近似计算,有效的信息处理

Swagath Venkataramani, S. Chakradhar, K. Roy, A. Raghunathan
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引用次数: 2

摘要

这一差距一方面是由于技术扩展带来的好处减少,另一方面是由于未来工作负载对计算需求的预计增长,这导致需要新的计算效率来源。幸运的是,推动整个计算范围需求的工作负载也提供了新的机会。在服务器端,对计算的需求是由组织、分析、解释和搜索爆炸式数字数据的需求驱动的。在移动设备和深度嵌入式系统中,更丰富的媒体的创造和消费,以及与用户和环境进行更自然、更智能的交互的需求,是推动大部分计算需求的趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximate computing for efficient information processing
The gap created due to diminishing benefits from technology scaling on the one hand, and projected growth in computing demand from future workloads on the other, leads to a need for new sources of computing efficiency. Fortunately, the workloads that are driving demand across the computing spectrum also present new opportunities. At the server end, the demand for computing is driven by the need to organize, analyze, interpret, and search through exploding digital data. In mobile devices and deeply embedded systems, the creation and consumption of richer media and the need to interact more naturally and intelligently with users and the environment are trends that drive much of the computing demand.
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