CAREER: Advanced System-Level Support for Hybrid Multi-Tasking Computing

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This work investigates new methods to provide operating system support for hybrid computing systems. A hybrid system includes one or more instruction-based processors coupled with accelerator logic that exploits application parallelism to increase performance. The work focuses on accelerators constructed from reconfigurable hardware, such as field-programmable gate array (FPGA) logic. Reconfigurable hardware also reduces energy by directly implementing the needed computation instead of fetching, decoding, and executing instructions. Future work will extend the investigation to other types of accelerators, such as general-purpose graphics processing units (GPGPUs). In particular, the research studies the interdependence of accelerator management and software thread scheduling in multi-tasking hybrid systems, and proposes integrating these two system-level functions to increase the overall performance and energy-efficiency. This will encourage industry to further embrace hybrid computing in the development of new products, and thus, enable more capable and energy-efficient mobile devices; quiet multi-function household information appliances; portable medical devices; and more flexible, capable, and robust infrastructure systems in transportation, healthcare, and other key industries. This project also targets to improve teaching, learning, and diversity in Computer Engineering. Activities include developing curriculum and teaching aids, outreach activities, undergraduate research, and involvement in education-related committees. As a part of this project, participants will create new instructional materials for Computer Engineering topics at a variety of levels of understanding.