execution efficiency
	├─Transaction conflict detection	Ensures that there are no conflicts between transactions and guarantees the order of transactions
	└─Optimistic parallel execution	Allows transactions to be processed in parallel, reducing waiting time and improving throughput
	EVM execution environment (Geth core)	Based on the Ethereum virtual machine (EVM), it executes smart contracts
Storage layer	DB (state sharding storage)	State sharding technology makes data storage and reading more efficient
	Parallel state access interface	Supports multi-threaded parallel access to the storage layer to improve access speed
Consensus layer	Consensus (0.4s confirmation)	Efficient consensus mechanism, providing fast block confirmation every 0.4 seconds

## **Consensus Layer** The consensus layer adopts an innovative fast consensus mechanism, achieving sub-second (<0.4s) block confirmation speed through multiple technical optimizations.
*** #### **Core Consensus Mechanism** The consensus mechanism is based on an improved **Pipeline BFT** design, which divides the block processing flow into four stages: **block proposal**, **pre-vote**, **pre-commit**, and **commit**. \ **Core Consensus Mechanism** The consensus mechanism is based on an improved **Pipeline BFT** design, which divides the block processing flow into four stages: **block proposal**, **pre-vote**, **pre-commit**, and **commit**. **Pipeline BFT Execution Flow**\ Block(n) -> PreVote(n) -> PreCommit(n) -> Commit(n) ↓ ↓ ↓ Block(n+1) -> PreVote(n+1) -> PreCommit(n+1) ↓ ↓ Block(n+2) -> PreVote(n+2) * **Dual-buffer design** allows simultaneous consensus processing of two block heights. * A height-based **message queue** ensures messages are processed in sequence. * **Batch message processing** is supported—multiple blocks can be confirmed in a single consensus round. *** #### **BLS Signature Optimization** * Uses the **BLS12-381** curve to support **signature aggregation**. * Implements **threshold signature schemes**, supporting *t-n* fault tolerance. * **Signature verification complexity**: *O(log n)*, where *n* is the number of validators. * **Aggregate signature size**: fixed at 96 bytes, regardless of the number of validators. *** #### **Fault Tolerance and Dynamic Membership** **View Change Mechanism**\ ViewChange { \ height: uint64 // current block height \ round: uint32 // current round \ newLeader: ValidatorID // new leader \ proof: \[]ViewProof // view change proof \ sigs: \[]Signature // validator signature \ } * **Timeout-triggered**: `primary_timeout = base_timeout * (1 + round)` * **Fast recovery**: Switches to new leader upon collecting `2f+1` ViewChange messages. * Includes a **ViewSync protocol** to ensure consistent state across nodes. *** #### **Dynamic Validator Management** * Supports **real-time validator set updates** without node restarts. * Implements a **stake-based validator election** mechanism. * Validator update process: `epoch_change -> validator_set_update -> commit -> apply` *** #### **Time Management Optimization** **VTS (Verifiable Timestamp Sequence) Implementation** #### **Time Management Optimization** **VTS (Verifiable Timestamp Sequence) Implementation** ```go type TimeStamp struct { Height uint64 Round uint32 Index uint32 Proposer ValidatorID Signature []byte } ``` * Utilizes **distributed clock synchronization algorithms** to maintain <10ms error margin. * Implements **hybrid timestamping** using Lamport logical clocks and physical clocks. * Supports **fast verification and propagation** of time proofs. **Global Time Consistency Guarantees** * Implements **VRF-based leader election** to ensure fairness. * Supports **deterministic transaction ordering**. * Timestamp verification complexity: *O(1)* *** #### **Parallel Execution Engine Implementation** The parallel execution engine achieves **efficient concurrent processing** of EVM transactions through an **optimistic concurrency execution strategy** and **fine-grained conflict detection**. This significantly enhances system throughput while preserving transaction order and state consistency. *** #### **Optimistic Concurrency Execution Mechanism** The core concept is to **optimistically assume transactions are non-conflicting**. The system performs **dependency analysis** before execution and constructs a **read-write set prediction model** using static contract analysis and historical execution data—achieving a prediction accuracy of over 95%. The execution process follows a **pipeline design** across three stages: * **Preprocessing stage**: Parses transaction data, extracts contract call info, and predicts state access patterns using ML-based models. * **Parallel execution stage**: Transactions are grouped and assigned to different threads. Each thread maintains an independent state view and records state modifications without committing immediately, enabling quick rollback if needed. * **Result validation stage**: Ensures consistency and correctness before committing changes. *** #### **Transaction Conflict Detection and Handling** Conflict detection follows a **three-phase model** to ensure both **efficiency** and **accuracy**: * **Pre-detection**: Uses **Bloom filters** to rapidly screen for potential conflicts. Each transaction maintains a fingerprint of accessed states, enabling microsecond-level detection. * **Runtime detection**: Tracks actual read-write sets of each transaction. It compares with other concurrent transactions to assess conflict severity. * **Commit-phase validation**: Compares state snapshots before and after execution to ensure correctness. *** #### **Performance Optimization Mechanisms** * **Transaction grouping**: Based on access patterns and contract call relationships, transactions are grouped to minimize cross-group conflicts. Conflict rates are usually kept below 5%. * **Adaptive concurrency control**: Monitors system metrics (conflict rate, CPU usage, memory pressure, queue depth) and dynamically adjusts the number of concurrently executed transactions. *** #### **Real-world Performance** In production environments, the optimized parallel execution engine demonstrates outstanding performance: * **Average parallelism**: 16–32 transactions * **Conflict detection latency**: < 50 microseconds * **Conflict recovery time**: typically < 100 microseconds * **Overall throughput**: 8x–15x improvement over serial execution