DTVM: Revolutionizing Smart Contract Execution with Determinism and Compatibility

2025-04-23

AI Summary

To address performance bottlenecks, non-determinism risks, and insufficient ecosystem compatibility in blockchain smart contract execution, this paper proposes the Deterministic Virtual Machine (DTVM) stack. Methodologically, it introduces: (1) a novel deterministic intermediate representation (dMIR) ensuring cross-platform execution consistency; (2) a hybrid lazy JIT engine with jump-stub hot-swapping for ultra-low-latency invocation (0.95 ms); (3) a modular ISA adaptation layer and an EVM ABI–compatible multi-language support framework; and (4) SmartCogent—a full-stack development platform powered by a RAG-enhanced, fine-tuned LLM. Experiments demonstrate a 2× speedup on mainstream ERC contracts, 11.8%–40.5% latency reduction in Fibonacci computation, 23× higher call efficiency, and 30.0%–72.6% bytecode size reduction. The implementation is open-sourced.

Technology Category

• Planning, Routing, and Scheduling: Deterministic Planning
• Data Mining & Knowledge Management: Intelligent Query Processing
• Intelligent Robots: Embodied AI

Application Category

• Security and Privacy: Cryptocurrency and smart contracts
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

We introduce the DeTerministic Virtual Machine (DTVM) Stack, a next-generation smart contract execution framework designed to address critical performance, determinism, and ecosystem compatibility challenges in blockchain networks. Building upon WebAssembly (Wasm) while maintaining full Ethereum Virtual Machine (EVM) ABI compatibility, DTVM introduces a Deterministic Middle Intermediate Representation (dMIR) and a hybrid lazy-JIT compilation engine to balance compilation speed and execution efficiency. DTVM further accommodates diverse instruction set architectures (e.g., EVM, RISC-V) through modular adaptation layers. This enables seamless integration with DTVM's hybrid lazy-JIT compilation engine, which dynamically optimizes performance while preserving deterministic execution guarantees across heterogeneous environments. The key contributions including: 1). The framework achieves up to 2$ imes$ acceleration over evmone in dominant Ethereum contract (e.g. ERC20/721/1155) execution and reduces fibonacci computation latency by 11.8$sim$40.5% compared to Wasm based VMs. 2). A novel trampoline hot-switch mechanism enables sub-millisecond (0.95ms) post-deployment invocation times, outperforming up to about 23$ imes$ in compilation and invocation efficiency. 3). It supports multi-language development (Solidity, C++, Rust, Java, Go, and AssemblyScript) through unified bytecode conversion while maintaining EVM ABI compatibility for seamless invocation. It reduces machine code object sizes by 30.0$sim$72.6%, coupled with a minimized Trusted Computing Base. 4). It offers SmartCogent, an AI-driven full-stack development experience, leveraging fine-tuned LLMs and retrieval-augmented generation to automate tasks across the smart contract lifecycle: development, debugging, security auditing, and deployment. DTVM Stack has been open-sourced (https://github.com/DTVMStack).

Problem

• Enhancing smart contract performance and determinism in blockchain
• Achieving EVM compatibility while supporting diverse instruction sets
• Optimizing compilation and execution efficiency across heterogeneous environments

Innovation

• Hybrid lazy-JIT compilation engine for efficiency
• Modular adaptation layers for diverse ISAs
• Deterministic Middle Intermediate Representation (dMIR)