Transforming memory systems: Optimizing for client value on emerging workloads

K. Nowka
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引用次数: 0

Abstract

Computing systems are increasingly being transformed to better satisfy the demands of cloud computing, Big Data, and deep, sophisticated analytics applications. These applications are driving an explosion in volume of data, acceleration of the rate at which this data must be consumed, and an increase in the diversity of sources of data. Memory system architectures and designs are perhaps most affected by these changes in computing applications. The disruptive trends resulting from these new application spaces lead to significant capacity, power, and cost pressures on computing systems. These trends will lead to changes in traditional memory technologies and memory systems and represent an opportunity of new memory technologies and organizations. Storage class memory is particularly suited to a significant set of these application spaces.
转换内存系统:在新兴工作负载上优化客户端价值
计算系统正在不断转型,以更好地满足云计算、大数据和深度、复杂分析应用的需求。这些应用程序正在推动数据量的爆炸式增长,加速了数据的消耗速度,并增加了数据源的多样性。存储系统架构和设计可能是受这些计算应用程序变化影响最大的。这些新的应用程序空间带来的颠覆性趋势给计算系统带来了巨大的容量、功率和成本压力。这些趋势将导致传统存储技术和存储系统的变化,并代表了新的存储技术和组织的机会。存储类内存特别适合这些应用程序空间中的一组。
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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