For many decades, progress in computing hardware has been closely associated with CMOS logic density, performance, and cost. As such, slowdown in 2-D scaling, frequency saturation in CPUs, and increased cost of design and chip fabrication for advanced technology nodes since the early 2000s have led to concerns about how semiconductor technology may evolve in the future. However, the last two decades have also witnessed a parallel development in the application landscape: the advent of big data and consequent rise of data-intensive computing, using techniques such as machine learning. In this article, we advance the idea that data-intensive computing would further cement semiconductor technology as a foundational technology with multidimensional pathways for growth. Continued progress of semiconductor technology in this new context would require the adoption of a system-centric perspective to holistically harness logic, memory, and packaging resources. After examining the performance metrics for data-intensive computing, we present the historical trends for general-purpose graphics processing unit (GPGPU) as a representative data-intensive computing hardware. Thereon, we estimate the values of the key data-intensive computing parameters for the next decade, and our projections may serve as a precursor for a dedicated technology roadmap. By analyzing the compiled data, we identify and discuss specific opportunities and challenges for data-intensive computing hardware technology.

中文翻译：

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数据密集型计算的技术前景

几十年来，计算硬件的进步与 CMOS 逻辑密度、性能和成本密切相关。因此，自 2000 年代初以来，二维缩放速度放缓、CPU 频率饱和以及先进技术节点的设计和芯片制造成本增加，引发了人们对未来半导体技术可能如何发展的担忧。然而，过去二十年也见证了应用领域的并行发展：大数据的出现以及随之而来的使用机器学习等技术的数据密集型计算的兴起。在本文中，我们提出了数据密集型计算将进一步巩固半导体技术作为具有多维增长途径的基础技术的想法。在这种新环境下，半导体技术的持续进步将需要采用以系统为中心的观点来全面利用逻辑、内存和封装资源。在检查了数据密集型计算的性能指标后，我们介绍了通用图形处理单元 (GPGPU) 作为数据密集型计算硬件的历史趋势。据此，我们估计了未来十年关键数据密集型计算参数的值，我们的预测可以作为专门技术路线图的先驱。通过分析编译后的数据，我们确定并讨论了数据密集型计算硬件技术的具体机遇和挑战。在检查了数据密集型计算的性能指标后，我们介绍了通用图形处理单元 (GPGPU) 作为数据密集型计算硬件的历史趋势。据此，我们估计了未来十年关键数据密集型计算参数的值，我们的预测可以作为专门技术路线图的先驱。通过分析编译后的数据，我们确定并讨论了数据密集型计算硬件技术的具体机遇和挑战。在检查了数据密集型计算的性能指标后，我们介绍了通用图形处理单元 (GPGPU) 作为数据密集型计算硬件的历史趋势。据此，我们估计了未来十年关键数据密集型计算参数的值，我们的预测可以作为专门技术路线图的先驱。通过分析编译后的数据，我们确定并讨论了数据密集型计算硬件技术的具体机遇和挑战。我们的预测可以作为专门技术路线图的先驱。通过分析编译后的数据，我们确定并讨论了数据密集型计算硬件技术的具体机遇和挑战。我们的预测可以作为专门技术路线图的先驱。通过分析编译后的数据，我们确定并讨论了数据密集型计算硬件技术的具体机遇和挑战。