{"title":"建模程序可预测性","authors":"Yiannakis Sazeides, James E. Smith","doi":"10.1145/279358.279371","DOIUrl":null,"url":null,"abstract":"Basic properties of program predictability-for both values and control-are defined and studied. We take the view that program predictability originates at certain points during a program's execution, flows through subsequent instructions, and then ends at other points in the program. These key components of predictability: generation, propagation, and termination; are defined in terms of a model. The model is based on a graph derived from dynamic data dependences and a predictor. Using the SPEC95 benchmarks, we analyze the predictability phenomena both separately and in combination. Examples are provided to illustrate relationships between model-based characteristics and program constructs. It is shown that most predictability derives from program control structure and immediate values, not program input data. Furthermore, most predictability originates from a relatively small number of generate points. The analysis of obtained results suggests a number of ramifications regarding predictability and its use.","PeriodicalId":393075,"journal":{"name":"Proceedings. 25th Annual International Symposium on Computer Architecture (Cat. No.98CB36235)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"68","resultStr":"{\"title\":\"Modeling program predictability\",\"authors\":\"Yiannakis Sazeides, James E. Smith\",\"doi\":\"10.1145/279358.279371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Basic properties of program predictability-for both values and control-are defined and studied. We take the view that program predictability originates at certain points during a program's execution, flows through subsequent instructions, and then ends at other points in the program. These key components of predictability: generation, propagation, and termination; are defined in terms of a model. The model is based on a graph derived from dynamic data dependences and a predictor. Using the SPEC95 benchmarks, we analyze the predictability phenomena both separately and in combination. Examples are provided to illustrate relationships between model-based characteristics and program constructs. It is shown that most predictability derives from program control structure and immediate values, not program input data. Furthermore, most predictability originates from a relatively small number of generate points. The analysis of obtained results suggests a number of ramifications regarding predictability and its use.\",\"PeriodicalId\":393075,\"journal\":{\"name\":\"Proceedings. 25th Annual International Symposium on Computer Architecture (Cat. No.98CB36235)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"68\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 25th Annual International Symposium on Computer Architecture (Cat. No.98CB36235)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/279358.279371\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 25th Annual International Symposium on Computer Architecture (Cat. No.98CB36235)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/279358.279371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Basic properties of program predictability-for both values and control-are defined and studied. We take the view that program predictability originates at certain points during a program's execution, flows through subsequent instructions, and then ends at other points in the program. These key components of predictability: generation, propagation, and termination; are defined in terms of a model. The model is based on a graph derived from dynamic data dependences and a predictor. Using the SPEC95 benchmarks, we analyze the predictability phenomena both separately and in combination. Examples are provided to illustrate relationships between model-based characteristics and program constructs. It is shown that most predictability derives from program control structure and immediate values, not program input data. Furthermore, most predictability originates from a relatively small number of generate points. The analysis of obtained results suggests a number of ramifications regarding predictability and its use.