{"title":"TC:优化编译器","authors":"Piotr Skotnicki","doi":"10.1016/j.softx.2025.102351","DOIUrl":null,"url":null,"abstract":"<div><div>In scientific codes, particularly those used in simulations, the majority of execution time is consumed by the processing of program loops. However, the ordering of statement instances constituting a loop nest, which arises from its naive, typically hand-written implementation, usually leads to inefficient and suboptimal utilization of hardware resources. Over the past decades, significant research efforts have been devoted to developing loop nest transformations aimed at enhancing thread- and instruction-level parallelism, as well as improving memory hierarchy usage, with the affine transformations framework becoming the canonical approach.</div><div>This paper presents TC – a source-to-source optimizing compiler for program loop nests. Unlike state-of-the-art solutions, TC extends the polyhedral compilation pipeline with a data dependence analysis based on the transitive closure relation, significantly broadening the range of optimization opportunities.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"32 ","pages":"Article 102351"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"TC: Optimizing compiler\",\"authors\":\"Piotr Skotnicki\",\"doi\":\"10.1016/j.softx.2025.102351\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In scientific codes, particularly those used in simulations, the majority of execution time is consumed by the processing of program loops. However, the ordering of statement instances constituting a loop nest, which arises from its naive, typically hand-written implementation, usually leads to inefficient and suboptimal utilization of hardware resources. Over the past decades, significant research efforts have been devoted to developing loop nest transformations aimed at enhancing thread- and instruction-level parallelism, as well as improving memory hierarchy usage, with the affine transformations framework becoming the canonical approach.</div><div>This paper presents TC – a source-to-source optimizing compiler for program loop nests. Unlike state-of-the-art solutions, TC extends the polyhedral compilation pipeline with a data dependence analysis based on the transitive closure relation, significantly broadening the range of optimization opportunities.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"32 \",\"pages\":\"Article 102351\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711025003176\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711025003176","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
In scientific codes, particularly those used in simulations, the majority of execution time is consumed by the processing of program loops. However, the ordering of statement instances constituting a loop nest, which arises from its naive, typically hand-written implementation, usually leads to inefficient and suboptimal utilization of hardware resources. Over the past decades, significant research efforts have been devoted to developing loop nest transformations aimed at enhancing thread- and instruction-level parallelism, as well as improving memory hierarchy usage, with the affine transformations framework becoming the canonical approach.
This paper presents TC – a source-to-source optimizing compiler for program loop nests. Unlike state-of-the-art solutions, TC extends the polyhedral compilation pipeline with a data dependence analysis based on the transitive closure relation, significantly broadening the range of optimization opportunities.
期刊介绍:
SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.