CAREER: Redefining Memory Virtualization in Clouds

About This Grant

Modern cloud applications, such as those involving artificial intelligence, have become increasingly memory intensive. These applications often require large amounts of memory to achieve high performance. Due to its poor scaling properties, traditional dynamic random-access memory (DRAM) has become a bottleneck and a major infrastructure cost in clouds, where DRAM is virtualized to serve applications running in virtual machines (VMs). To address the DRAM scalability issue, emerging and future memory (EFM) such as Compute Express Link (CXL)-based memory has demonstrated high potential. EFM will encompass heterogeneous memory with multiple memory tiers and distinct characteristics such as cost and volatility. Traditional memory virtualization was primarily designed for virtualizing homogeneous volatile DRAM. It will incur high overhead, lack mechanisms for reducing cloud memory costs, and offer limited usability when used for virtualizing EFM. This CAREER project will redefine memory virtualization for EFM, aiming to significantly reduce cloud memory costs, while offering high performance and usability for modern cloud applications. This project incorporates innovative techniques to minimize virtualized EFM address translation overhead, virtualize slow memory as fast memory in EFM virtualization, and improve VM live migration performance. The success of this CAREER project is expected to enable data centers utilizing current and future cloud systems to achieve high performance, low cost, and high usability, fundamentally changing virtualization management for increasingly large-scale memory systems. Although this project is designed for virtualizing EFM, its concepts, ideas, and techniques can be widely applied to improve various system infrastructures. This project also involves extensive education plans to teach emerging cloud computing technologies to both college and K-12 students by collaborating with local schools. Ultimately, this research will advance next-generation cloud computing by enhancing efficiency, reducing costs, boosting performance, and improving usability, benefiting a broad spectrum of cloud workloads, such as artificial intelligence, databases, and data analytics. 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.