Smart Contract Bytecode Preprocessing for Execution Speed
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Solution Overview
Problem
Current blockchain platforms face inefficiencies in executing smart contracts due to the need for repeated parsing and decoding of bytecode during invocation, which hampers execution speed and overall platform performance.
Innovation Solution
Preprocessing bytecode during deployment to generate a cacheable data structure that includes executable instruction codes and function index tables, allowing direct execution without additional parsing or decoding during invocation, and reusing this structure for multiple executions of the same smart contract.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If bytecode is parsed and decoded during each contract invocation, then the smart contract can be executed, but execution speed decreases due to repeated processing overhead
Solution Approach 1:
The patent applies preliminary action by preprocessing the bytecode during the contract deployment phase. The virtual machine parses and decodes the bytecode once during deployment, converting it into executable instructions and storing them in cache memory. This eliminates the need for repeated parsing and decoding during subsequent contract invocations, directly resolving the technical contradiction by preparing the execution environment in advance.
2Productivity
If bytecode is preprocessed during deployment phase, then execution efficiency improves, but deployment phase complexity increases
Solution Approach 1:
The patent performs bytecode parsing and decoding as a preliminary action during the deployment phase. The virtual machine processes the bytecode once, generates executable instructions, and caches them for rapid execution. This shifts the processing complexity to the deployment phase while achieving significant productivity gains during execution, accepting temporary complexity increase for long-term efficiency improvement.
3Speed
If bytecode is cached in memory during deployment, then invocation speed increases, but memory usage increases
Solution Approach 1:
The patent applies the copying principle by creating a cached copy of the parsed and decoded bytecode instructions in the virtual machine's memory. Instead of repeatedly processing the original bytecode during each invocation, the system stores and reuses the executable instruction copy. This trade-off increases memory consumption but dramatically improves invocation speed by eliminating repeated parsing operations.
Data Source
AI summary
Implementations of the present specification provide a method for deploying a smart contract. According to one implementation the method includes: receiving a transaction request for invoking a first contract; obtaining a first instruction code and a function index table, wherein the function index table is used to indicate a memory address of an instruction code corresponding to each of import and export functions in the first contract; determining a first memory address corresponding to the invocation function based on the function index table; and executing the first instruction code in the first memory address based on the determined first memory address.


