{"title":"Pipe-DBT: enhancing dynamic binary translation simulators to support pipeline-level simulation","authors":"Tiancheng Tang, Yi Man, Xinbing Zhou, Duqing Wang","doi":"10.1007/s10515-025-00506-8","DOIUrl":null,"url":null,"abstract":"<div><p>In response to the lack of pipeline behavior modeling in Instruction-Set Simulators (ISS) and the performance limitations of Cycle-Accurate Simulators (CAS), this paper proposes Pipe-DBT, a pipeline simulation framework based on Dynamic Binary Translation (DBT). This method achieves a balance between accuracy and efficiency through two key techniques: (1) the design of a pipeline state descriptor called Pipsdep, which abstracts data hazards and resource contentions in the form of formal rules about resource occupancy and read/write behaviors, thereby avoiding low-level hardware details; (2) the introduction of a coroutine-based instruction execution flow partitioning mechanism that employs dynamic suspension/resumption to realize cycle-accurate scheduling in multi-stage pipelines. Implemented on QEMU, Pipe-DBT supports variable-length pipelines, a Very Long Instruction Word (VLIW) architecture with four-issue capability, and pipeline forwarding. Under typical DSP workloads, it achieves a simulation speed of 400–1100 KIPS, representing a 2.3<span>\\(\\times\\)</span> improvement over Gem5 in cycle-accurate mode. Experimental results show that only modular extensions to the host DBT framework are required to accommodate heterogeneous pipeline microarchitectures, thereby providing a high-throughput simulation infrastructure for processor design. To the best of our knowledge, this is the first pipeline-level simulation model implemented on a DBT simulator.</p></div>","PeriodicalId":55414,"journal":{"name":"Automated Software Engineering","volume":"32 2","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10515-025-00506-8.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automated Software Engineering","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10515-025-00506-8","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
In response to the lack of pipeline behavior modeling in Instruction-Set Simulators (ISS) and the performance limitations of Cycle-Accurate Simulators (CAS), this paper proposes Pipe-DBT, a pipeline simulation framework based on Dynamic Binary Translation (DBT). This method achieves a balance between accuracy and efficiency through two key techniques: (1) the design of a pipeline state descriptor called Pipsdep, which abstracts data hazards and resource contentions in the form of formal rules about resource occupancy and read/write behaviors, thereby avoiding low-level hardware details; (2) the introduction of a coroutine-based instruction execution flow partitioning mechanism that employs dynamic suspension/resumption to realize cycle-accurate scheduling in multi-stage pipelines. Implemented on QEMU, Pipe-DBT supports variable-length pipelines, a Very Long Instruction Word (VLIW) architecture with four-issue capability, and pipeline forwarding. Under typical DSP workloads, it achieves a simulation speed of 400–1100 KIPS, representing a 2.3\(\times\) improvement over Gem5 in cycle-accurate mode. Experimental results show that only modular extensions to the host DBT framework are required to accommodate heterogeneous pipeline microarchitectures, thereby providing a high-throughput simulation infrastructure for processor design. To the best of our knowledge, this is the first pipeline-level simulation model implemented on a DBT simulator.
期刊介绍:
This journal details research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modeling software artifacts and processes.
Coverage in Automated Software Engineering examines both automatic systems and collaborative systems as well as computational models of human software engineering activities. In addition, it presents knowledge representations and artificial intelligence techniques applicable to automated software engineering, and formal techniques that support or provide theoretical foundations. The journal also includes reviews of books, software, conferences and workshops.