SHF: Small: Emerging Memory Architectures for Big Memory Applications

计算正在发生巨大变化，特别是对于Facebook、谷歌和亚马逊等基于云的服务提供商。 在线服务应用，如社交网络和搜索，对处理器存储器系统提出了独特的要求。 特别是，这些“大内存”应用程序的工作数据大小超过了计算机设计研究中通常使用的工作负载中的工作数据大小几个数量级。 结果，这些应用对处理器存储器系统施加不同的压力。 同时，诸如相变存储器（PCM）、自旋转移矩随机存取存储器（STT-RAM）和忆阻器的新的非易失性存储器（NVM）技术正在出现，以用作传统动态RAM（DRAM）主存储器的替代或增强。 这些新的存储器技术承诺更高的容量和快速访问时间沿着与非易失性（数据保留时，电源关闭）。 因此，它们有可能弥合当前处理器存储器系统在数据容量和速度要求方面的差距，从而产生新的使用模式，例如存储类存储器或组合的主存储器和存储实现。 这些趋势共同支持新的存储器系统架构，旨在应对大存储器应用的挑战，利用新的存储器技术以及传统DRAM和新兴工艺技术（如3-D芯片堆叠）。这项研究将根据未来更大的非易失性存储器更接近处理器的可用性，大内存应用程序的特点。 它将研究这些应用程序对新兴的存储器架构的组织，层次结构和其他结构和管理问题的影响。 特别是，本研究集中在以下方面的发展：1）大存储器应用的存储器体系结构，利用新兴技术，如3-D管芯堆叠和新的字节可寻址的密集非易失性存储器; 2）深入推测大存储器应用的指令和数据预取器; 3）高速缓存策略，其主动管理存储器系统中的性能、功率和可靠性，以用于利用NVM的未来大存储器应用; 4）新的存储器转换微架构，以满足大存储器应用和存储级主存储器的需求;以及5）服务质量策略，用于基于将来的使用，混合，以及由DRAM和新的NVM技术组成的复合存储器系统。 这项研究的教育影响将包括培养研究生和本科生有价值的研究技能，同时推进计算机体系结构和分布式系统的最新技术，为技术劳动力做出贡献。

Computing is changing dramatically, particularly for cloud-based service providers such as Facebook, Google, and Amazon. On-line service applications, such as social networking and search, place unique demands on processor memory systems. In particular, these "big-memory" applications have working data sizes several orders of magnitude beyond those found in the workloads typically used in computer design research. As a result, these applications place different stresses on processor memory systems. Simultaneously, new, non-volatile memory (NVM) technologies such as Phase Change Memory (PCM), spin-transfer torque random access memory (STT-RAM), and memristors are emerging for use as a replacement for or augmentation to traditional dynamic RAM (DRAM) main memory. These new memory technologies promise higher capacities and fast access times along with non-volatility (data retention when the power is off). As a result, they have the potential to bridge the gaps in current processor memory systems for both data capacity and speed requirements, leading to new usage models, such as storage class memories or combined main memory and storage implementations. These trends together argue for new memory systems architectures, designed for the challenges of big-memory applications, leveraging new memory technologies together with traditional DRAM and emerging process techniques such as 3-D die stacking. This research will characterize big-memory applications in light of future availability of much larger and nonvolatile memories closer to the processor. It will study the implications of these applications on emerging memory architectures in terms of organization, hierarchies, and other structural and management questions. In particular, this research focuses on the development of the following: 1) Memory architectures for big memory applications, leveraging emerging technologies, such as 3-D die stacking and new, byte-addressable, dense non-volatile memories; 2) Deeply speculating instruction and data prefetchers for big-memory applications; 3) Cache policies that proactively manage performance, power, and reliability in memory systems for future big memory applications utilizing NVM; 4) New memory translation microarchitectures to meet the needs of big-memory applications and storage-class main memories; and 5) Quality-of-service policies to manage memory placement based upon usage in future, hybrid, and composite memory systems composed of DRAM and new NVM technologies. The educational impact of this research will include training graduate and undergraduate students with valuable research skills while advancing the state of the art in computer architecture and distributed systems, contributing to the technology workforce.