{"title":"两个C的故事:收敛和可组合性","authors":"I. Altintas","doi":"10.1109/ipdps49936.2021.00001","DOIUrl":null,"url":null,"abstract":"Cyberinfrastructure is everywhere in diverse forms in service of applications in science, business and society. From IoT to extreme-scale computing data and computing have never been so distributed with the potential for real-time integration into these applications. The common theme to these applications, mostly composed of (big) data-integrated workloads, is their need to run in specialized environments for reasons such as on-demand or 24x7 nature of the tasks they are performing, and difficulties regarding their portability, latency, privacy, and performance optimization. Moreover, in many data-driven scientific applications, there is a need for heterogeneous integration of tasks requiring specialized computing capabilities with traditional high-throughput computing or high-performance computing tasks. Although some key middleware technologies enabled demonstration of standalone heterogeneous applications, such integration requires expertise convergence from a large group of people in very specialized settings. There are still many challenges for streamlined, scalable, repeatable, responsible, and explainable integration of data-integrated applications. Key opportunities for further innovations include intelligent systems and automated workflow management software that can compose and steer dynamic applications that can adapt to changing conditions in a data-driven fashion while integrating many tools to explore, analyze and utilize data. This talk will discuss some examples for data-integrated applications, describe emerging systems that enabled these applications, and overview our recent research to enable composable applications including a convergence application development methodology, intelligent middleware, and workflow composition.","PeriodicalId":372234,"journal":{"name":"2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"338 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Tale of Two C’s: Convergence and Composability\",\"authors\":\"I. Altintas\",\"doi\":\"10.1109/ipdps49936.2021.00001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cyberinfrastructure is everywhere in diverse forms in service of applications in science, business and society. From IoT to extreme-scale computing data and computing have never been so distributed with the potential for real-time integration into these applications. The common theme to these applications, mostly composed of (big) data-integrated workloads, is their need to run in specialized environments for reasons such as on-demand or 24x7 nature of the tasks they are performing, and difficulties regarding their portability, latency, privacy, and performance optimization. Moreover, in many data-driven scientific applications, there is a need for heterogeneous integration of tasks requiring specialized computing capabilities with traditional high-throughput computing or high-performance computing tasks. Although some key middleware technologies enabled demonstration of standalone heterogeneous applications, such integration requires expertise convergence from a large group of people in very specialized settings. There are still many challenges for streamlined, scalable, repeatable, responsible, and explainable integration of data-integrated applications. Key opportunities for further innovations include intelligent systems and automated workflow management software that can compose and steer dynamic applications that can adapt to changing conditions in a data-driven fashion while integrating many tools to explore, analyze and utilize data. This talk will discuss some examples for data-integrated applications, describe emerging systems that enabled these applications, and overview our recent research to enable composable applications including a convergence application development methodology, intelligent middleware, and workflow composition.\",\"PeriodicalId\":372234,\"journal\":{\"name\":\"2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)\",\"volume\":\"338 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ipdps49936.2021.00001\",\"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 International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ipdps49936.2021.00001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cyberinfrastructure is everywhere in diverse forms in service of applications in science, business and society. From IoT to extreme-scale computing data and computing have never been so distributed with the potential for real-time integration into these applications. The common theme to these applications, mostly composed of (big) data-integrated workloads, is their need to run in specialized environments for reasons such as on-demand or 24x7 nature of the tasks they are performing, and difficulties regarding their portability, latency, privacy, and performance optimization. Moreover, in many data-driven scientific applications, there is a need for heterogeneous integration of tasks requiring specialized computing capabilities with traditional high-throughput computing or high-performance computing tasks. Although some key middleware technologies enabled demonstration of standalone heterogeneous applications, such integration requires expertise convergence from a large group of people in very specialized settings. There are still many challenges for streamlined, scalable, repeatable, responsible, and explainable integration of data-integrated applications. Key opportunities for further innovations include intelligent systems and automated workflow management software that can compose and steer dynamic applications that can adapt to changing conditions in a data-driven fashion while integrating many tools to explore, analyze and utilize data. This talk will discuss some examples for data-integrated applications, describe emerging systems that enabled these applications, and overview our recent research to enable composable applications including a convergence application development methodology, intelligent middleware, and workflow composition.