{"title":"一种基于随机启发式的测试向量重排序方法,用于动态降低测试功率","authors":"Sanjoy Mitra, Debaprasad Das","doi":"10.1109/IC3I.2016.7918020","DOIUrl":null,"url":null,"abstract":"With the growth of IC technology, power minimization has become a serious concern for the test engineers. Power consumption in test mode is comparatively higher than in functional mode. This high power consumption during testing may generate too much heat which in turn can spoil the circuit under test. Considering the spectrum of low power testing approaches, reduction in dynamic power is viewed here as a sub-problem and resolved through test vector reordering. In this paper, an Enhanced Ant Colony Optimization (EACO) heuristic is applied to sort out an optimal order of test vectors so that switching activity during testing gets lessened. The simulation on ISCAS 85 bench mark test data set has shown promising power reduction when compared with simple ant colony optimization (ACO) and other relevant heuristic approaches.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A stochastic heuristic based approach to test vector reordering for dynamic test power reduction\",\"authors\":\"Sanjoy Mitra, Debaprasad Das\",\"doi\":\"10.1109/IC3I.2016.7918020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the growth of IC technology, power minimization has become a serious concern for the test engineers. Power consumption in test mode is comparatively higher than in functional mode. This high power consumption during testing may generate too much heat which in turn can spoil the circuit under test. Considering the spectrum of low power testing approaches, reduction in dynamic power is viewed here as a sub-problem and resolved through test vector reordering. In this paper, an Enhanced Ant Colony Optimization (EACO) heuristic is applied to sort out an optimal order of test vectors so that switching activity during testing gets lessened. The simulation on ISCAS 85 bench mark test data set has shown promising power reduction when compared with simple ant colony optimization (ACO) and other relevant heuristic approaches.\",\"PeriodicalId\":305971,\"journal\":{\"name\":\"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3I.2016.7918020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3I.2016.7918020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A stochastic heuristic based approach to test vector reordering for dynamic test power reduction
With the growth of IC technology, power minimization has become a serious concern for the test engineers. Power consumption in test mode is comparatively higher than in functional mode. This high power consumption during testing may generate too much heat which in turn can spoil the circuit under test. Considering the spectrum of low power testing approaches, reduction in dynamic power is viewed here as a sub-problem and resolved through test vector reordering. In this paper, an Enhanced Ant Colony Optimization (EACO) heuristic is applied to sort out an optimal order of test vectors so that switching activity during testing gets lessened. The simulation on ISCAS 85 bench mark test data set has shown promising power reduction when compared with simple ant colony optimization (ACO) and other relevant heuristic approaches.