CSR: Small: Memory System Optimizations to Enable Fast-Response Mobile Devices at Low Power

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

The past decade has seen a paradigm shift in computing platforms. Emerging handheld devices such as Smartphones and Tablets have become one of the most common devices for computing in everyday use. Energy consumption is one of the prime considerations that influence the development of mobile hand-held devices, as it determines the duration for which the device remains usable on battery power. The usage patterns for devices such as smartphones are quite different from traditional computing devices such as laptops and desktops, and users have a different set of expectation from these handheld mobile devices. For example, mobile devices are expected to be always-on for at-least a day and to start-up and respond quickly. On the other hand, laptop/desktop devices are expected to perform well under heavy use, and the expectations of fast start-up and response are not as stringent. Furthermore, in terms of application usage, mobile systems tends to have burst usage with low-levels of multitasking, while desktop usage involves more continuous long-running programs with high-levels of multitasking. The project seeks to optimize the memory system in mobile devices to enable fast-response time while maintaining low power by levering these usage differences. It consists of a three-pronged approach: First, reducing active memory footprint size by analyzing the usage patterns of mobile users by developing a usage logging program. Second, developing intelligent error correction schemes that can reduce the refresh energy consumed by the memory system without compromising data integrity. Third, reducing the memory power by utilizing emerging Non Volatile Memory (NVM) technologies and developing data partitioning techniques that can keep critical data in NVM. Memory power consumption continues to be one of the main limiter of the battery life of mobile platforms. In additional to the general use as smartphone and tablets, efficient mobile memory system has use in several other application domains such as surveillance, automotive, environment, military, and biomedical. The techniques developed in our proposal will be useful for these domains as well. The infrastructure on usage logging and the usage characterization will foster other studies in the area of mobile memory systems.