{"title":"The Intelligence Advanced Research Projects Activity Advanced Graph Intelligent Logical Computing Environment Program: Reinventing Computing","authors":"William J. Harrod","doi":"10.1109/mcse.2023.3332321","DOIUrl":null,"url":null,"abstract":"New data-centric architectures optimized for knowledge discovery and analytics are urgently required. This article describes the Intelligence Advanced Research Projects Activity’s Advanced Graph Intelligent Logical Computing Environment program, the first step toward catalyzing a computing revolution by pioneering new hardware and software co-designs tailored for data handling and movement. The goal is to empower transformative applications across all fields through efficient, scalable systems balanced for both data-intensive and compute-intensive workloads. Realizing this vision demands continued research into components, prototypes, and architectural design principles that place priority on the data.","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":"3 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing in Science & Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/mcse.2023.3332321","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
New data-centric architectures optimized for knowledge discovery and analytics are urgently required. This article describes the Intelligence Advanced Research Projects Activity’s Advanced Graph Intelligent Logical Computing Environment program, the first step toward catalyzing a computing revolution by pioneering new hardware and software co-designs tailored for data handling and movement. The goal is to empower transformative applications across all fields through efficient, scalable systems balanced for both data-intensive and compute-intensive workloads. Realizing this vision demands continued research into components, prototypes, and architectural design principles that place priority on the data.
期刊介绍：
Physics, medicine, astronomy -- these and other hard sciences share a common need for efficient algorithms, system software, and computer architecture to address large computational problems. And yet, useful advances in computational techniques that could benefit many researchers are rarely shared. To meet that need, Computing in Science & Engineering presents scientific and computational contributions in a clear and accessible format.
The computational and data-centric problems faced by scientists and engineers transcend disciplines. There is a need to share knowledge of algorithms, software, and architectures, and to transmit lessons-learned to a broad scientific audience. CiSE is a cross-disciplinary, international publication that meets this need by presenting contributions of high interest and educational value from a variety of fields, including—but not limited to—physics, biology, chemistry, and astronomy. CiSE emphasizes innovative applications in advanced computing, simulation, and analytics, among other cutting-edge techniques. CiSE publishes peer-reviewed research articles, and also runs departments spanning news and analyses, topical reviews, tutorials, case studies, and more.
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