{"title":"ENIAD:面向web级ai大数据服务的可重构近数据处理架构","authors":"Jialiang Zhang, JingJane Li","doi":"10.1109/HCS52781.2021.9567229","DOIUrl":null,"url":null,"abstract":"To meet the surging demands required by AI-enriched Big Data services, cloud vendors are turning toward domain specific accelerators for improved efficiency, scalability and performance. ENIAD, the first end-to-end infrastructure for AI-enriched Big Data serving in real time, accelerates both deep neural network inferencing and billion-scale indexing at the data-center scale. Exploiting near- data computation, reconfigurable computing and rapid/agile hardware deployment flow, ENIAD serves state-of-the-art, online built indexing service with high efficiency at low batch sizes. A high-performance, index (data)-adaptable FPGA soft processor is at the heart of the system and able to serve 10x larger index size with 14x lower latency compared to state-of-the-art CPU and GPU architectures.","PeriodicalId":246531,"journal":{"name":"2021 IEEE Hot Chips 33 Symposium (HCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"ENIAD: A Reconfigurable Near-data Processing Architecture for Web-Scale AI-enriched Big Data Service\",\"authors\":\"Jialiang Zhang, JingJane Li\",\"doi\":\"10.1109/HCS52781.2021.9567229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To meet the surging demands required by AI-enriched Big Data services, cloud vendors are turning toward domain specific accelerators for improved efficiency, scalability and performance. ENIAD, the first end-to-end infrastructure for AI-enriched Big Data serving in real time, accelerates both deep neural network inferencing and billion-scale indexing at the data-center scale. Exploiting near- data computation, reconfigurable computing and rapid/agile hardware deployment flow, ENIAD serves state-of-the-art, online built indexing service with high efficiency at low batch sizes. A high-performance, index (data)-adaptable FPGA soft processor is at the heart of the system and able to serve 10x larger index size with 14x lower latency compared to state-of-the-art CPU and GPU architectures.\",\"PeriodicalId\":246531,\"journal\":{\"name\":\"2021 IEEE Hot Chips 33 Symposium (HCS)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Hot Chips 33 Symposium (HCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HCS52781.2021.9567229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Hot Chips 33 Symposium (HCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HCS52781.2021.9567229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ENIAD: A Reconfigurable Near-data Processing Architecture for Web-Scale AI-enriched Big Data Service
To meet the surging demands required by AI-enriched Big Data services, cloud vendors are turning toward domain specific accelerators for improved efficiency, scalability and performance. ENIAD, the first end-to-end infrastructure for AI-enriched Big Data serving in real time, accelerates both deep neural network inferencing and billion-scale indexing at the data-center scale. Exploiting near- data computation, reconfigurable computing and rapid/agile hardware deployment flow, ENIAD serves state-of-the-art, online built indexing service with high efficiency at low batch sizes. A high-performance, index (data)-adaptable FPGA soft processor is at the heart of the system and able to serve 10x larger index size with 14x lower latency compared to state-of-the-art CPU and GPU architectures.