The adoption of flash memory in high volume consumer products such as cell phones, tablet computers, digital cameras, and portable music players has driven down flash costs and increased flash quality. This trend is pushing flash memory into new applications, including enterprise computing. In enterprise data centers, servers containing flash-based SolidState Drives (SSDs) are becoming common. However, data center architects prefer to deploy shared storage over direct-attached storage (DAS). Shared storage offers superior manageability, availability, and scalability compared to DAS. For these reasons, system designers want to reap the benefits of direct attached flash memory without decreasing the value of shared storage systems. Our solution is Mercury, a persistent, write-through host-side cache for flash memory. By designing Mercury as a hypervisor cache, we simplify integration and deployment into host environments. This paper presents our experience building a host-side flash cache, an architectural analysis of possible cache attachment points, and a performance evaluation using enterprise workloads. Our results show a 26% improvement in the bandwidth observed by the Jetstress benchmark and a 500% improvement in the I/O rate of an enterprise workload.

We develop a holistic framework for adaptively scheduling asynchronous requests in distributed file systems. The system is holistic in that it manages all resources, including network bandwidth, server I/O, server CPU, and client and server memory utilization. It accelerates, defers, or cancels asynchronous requests in order to improve application-perceived performance directly. We employ congestion pricing via online auctions to coordinate the use of system resources by the file system clients so that they can detect shortages and adapt their resource usage. We implement our modifications in the Congestion-Aware Network File System (CA-NFS), an extension to the ubiquitous network file system (NFS). Our experimental result shows that CA-NFS results in a 20% improvement in execution times when compared with NFS for a variety of workloads.