用于比特币区块链头的硬件加速可重用Merkle树生成

IF 1.4 3区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Computer Architecture Letters Pub Date : 2023-06-28 DOI:10.1109/LCA.2023.3289515
Kiseok Jeon;Junghee Lee;Bumsoo Kim;James J. Kim
{"title":"用于比特币区块链头的硬件加速可重用Merkle树生成","authors":"Kiseok Jeon;Junghee Lee;Bumsoo Kim;James J. Kim","doi":"10.1109/LCA.2023.3289515","DOIUrl":null,"url":null,"abstract":"As the value of Bitcoin increases, the difficulty level of mining keeps increasing. This is generally addressed with application-specific integrated circuits (ASIC), but block candidates are still created by the software. The overhead of block candidate generation is relatively growing because the hash computation is boosted by ASIC. Additionally, it is getting harder to find the target nonce; If it is not found for a block candidate, a new block candidate must be generated. A new candidate can be generated to reduce the overhead of block candidate generation by modifying the coinbase without selecting and verifying transactions again. To this end, we propose a hardware accelerator for generating Merkle trees efficiently. The hash computation for Merkle tree generation is conducted with ASIC to reduce the overhead of block candidate generation, and the tree with only the modified coinbase is rapidly regenerated by reusing the intermediate results of the previously generated tree. Our simulation results demonstrate that the execution time can be reduced by up to 98.92% and power consumption by up to 99.73% when the number of transactions in a tree is 2048.","PeriodicalId":51248,"journal":{"name":"IEEE Computer Architecture Letters","volume":"22 2","pages":"69-72"},"PeriodicalIF":1.4000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hardware Accelerated Reusable Merkle Tree Generation for Bitcoin Blockchain Headers\",\"authors\":\"Kiseok Jeon;Junghee Lee;Bumsoo Kim;James J. Kim\",\"doi\":\"10.1109/LCA.2023.3289515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the value of Bitcoin increases, the difficulty level of mining keeps increasing. This is generally addressed with application-specific integrated circuits (ASIC), but block candidates are still created by the software. The overhead of block candidate generation is relatively growing because the hash computation is boosted by ASIC. Additionally, it is getting harder to find the target nonce; If it is not found for a block candidate, a new block candidate must be generated. A new candidate can be generated to reduce the overhead of block candidate generation by modifying the coinbase without selecting and verifying transactions again. To this end, we propose a hardware accelerator for generating Merkle trees efficiently. The hash computation for Merkle tree generation is conducted with ASIC to reduce the overhead of block candidate generation, and the tree with only the modified coinbase is rapidly regenerated by reusing the intermediate results of the previously generated tree. Our simulation results demonstrate that the execution time can be reduced by up to 98.92% and power consumption by up to 99.73% when the number of transactions in a tree is 2048.\",\"PeriodicalId\":51248,\"journal\":{\"name\":\"IEEE Computer Architecture Letters\",\"volume\":\"22 2\",\"pages\":\"69-72\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2023-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Computer Architecture Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10167735/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Computer Architecture Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10167735/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0

摘要

随着比特币价值的增加,挖矿的难度也在不断增加。这通常通过专用集成电路(ASIC)来解决,但块候选者仍然由软件创建。块候选生成的开销相对增长,因为ASIC提高了哈希计算。此外,查找目标nonce变得越来越困难;如果找不到块候选,则必须生成新的块候选。可以生成新的候选,以通过修改coinbase来减少块候选生成的开销,而无需再次选择和验证事务。为此,我们提出了一种有效生成Merkle树的硬件加速器。Merkle树生成的哈希计算是用ASIC进行的,以减少块候选生成的开销,并且通过重用先前生成的树的中间结果来快速再生仅具有修改的coinbase的树。我们的仿真结果表明,当树中的事务数为2048时,执行时间可以减少98.92%,功耗可以减少99.73%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Hardware Accelerated Reusable Merkle Tree Generation for Bitcoin Blockchain Headers
As the value of Bitcoin increases, the difficulty level of mining keeps increasing. This is generally addressed with application-specific integrated circuits (ASIC), but block candidates are still created by the software. The overhead of block candidate generation is relatively growing because the hash computation is boosted by ASIC. Additionally, it is getting harder to find the target nonce; If it is not found for a block candidate, a new block candidate must be generated. A new candidate can be generated to reduce the overhead of block candidate generation by modifying the coinbase without selecting and verifying transactions again. To this end, we propose a hardware accelerator for generating Merkle trees efficiently. The hash computation for Merkle tree generation is conducted with ASIC to reduce the overhead of block candidate generation, and the tree with only the modified coinbase is rapidly regenerated by reusing the intermediate results of the previously generated tree. Our simulation results demonstrate that the execution time can be reduced by up to 98.92% and power consumption by up to 99.73% when the number of transactions in a tree is 2048.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Computer Architecture Letters
IEEE Computer Architecture Letters COMPUTER SCIENCE, HARDWARE & ARCHITECTURE-
CiteScore
4.60
自引率
4.30%
发文量
29
期刊介绍: IEEE Computer Architecture Letters is a rigorously peer-reviewed forum for publishing early, high-impact results in the areas of uni- and multiprocessor computer systems, computer architecture, microarchitecture, workload characterization, performance evaluation and simulation techniques, and power-aware computing. Submissions are welcomed on any topic in computer architecture, especially but not limited to: microprocessor and multiprocessor systems, microarchitecture and ILP processors, workload characterization, performance evaluation and simulation techniques, compiler-hardware and operating system-hardware interactions, interconnect architectures, memory and cache systems, power and thermal issues at the architecture level, I/O architectures and techniques, independent validation of previously published results, analysis of unsuccessful techniques, domain-specific processor architectures (e.g., embedded, graphics, network, etc.), real-time and high-availability architectures, reconfigurable systems.
期刊最新文献
A Flexible Hybrid Interconnection Design for High-Performance and Energy-Efficient Chiplet-Based Systems Efficient Implementation of Knuth Yao Sampler on Reconfigurable Hardware SmartQuant: CXL-Based AI Model Store in Support of Runtime Configurable Weight Quantization Proactive Embedding on Cold Data for Deep Learning Recommendation Model Training Octopus: A Cycle-Accurate Cache System Simulator
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1