Operating Systems, Computer Architectures, File and Storage Systems
Research Summary: The goal of my research focuses on fundamentally improving the performance and scalability of modern virtualization technologies. Today, virtualization technologies form the foundation of cloud and edge computing infrastructures. However, existing virtualization technologies for memory, storage, and even CPU have high performance overhead, especially with increasingly fast hardware. The central theme of my research is to minimize virtualization overhead to its bare minimum in order to close the performance gap between virtualized systems and native systems, without losing isolation or compatibility. I am currently working on providing efficient and scalable virtualization support for emerging software and hardware.
For a list of all my published works, please click here
This paper presents HugeGPT, a software approach to reducing two-dimensional page table walk overhead in virtualized environments. HugeGPT ensures that page tables used in guest systems are physically held in the huge pages formed in the host. HugeGPT can efficiently reduce address translation overhead and improve application performance in virtualized clouds. Read More
This paper identifies host-guest page size mismatch as a main cause of high TLB misses and low performance in virtualized systems. This paper presents Gemini, a VM-hypervisor-based technique to mitigate the issue. Gemini can reduce TLB misses by up to 83% and improve application performance by up to 126%. Read More
This paper proposes DASEC, a task scheduler for edge clouds. DASEC makes application performance less sensitive to the interference between workloads by detecting and protecting critical paths. DASEC can reduce the latencies of edge workloads by 32% ~ 52%. Read More