|Institution:||Texas A&M University|
|Keywords:||Storage Class Memory|
|Full text PDF:||http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11761|
This thesis presents a method for enhancing performance of Storage Class Memory File System (SCMFS) and an implementation of SCMFS on Android platform. It focuses on analyzing performance influencing factors of memory file systems and the differences in implementation of SCMFS on Android and Linux kernels. SCMFS allocates memory pages as file blocks and employs virtual memory addresses as file block addresses. SCMFS utilizes processor's memory management unit and TLB (Translation Lookaside Buffer) during file accesses. TLB is an expensive resource and has a limited number of entries to cache virtual to physical address translations. TLB miss results in expensive page walks through memory page table. Thus TLB misses play an important role in determining SCMFS performance. In this thesis, SCMFS is designed to support both 4KB and 2MB page sizes in order to reduce TLB misses and to avoid significant internal fragmentation. By comparing SCMFS with YAFFS2 and EXT4 using popular benchmarks, both advantages and disadvantages of SCMFS huge-page version and small-page version are revealed. In the second part of this thesis, an implementation of SCMFS on Android platform is presented. At the time of working on this research project, Android kernel was not merged into Linux kernel yet. Two main changes of SCMFS kernel code: memory zoning and inode functions, are made to be compatible with Android kernel. AndroSH, a file system benchmark for SCMFS on Android, is developed based on shell script. Evaluations are made from three perspectives to compare SCMFS with YAFFS2 and EXT4: I/O throughput, user data access latency, and application execution latency. SCMFS shows a performance advantage because of its small instruction footprint and its pre-allocation mechanism. However, the singly linked list used by SCMFS to store subdirectories is less efficient than HTree index used by EXT4. The future work can improve lookup efficiency of SCMFS.