现代计算:愿景与挑战

Sukhpal Singh Gill , Huaming Wu , Panos Patros , Carlo Ottaviani , Priyansh Arora , Victor Casamayor Pujol , David Haunschild , Ajith Kumar Parlikad , Oktay Cetinkaya , Hanan Lutfiyya , Vlado Stankovski , Ruidong Li , Yuemin Ding , Junaid Qadir , Ajith Abraham , Soumya K. Ghosh , Houbing Herbert Song , Rizos Sakellariou , Omer Rana , Joel J.P.C. Rodrigues , Rajkumar Buyya
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摘要

过去六十年间,计算机系统领域经历了重大变革,互联网和计算机商品化等变革性发展对社会产生了深远影响。在技术进步的支撑下,计算机系统远非一成不变,而是不断发展和适应,以覆盖多方面的社会利基。这导致了云计算、雾计算、边缘计算和物联网(IoT)等新模式的出现,为经济和创新提供了新的机遇。然而,这种快速变化带来了复杂的研究挑战,特别是在最大限度地挖掘潜力和增强功能方面。因此,为了保持经济的性能水平,满足日益严格的要求,我们必须了解新模式出现和扩展的驱动因素,以及当代的挑战与过去的挑战有何不同。为此,本文调查并评估了影响计算系统演变的因素,涵盖了既有的系统和架构以及更新的发展,如无服务器计算、量子计算和边缘设备上的人工智能。当我们追溯技术发展轨迹时,就会发现一些趋势,其中包括由于业务和技术限制导致框架迅速过时、向专业化系统和模型发展,以及集中式和分散式控制的不同方法。这篇关于现代计算系统的综合评论展望了该领域研究的未来,强调了关键挑战和新兴趋势,并强调了它们在经济高效地推动技术进步方面的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Modern computing: Vision and challenges

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress.

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