Database and System Design for Emerging Storage Technologies

Emerging storage technologies offer an alternative to disk that is
durable and accelerates data access. However, new nonvolatile
memories (NVRAM) such as flash and phase change memory used merely as
a disk replacement fail to achieve their full potentials. Flash's
asymmetric read/write access (i.e., reads execute faster than writes)
opens new opportunities to optimize flash-specific access. Similarly,
NVRAM's low latency persistent accesses enable new designs for high
performance failure-resistant applications.

My dissertation addresses several storage-critical applications that
stand to benefit from new NVRAMs. First, I investigate analytics query
optimization for flash. Second, I examine new opportunities for
durable, recoverable transaction processing with NVRAM. Finally, I
propose a new framework for persistent programming and memory systems
to enable high performance recoverable data structures with NVRAM,
extending memory consistency with persistent semantics to introduce
memory persistency.