This third in the series, an interdisciplinary, international workshop, will draw academic and industry leaders from a variety of fields, including computer science, physical sciences, astronomy, applied mathematics, and social sciences, to discuss the state of the art of computing, its applications and, more importantly, it’s future over the next decade. The detailed results of the workshop will be published in the form of a report that will be made available to the public. The previous workshops were held in 2012 (second) and 2003 (first) respectively.
Computing, in its broadest sense, and its scientific, engineering, mathematical, technological, data-related, and social aspects, plays a central role in modern life—revolutionizing research, scholarship, and discovery across all domains of every university, driving innovation in every industry, and profoundly affecting every facet of our society. Various organizations worldwide, including academia and industry, are looking into the future with a bold vision to become more impactful, digital, entrepreneurial, interdisciplinary, and inclusive. A transformative and visionary plan for computing and data curriculum, research, and infrastructure should be essential to this vision. Therefore, the computing activities an organization undertakes must be transformative across the organization’s structure. At universities, it should serve as a pillar for education to prepare students broadly, all majors, all levels, for their future, for research and scholarship, and economic develop- ment, as well as for addressing the new social challenges requiring critical analysis. In academia and the industry, it has to serve as a pillar for research that requires advanced computational tools, visualization, and software. Various organizations have developed a pretty impactful roadmap for computing, while others have not yet fully developed nor implemented such a strategic plan for com- puting. It will require not only the best thinking from our faculty, staff, and administration across the university, but it will also require new ideas, recruits to contribute to the vision, advisory input, new partnerships with academia, national labs, companies, international and community partners, and new funding mechanisms to support it.
Whatever is said about grid computing, it is still a key element of global cyberinfrastructure. The largest scientific computational collaborations, such as LHC, LIGO, CMS, SKA, LOFAR, etc. have deployed and depend on computing infrastructures as their production computing engines. Workshop organizers will drive discussions around the process by which a national, continental, or global grid computing vision might be established. Who are the key stakeholders who need to be involved? How the global community should move towards truly integrating grid elements at all levels, including those of individual investigators, campuses, countries, and regions? How do they move towards integrating networks, clusters, supercomputers, grids, and clouds? How do they provide integrated support and training for users? How do they integrate software and middleware across this variety of systems? How do they provide sufficiently simple abstractions that developers can write applications once, and run them anywhere? How do they unify authentication and accounting? And underlying all of these decisions, what metrics do they seek to maximize in these processes, and how will they measure them? Recent advances in AI are adding impetus to computing revolution. How will ChatGPT change education? ChatGPT, a new Artificial Intelligence tool from OpenAI, is as simple to use as a search engine but can generate almost any text on command in response to a user prompt. Already, users have discovered that it can draw paintings, compose new songs and poems, write essays, and take tests. The tool reportedly scored an 82 on an IQ test, a 1020 on the SAT, and showed itself to have establishment liberal political leanings. Tools like ChatGPT have the potential to change society dramatically – and education, in particular, may never be the same. Is this the time when we need to pull computing, data, domain sciences, and AI in the same direction?
Answering these questions is critically important to many science domains, and while the work- shop organizers don’t think they will actually be able to answer them completely, they believe that this workshop and the subsequent report will make a significant contribution toward establishing a common vision among the community leaders who will have to do the work to unify the field, and among the government agencies who will be asked to fund the activities. Many fields have depended on computational science simulations, and many now are beginning to depend on computationally intensive data analysis. Infrastructure providers seek to build computational systems that support these researchers. Developing the common vision that is needed to support these efforts is the eventual goal of this activity. The meeting will bring international experts representing such distributed scientific infrastructures.
