Architecting Memory Systems for Emerging Technologies

The advance of traditional dynamic random access memory (DRAM) technology has slowed down, while the capacity and performance needs of memory system have continued to increase. This is a result of increasing data volume from emerging applications, such as machine learning and big data analytics. In addition to such demands, increasing energy consumption is becoming a major constraint on the capabilities of computer systems. As a result, emerging non-volatile memories, for example, Spin Torque Transfer Magnetic RAM (STT-MRAM), and new memory interfaces, for example, High Bandwidth Memory (HBM), have been developed as an alternative. Thus far, most previous studies have retained a DRAM-like memory architecture and management policy. This preserves compatibility but hides the true benefits of those new memory technologies. In this research, we proposed the co-design of memory architectures and their management policies for emerging technologies. First, we introduced a new memory architecture for an STT-MRAM main memory. In particular, we defined a new page mode operation for efficient activation and sensing. By fully exploiting the non-destructive nature of STT- MRAM, our design achieved higher performance, lower energy consumption, and a smaller area than the traditional designs. Second, we developed a cost-effective technique to improve load balancing for HBM memory channels. We showed that the proposed technique was capable of efficiently redistributing memory requests across multiple memory channels to improve the channel utilization, resulting in improved performance.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145988/1/bcoh_1.pd

Architectural Techniques to Enable Reliable and Scalable Memory Systems

High capacity and scalable memory systems play a vital role in enabling our desktops, smartphones, and pervasive technologies like Internet of Things (IoT). Unfortunately, memory systems are becoming increasingly prone to faults. This is because we rely on technology scaling to improve memory density, and at small feature sizes, memory cells tend to break easily. Today, memory reliability is seen as the key impediment towards using high-density devices, adopting new technologies, and even building the next Exascale supercomputer. To ensure even a bare-minimum level of reliability, present-day solutions tend to have high performance, power and area overheads. Ideally, we would like memory systems to remain robust, scalable, and implementable while keeping the overheads to a minimum. This dissertation describes how simple cross-layer architectural techniques can provide orders of magnitude higher reliability and enable seamless scalability for memory systems while incurring negligible overheads.Comment: PhD thesis, Georgia Institute of Technology (May 2017