Towards Predictable Real-Time Performance on Multi-Core Platforms

Abstract

Cyber-physical systems (CPS) integrate sensing, computing, communication and actuation capabilities to monitor and control operations in the physical environment. A key requirement of such systems is the need to provide predictable real-time performance: the timing correctness of the system should be analyzable at design time with a quantitative metric and guaranteed at runtime with high assurance. This requirement of predictability is particularly important for safety-critical domains such as automobiles, aerospace, defense, manufacturing and medical devices.The work in this dissertation focuses on the challenges arising from the use of modern multi-core platforms in CPS. Even as of today, multi-core platforms are rarely used in safety-critical applications primarily due to the temporal interference caused by contention on various resources shared among processor cores, such as caches, memory buses, and I/O devices. Such interference is hard to predict and can significantly increase task execution time, e.g., up to 12× on commodity quad-core platforms. To address the problem of ensuring timing predictability on multi-core platforms, we develop novel analytical and systems techniques in this dissertation. Our proposed techniques theoretically bound temporal interference that tasks may suffer from when accessing shared resources. Our techniques also involve software primitives and algorithms for real-time operating systems and hypervisors, which significantly reduce the degree of the temporal interference. Specifically, we tackle the issues of cache and memory contention, locking and synchronization, interrupt handling, and access control for computational accelerators such as general-purpose graphics processing units (GPGPUs), all of which are crucial to achieving predictable real-time performance on a modern multi-core platform. Our solutions are readily applicable to commodity multi-core platforms, and can be used not only for developing new systems but also migrating existing applications from single-core to multi-core platforms. vi This dissertation would have been impossible without the help and support of many people. First and foremost, I would like to thank my advisor, Prof. Raj Rajkumar. I was lucky to work with Raj. His guidance and expertise have made me a better thinker, writer, and researcher. Raj gave me opportunities to participate in exciting projects, demonstrate my research results, and mentor other students, all of which led me to become an independent researcher and to pursue an academic career. I am grateful to the members of my thesis committee, Prof. Onur Mutlu, Prof. Anthony Rowe, and Dr. Shige Wang for their time, effort and inputs in completing this dissertation. Thanks to Onur for his insights on various aspects of my work. I learned a lot from Onur on computer architectures, which was a great asset for my research. Thanks to Anthony for his feedback and advice, even since my very early days at CMU. I enjoyed lively conversations with Anthony and liked to hear his view on cyber-physical...