{"title":"研讨会7:HPBDC高性能大数据与云计算","authors":"Xiaoyi Lu, Jianfeng Zhan","doi":"10.1109/IPDPSW50202.2020.00073","DOIUrl":null,"url":null,"abstract":"Managing and processing large volumes of data, or Big Data, and gaining meaningful insights is a significant challenge facing the parallel and distributed computing community. This has significant impact in a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing. As data-gathering technologies and data sources witness an explosion in the amount of input data, it is expected that in the future massive quantities of data in the order of hundreds or thousands of petabytes will need to be processed. Thus, it is critical that data-intensive computing middleware (such as Hadoop, Spark, Flink, etc.) to process such data are diligently designed, with high performance and scalability, in order to meet the growing demands of such Big Data applications.","PeriodicalId":398819,"journal":{"name":"2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)","volume":"3 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Workshop 7: HPBDC High-Performance Big Data and Cloud Computing\",\"authors\":\"Xiaoyi Lu, Jianfeng Zhan\",\"doi\":\"10.1109/IPDPSW50202.2020.00073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Managing and processing large volumes of data, or Big Data, and gaining meaningful insights is a significant challenge facing the parallel and distributed computing community. This has significant impact in a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing. As data-gathering technologies and data sources witness an explosion in the amount of input data, it is expected that in the future massive quantities of data in the order of hundreds or thousands of petabytes will need to be processed. Thus, it is critical that data-intensive computing middleware (such as Hadoop, Spark, Flink, etc.) to process such data are diligently designed, with high performance and scalability, in order to meet the growing demands of such Big Data applications.\",\"PeriodicalId\":398819,\"journal\":{\"name\":\"2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)\",\"volume\":\"3 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPDPSW50202.2020.00073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPSW50202.2020.00073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Workshop 7: HPBDC High-Performance Big Data and Cloud Computing
Managing and processing large volumes of data, or Big Data, and gaining meaningful insights is a significant challenge facing the parallel and distributed computing community. This has significant impact in a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing. As data-gathering technologies and data sources witness an explosion in the amount of input data, it is expected that in the future massive quantities of data in the order of hundreds or thousands of petabytes will need to be processed. Thus, it is critical that data-intensive computing middleware (such as Hadoop, Spark, Flink, etc.) to process such data are diligently designed, with high performance and scalability, in order to meet the growing demands of such Big Data applications.