Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3363828
Michela Taufer, Heberth Martinez, Jakob Luettgau, Lauren Whitnah, Giorgio Scorzelli, Pania Newell, Aashish Panta, Peer-Timo Bremer, Douglas Fils, Christine R. Kirkpatrick, Valerio Pascucci
This perspective article presents the vision of combining findable, accessible, interoperable, and reusable (FAIR) Digital Objects with the National Science Data Fabric (NSDF) to enhance data accessibility, scientific discovery, and education. Integrating FAIR Digital Objects into the NSDF overcomes data access barriers and facilitates the extraction of machine-actionable metadata in alignment with FAIR principles. The article discusses examples of climate simulations and materials science workflows and establishes the groundwork for a dataflow design that prioritizes inclusivity, web-centricity, and a network-first approach to democratize data access and create opportunities for research and collaboration in the scientific community.
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Pub Date : 2024-04-18DOI: 10.1109/mcse.2023.3329330
Anshu Dubey, Tal Ben-Nun, Bradford L. Chamberlain, Bronis R. de Supinski, Damian Rouson
Computing at large scales has become extremely challenging due to increasing heterogeneity in both hardware and software. More and more scientific workflows must tackle a range of scales and use machine learning and AI intertwined with more traditional numerical modeling methods, placing more demands on computational platforms. These constraints indicate a need to fundamentally rethink the way computational science is done and the tools that are needed to enable these complex workflows. The current set of C++-based solutions may not suffice, and relying exclusively upon C++ may not be the best option, especially because several newer languages and boutique solutions offer more robust design features to tackle the challenges of heterogeneity. In June 2023, we held a mini symposium that explored the use of newer languages and heterogeneity solutions that are not tied to C++ and that offer options beyond template metaprogramming and Parallel. For for performance and portability. We describe some of the presentations and discussion from the mini symposium in this article.
由于硬件和软件的异质性不断增加，大规模计算变得极具挑战性。越来越多的科学工作流程必须处理各种规模的问题，并将机器学习和人工智能与更传统的数值建模方法结合起来使用，这对计算平台提出了更高的要求。这些制约因素表明，有必要从根本上重新思考计算科学的工作方式以及实现这些复杂工作流程所需的工具。目前基于 C++ 的一系列解决方案可能无法满足需要，而完全依赖 C++ 可能也不是最佳选择，特别是因为一些更新的语言和精品解决方案提供了更强大的设计功能，可以应对异构性的挑战。2023 年 6 月，我们举办了一次小型研讨会，探讨了如何使用更新的语言和异构性解决方案，这些语言和解决方案与 C++ 无关，而且提供了模板元编程和并行之外的选择。对于性能和可移植性。我们将在本文中介绍小型研讨会的部分演讲和讨论内容。
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Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3378620
{"title":"IEEE Computer Society Career Center","authors":"","doi":"10.1109/mcse.2024.3378620","DOIUrl":"https://doi.org/10.1109/mcse.2024.3378620","url":null,"abstract":"","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3378616
{"title":"IEEE Computer Society Information","authors":"","doi":"10.1109/mcse.2024.3378616","DOIUrl":"https://doi.org/10.1109/mcse.2024.3378616","url":null,"abstract":"","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3378624
{"title":"IEEE Computer Society Has You Covered!","authors":"","doi":"10.1109/mcse.2024.3378624","DOIUrl":"https://doi.org/10.1109/mcse.2024.3378624","url":null,"abstract":"","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3378627
{"title":"Get Published in the New IEEE Transactions on Privacy","authors":"","doi":"10.1109/mcse.2024.3378627","DOIUrl":"https://doi.org/10.1109/mcse.2024.3378627","url":null,"abstract":"","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3352451
Tapio Schneider, Ilkay Altintas, Daniel Atkins
AI-aided design of experiments and observations, together with robotic instrumentation and automated learning from data, has the potential to transform science and propel it forward with unprecedented speed.
{"title":"Accelerating Scientific Discovery With AI-Aided Automation","authors":"Tapio Schneider, Ilkay Altintas, Daniel Atkins","doi":"10.1109/mcse.2024.3352451","DOIUrl":"https://doi.org/10.1109/mcse.2024.3352451","url":null,"abstract":"AI-aided design of experiments and observations, together with robotic instrumentation and automated learning from data, has the potential to transform science and propel it forward with unprecedented speed.","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1109/mcse.2024.3378626
{"title":"IEEE Computer Society - Call for Papers","authors":"","doi":"10.1109/mcse.2024.3378626","DOIUrl":"https://doi.org/10.1109/mcse.2024.3378626","url":null,"abstract":"","PeriodicalId":10553,"journal":{"name":"Computing in Science & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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