SHF: Small: High-Performance, Energy-Efficient Mobile Web Computing

University Of Texas At Austin, Austin TX

Investigators

Abstract

The Web is continuously transforming society - shaping communications, catalyzing innovations, even shaping thought processes. Over the past decade, the role of the Web has shifted from information retrieval (Web 1.0) to providing a platform for interactive and engaging user experiences (Web 2.0). The Web is once again entering a new age, transcending user engagement to provide intelligent services that integrate multiple devices together. The driving force behind the Web's evolution is the ubiquity of mobile devices-undoubtedly today's most pervasive personal computing platform. The PI will study the crucial conjunction between mobile devices and Web technologies because mobile devices struggle to deliver high computational capability on a battery-power budget. The PI's integrated education plan, involving workshops, new curriculum and cutting-edge Web technologies, will stimulate students from a young age, who come from a diverse range of backgrounds, ethnicities, age groups and skill sets, to pursue academic interests in relevant scientific and technological fields. The exposure will nurture students to embrace careers in science, technology, engineering, and mathematics. The research will lay the groundwork and establish the foundations needed to develop future high-performance and energy-efficient mobile computing systems that can usher in the next generation of Web applications.  The PI will research and investigate optimizations across the layers of the execution stack: at the (1) hardware layer the research will yield insights into new mobile processor architectures that achieve high efficiency by exploiting domain-specific and runtime knowledge; at the (2) runtime software layer, the project will lay the foundations for feedback-driven mechanisms that can dynamically learn to operate the architecture at energy-efficient points without compromising end-user application performance and user experience; at the (3) application layer, the research will discover language hints to empower application writers with awareness of their applications' energy consumption.