{"title":"Instruction folding in a hardware-translation based java virtual machine","authors":"Hitoshi Oi","doi":"10.1145/1128022.1128041","DOIUrl":null,"url":null,"abstract":"Bytecode hardware-translation improves the performance of a Java Virtual Machine (JVM) with small hardware resource and complexity overhead. Instruction folding is a technique to further improve the performance of a JVM by reducing the redundancy in the stack-based instruction execution. However, the variable instruction length of the Java bytecode makes the folding logic complex. In this paper, we propose a folding scheme with reduced hardware complexity and evaluate its performance. For seven benchmark cases, the proposed scheme folded 6.6% to 37.1% of the bytecodes which correspond to 84.2% to 102% of the PicoJava-II's performance.","PeriodicalId":278223,"journal":{"name":"J. Instr. Level Parallelism","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Instr. Level Parallelism","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1128022.1128041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Bytecode hardware-translation improves the performance of a Java Virtual Machine (JVM) with small hardware resource and complexity overhead. Instruction folding is a technique to further improve the performance of a JVM by reducing the redundancy in the stack-based instruction execution. However, the variable instruction length of the Java bytecode makes the folding logic complex. In this paper, we propose a folding scheme with reduced hardware complexity and evaluate its performance. For seven benchmark cases, the proposed scheme folded 6.6% to 37.1% of the bytecodes which correspond to 84.2% to 102% of the PicoJava-II's performance.