Accelerated and Heterogeneous Computing for Robotics
Project Goals and Description:
Extracting full performance from modern computational devices requires effective use of a variety of specialized, heterogeneous processing units and accelerators: CPU cores, GPUs, learning accelerators, etc. Traditional techniques cannot fully utilize such heterogeneous devices. Instead, operating systems must analyze connections between computational tasks to best allocate different tasks to different processing units. In robotics applications, task dependencies further rely on interactions with the physical environment. This project develops novel programming abstractions and scheduling techniques to leverage the capabilities of modern, heterogeneous computing platforms in robotics applications.
Grand Challenge: Engineer the tools of scientific discovery.
- SMT Introduction: https://www.cs.cmu.edu/~15811/papers/smt-intro.pdf
- SMT-LIB Tutorial: https://smtlib.github.io/jSMTLIB/SMTLIBTutorial.pdf
Neil Dantam, email@example.com. Mehmet Belviranli, firstname.lastname@example.org.
Student must be familiar with programming and data structures. Prior experience with programming languages and operating systems is desirable. Necessary Courses: CSCI-262. Desired Courses: CSCI-400 and CSCI-442.
TIME COMMITMENT (HRS/WK)
Student will develop an understanding of heterogeneous computing, robot programming, and operating system scheduling. Student will learn methods and algorithms for scheduling and constraint solving.
Weekly individual meetings with the MURF student and faculty member to discuss progress and provide directed guidance. Weekly lab meetings to discuss the overall project and integration. Assigned graduate student mentor for the MURF student.
PREFERRED STUDENT STATUS