Robert Gifford’s breakthroughs in real-time system safety
The doctoral candidate with the Penn Research in Embedded Computing and Integrated Systems Engineering Center at Penn Engineering is revolutionizing real-time systems on modern multicore computers.
Robert Gifford is at the forefront of revolutionizing real-time systems on modern multicore computers. The doctoral candidate with the Penn Research in Embedded Computing and Integrated Systems Engineering (PRECISE) Center at the School of Engineering and Applied Science works with Linh Thi Xuan Phan and Andreas Haeberlen, associate professor and professor in the Department of Computer and Information Science, respectively, to develop solutions that could significantly enhance the safety and predictability of systems that power critical applications, from aerospace to medical devices.
(From left) Penn Engineering’s Andreas Haeberlen, Robert Gifford, Linh Thi Xuan Phan, and Insup Lee.
(Image: Courtesy of Penn Engineering)
Real-time systems, like those in pacemakers or flight control systems, must respond to inputs within strict timeframes to ensure safety. Traditionally, these systems are built using single-core processors, where tasks are isolated and executed within predictable amounts of time. However, as multi-core processors have become common, new challenges have emerged because of cross-core resource sharing, which can add unpredictable delays. Gifford’s research is developing new, innovative ways to allocate these shared resources on multi-core systems, so that critical tasks can remain predictable and safe while fully leveraging the power of modern hardware.
Gifford’s first major contribution is dynamic resource allocation (DNA), a groundbreaking technique for distributing resources in soft real-time multicore systems. Before DNA, these systems typically used a static approach—shared resources like CPU, cache and memory bandwidth were allocated to computational tasks only once, using their worst-case requirements, even if any computational tasks’ actual requirements varied significantly during different phases.
Gifford and his team introduced a dynamic allocation method that can redistribute resources on the fly, based on the current demands of each task. This approach led to a significant improvement in efficiency, allowing the system to safely run more tasks simultaneously.
Building on the success of DNA, Gifford broadened his focus to multimode systems with Omni, which combines a novel algorithm and a test for scheduling tasks. Multimode systems switch between different operational modes—like an autonomous vehicle adapting its behavior when moving from a highway to a crowded urban street. Each mode can have different timing requirements, and transitions between modes can be challenging to schedule safely.
The culmination of Gifford’s work to date is DECNTR, which takes the ideas from Omni even further by integrating control theory into the resource allocation process. DECNTR allows for the safe delay of task deadlines during mode transitions, enabling far better resource allocations without the tradeoffs that Omni requires. By co-designing the system’s control and scheduling mechanisms, DECNTR offers a more holistic and effective solution to the challenges of multicore real-time systems.
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