Software optimization methods for high-performance flash-based storage devices

Abstract

Flash memory has emerged as a strong candidate for a storage device because of its fast random access, low power consumption, small and light form, and shock resistance. However, flash memory has different hardware characteristics compared to the traditional storage device, magnetic disk. In particular, flash memory has uniform access speed, asymmetric read and write performance, and no in-place update. To narrow the hardware gap between flash memory and magnetic disks, flash memory-based storage devices employ special software programs such as Flash Translation Layers (FTLs) and flash file systems. These software programs have been improved to reduce the management overheads of flash memory in terms of both time and energy. However, in spite of these efforts, flash memory does not exhibit full perform gain under existing operating systems, which have been optimized under the assumption that secondary storage is composed of magnetic disks. Therefore, it is necessary to revisit operating system policies and mechanisms, and to revise them for flash memory-based secondary storage. This thesis deals with the software optimization in order to use flash memory as a secondary storage device. First, a new page replacement algorithm, Cost-based LRU (CBLRU) is proposed. The CBLRU analyzes the cost and benefit of two replacement decisions using the information of early evicted clean pages. Based on the precise analysis, this algorithm reduces the number of costly write and erase operations, while avoiding an escalation of cache misses. Second, this research suggests an I/O request handling method that reorders the outstanding requests in the request queue to increase the use of parallel components in flash-based storage devices. In addition, it explores write request mapping methods that also affect the parallel executions of storage components. Simulation results with real workloads show that the I/O performance of the proposed replacement algorithm is enhanced by up to ...