Scheduling and Allocation for Embedded Reconfigurable Systems

  • Current/future systems are faced with challenge of processing large data (e.g. from multiple sensors) reliably under real time, and sometimes harsh conditions

  • For autonomous systems, data from cameras, LIDAR, Ultrasonic sensors, WiFi Module, and a host of other sensors need to be processed in real time, reliably.

  • Developing efficient computing solutions for these systems have remained a challenge, mainly due to issues revolving around relaibility and cost.

  • This project Investigates the use of Reconfigurable Hardware (such as FPGAs) for such systems by efficiently managing these multiple tasks on the Reconfigurable Hardware resources to achieve high performance and reliability.

  • The main objectives of the project are:

    • Maximize the fragmentation on Reconfigurable Hardware under real-time conditions

    • Circumvent the large (re)configuration time on such platforms

    • Devolepe high - level tools to minimize the technical skills needed to harness the potentials of the platforms

 

Large Amount of Data to be Processed in Real-Time
Autonomous Vehicle
Robots in Hostile Environment