一句话：提出 Vectra，通过 JIT 合并同构指令来减少 WASM 指令并加速网页端加密货币挖矿。
加密货币生态的民主性依赖矿工多样性，但挖矿逐渐被 ASIC 矿场垄断，网页客户端从 5000 万以上锐减至约 10 万。Monero 等采用 RandomX 等通用硬件算法以抑制矿场，却因网页客户端无法提供所需架构支持而进一步削弱网页挖矿。本文提出 Vectra，一种面向 Web 架构的挖矿程序 JIT 变换技术：它在执行时识别并合并同构指令，并利用指令的符号约束保证变换正确。真实部署表明，Vectra 将 WASM 指令数减少约 7 倍，在 PC、手机和 serverless 等环境取得 3–16 倍加速，为普通用户带来 69%–274% 的投资回报率。
Democracy is crucial to a cryptocurrency ecosystem, as the diversity of miners (farms, personal computers, web clients, or even cloud functions) underlays the credibility of the cryptocurrency. Among miners, web clients used to be the vast majority, e.g., 50M+ as of March 2018. As time went on, however, cryptomining was gradually monopolized by mining farms with dedicated hardware (e.g., ASICs), and web clients scaled down to ∼0.1M. To suppress mining farms, certain cryptocurrencies (like Monero) adopted new mining algorithms such as RandomX whose execution relies on general-purpose hardware architectures. Unfortunately, this further impairs web-based cryptomining as web clients cannot provide the desired architecture support to these algorithms. This paper explores how to revive software democracy of efficient web-based crypto-mining, using a novel program transformation technique termed Vectra. Vectra employs just-in-time (JIT) transformations of mining programs for web architectures; it effectively identifies and merges isomorphic instructions upon execution. Vectra ensures correct transformations based on symbolic constraints of the instructions. Real-world deployments show that Vectra reduces WASM instructions by about 7× and achieves a 3× –16× speedup for web cryptomining in diverse execution environments like PCs, mobile phones, and serverless platforms, which translates to a high (69%–274%) return-on-investment (ROI) for common users.
DOI 原文 ·
@inproceedings{paperbot9320,
title = {Democratizing the Cryptocurrency Ecosystem by Just-In-Time Transformation of Mining Programs},
author = {Wei Liu and Zhenhua Li and Feng Qian and Feiyu Jin and Hao Lin and Yannan Zheng and Bo Xiao and Xiaokang Qin and Tianyin Xu},
booktitle = {ASE},
year = {2025},
doi = {10.1109/ase63991.2025.00040}
}