Towards Building Energy Efficient, Reliable, and Scalable NAND Flash Based Storage Systems

NAND Flash (or Flash) is the most popular solid-state non-volatile memory technology used today. As the memory technolgy scales and costs reduce, flash has replaced Hard Disk Drives (HDDs) to become the de facto storage technology. However, flash memory scaling has adversely impacted the energy efficiency and reliability of flash based storage systems. While smaller flash geometries have driven storage system capacity to approach petabyte limit, performance of such high capacity storage systems is also a major limitation. In this dissertation, we address the power, reliability, and scalability challenges of NAND flash based storage systems by modeling key metrics, evaluating the tradeoffs between these metrics and exploring the design space to build application optimal storage systems.

To address the power efficiency of flash memory, this dissertation presents FlashPower, a detailed analytical power model for flash memory chips. Using FlashPower, this dissertation provides detailed insights on how various parameters affect flash energy dissipation and proposes several architecture level optimizations to reduce memory power consumption.

To address the reliability challenges facing modern flash memory systems, this dissertation presents FENCE, a transistor-level model to study various failure mechanisms that affect flash memories and analyze the trade-off between flash geometries and operation conditions like temperature and usage frequency. Using FENCE, this dissertation proposes both firmware level algorithms to enable reliable and application optimal storage systems.

Finally, to address scalability limitations of flash based high capacity Solid State Disks (SSDs), this dissertation evaluates the bottlenecks faced by conventional SSD architectures to show that the size of the indirection tables and the processing power available in such architectures severely limit performance as SSD capacity approaches the petabyte limit. This dissertation proposes FScale, a scalable, distributed processor based SSD architecture that can match the scaling rate of NAND flash memory and enable high performance petabyte scale SSDs.