M. Imani, Saransh Gupta, Atl Arredondo, T. Simunic
{"title":"在交叉内存中高效的查询处理","authors":"M. Imani, Saransh Gupta, Atl Arredondo, T. Simunic","doi":"10.1109/ISLPED.2017.8009204","DOIUrl":null,"url":null,"abstract":"Today's computing systems use huge amount of energy and time to process basic queries in database. A large part of it is spent in data movement between the memory and processing cores, owing to the limited cache capacity and memory bandwidth of traditional computers. In this paper, we propose a non-volatile memory-based query accelerator, called NVQuery, which performs several basic query functions in memory including aggregation, prediction, bit-wise operations, as well as exact and nearest distance search queries. NVQuery is implemented on a content addressable memory (CAM) and exploits the analog characteristic of non-volatile memory in order to enable in-memory processing. To implement nearest distance search in memory, we introduce a novel bitline driving scheme to give weights to the indices of the bits during the search operation. Our experimental evaluation shows that, NVQuery can provide 49.3× performance speedup and 32.9× energy savings as compared to running the same query on traditional processor. In addition, compared to the state-of-the-art query accelerators, NVQuery can achieve 26.2× energy-delay product improvement while providing the similar accuracy.","PeriodicalId":385714,"journal":{"name":"2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Efficient query processing in crossbar memory\",\"authors\":\"M. Imani, Saransh Gupta, Atl Arredondo, T. Simunic\",\"doi\":\"10.1109/ISLPED.2017.8009204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today's computing systems use huge amount of energy and time to process basic queries in database. A large part of it is spent in data movement between the memory and processing cores, owing to the limited cache capacity and memory bandwidth of traditional computers. In this paper, we propose a non-volatile memory-based query accelerator, called NVQuery, which performs several basic query functions in memory including aggregation, prediction, bit-wise operations, as well as exact and nearest distance search queries. NVQuery is implemented on a content addressable memory (CAM) and exploits the analog characteristic of non-volatile memory in order to enable in-memory processing. To implement nearest distance search in memory, we introduce a novel bitline driving scheme to give weights to the indices of the bits during the search operation. Our experimental evaluation shows that, NVQuery can provide 49.3× performance speedup and 32.9× energy savings as compared to running the same query on traditional processor. In addition, compared to the state-of-the-art query accelerators, NVQuery can achieve 26.2× energy-delay product improvement while providing the similar accuracy.\",\"PeriodicalId\":385714,\"journal\":{\"name\":\"2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISLPED.2017.8009204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISLPED.2017.8009204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Today's computing systems use huge amount of energy and time to process basic queries in database. A large part of it is spent in data movement between the memory and processing cores, owing to the limited cache capacity and memory bandwidth of traditional computers. In this paper, we propose a non-volatile memory-based query accelerator, called NVQuery, which performs several basic query functions in memory including aggregation, prediction, bit-wise operations, as well as exact and nearest distance search queries. NVQuery is implemented on a content addressable memory (CAM) and exploits the analog characteristic of non-volatile memory in order to enable in-memory processing. To implement nearest distance search in memory, we introduce a novel bitline driving scheme to give weights to the indices of the bits during the search operation. Our experimental evaluation shows that, NVQuery can provide 49.3× performance speedup and 32.9× energy savings as compared to running the same query on traditional processor. In addition, compared to the state-of-the-art query accelerators, NVQuery can achieve 26.2× energy-delay product improvement while providing the similar accuracy.