Fine grained, direct access file system support for storage class memory

- We propose a file system-independent block device interface for SCM, which provides backward compatibility and transparently supports the integration of SCM in current computer systems.
- We bypass traditional disk caches to allow fast direct I/O access to SCM, so that secondary storage can be accessed identically as main memory.
- We propose a new hybrid CPU mode for the DRAM-SCM architecture and introduce two new privileged instructions to provide fine-grained, physical access to SCM.

New storage class memory (SCM) technologies, such as phase change memory (PCM) and memristors, are not only byte-addressable like DRAM but also non-volatile like traditional hard disk drives. SCM modules can be placed side-by-side with DRAM on the memory bus, available to memory instructions issued by the CPU. This shift thus engenders a new “DRAM-SCM” storage architecture, which promises near-DRAM secondary storage access speed at several orders of magnitude faster than magnetic disk or flash memory. Utilizing SCM as a secondary storage device will have a profound impact on memory hierarchy design, requiring new architectural and operating system support.In this paper, we adopt PCM in the DRAM-SCM storage architecture and present BSS to provide file system-independent Block device Support for Storage class memory. To ensure backward compatibility and high performance, BSS provides a block device interface found in traditional hard disk drives and allows existing file systems to be built on top of itself without any modifications. BSS is designed to directly access the PCM through memory instructions and bypass traditional disk caches that are intended to reduce seek time.The DRAM-SCM architecture and BSS are prototyped in QEMU and the Linux kernel, respectively. Validation using benchmarks reveals that both work together well to exploit significant advantages of SCM. Compared to traditional hard disk drives, our approach boosts the write/read performance by up to 204x for large files and achieves comparable performance for small ones.