SPX: Integrating Persistent Memory in the Cloud

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The massive volume of data and high computing intensity of large-scale applications in the cloud require thousands of machines in big data centers. In addition, there is an increasing demand for faster, energy-efficient, and scalable performance from new data-intensive applications. Unfortunately, as the technology scaling slows down, the semiconductor industry has been facing a major challenge in providing better performance and reducing the power consumption while processing large datasets. To provide better performance and lower costs for cloud applications that manipulate massive data with tight latency constraints, service providers are moving towards in-memory frameworks to store the working data. By exploring the roles of emerging memory technologies, this research project has the potential to improve cloud computing performance. The ideas developed in this research will bridge the gap between architecture, systems, and software engineering community and will enable system support and automated tools for adapting applications in the persistent cloud. The project will eventually enable a holistic "persistent cloud system" such that the cloud applications can be adapted transparently without significant programmers' effort.The goal of this work is to enable a persistent cloud system in a holistic manner across the system stack such that the persistent cloud applications can be adapted in the systems without significant programmers? effort. In order to design a persistent cloud system, this work is to provide full stack support from the applications to hardware through three major research directions that need to be addressed to design a full-stack persistent cloud system, (i) lightweight storage layer support for persistent memory systems, (ii) data monitoring and placement based on application characteristics and trade-offs in NVM, and (iii) automated persistency support at the application-level.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.