Mission-critical systems are those imperative systems whose failures can result in catastrophic consequences. Traditional techniques, such as manual investigation and testing, cannot ensure the absence of errors and security vulnerabilities within these systems. This dissertation leverages formal methods to comprehensively examine several mission-critical systems and their essential components. For each...
The speed of the storage device has long lagged behind the computation speed of processors.As a result, the I/O performance of storage systems in a supercomputer fails to keep up with its computational power.
This gap continues to widen in modern supercomputers.
On future exascale supercomputers, this issue can worsen...
Machine learning is seeping into every fabric in various practical domains such as autonomous driving, wearable computing, and smart buildings. However, in the actual development and integration, especially when the learning-based components are frequently included as components of large complex systems where the physical instances can be included as interactable...
Machine learning-based techniques have shown great promises in perception, prediction, planning, and general decision-making for improving task performance of autonomous driving. Connectivity technology has also presented great potentials in improving the safety and efficiency of transportation systems by providing information beyond the perception and prediction capabilities of individual vehicles. However,...
The speed of the storage device has long lagged behind the computation speed of processors.As a result, the I/O performance of storage systems in a supercomputer fails to keep up with its computational power.
This gap continues to widen in modern supercomputers.
On future exascale supercomputers, this issue can worsen...
Memory management and address translation need significant optimizations in order to not behindrances in the near future. Currently, plenty of work has started to address issues within the
current abstraction of the hardware-software codesign of paging. I argue that a new abstraction
is needed in order to properly address this...
With growing system complexity and closer cyber-physical interaction, there are stronger needs for cyber-physical systems to adapt to the dynamic environment and improve their runtime performance. However, especially for safety-critical systems, the ability of such adaptation and improvement is often restricted by multiple factors, such as limited resources, stringent timing...
Computer systems supported by photonic interconnects and photonic memory devices can reach performance and energy efficiency levels unattainable through purely electronic means across scales, from processor chips to the data center. However, the promised benefits cannot be realized through a simple replacement process; to reach their full potential, several aspects...
With the rapid advancement of machine learning techniques (in particular deep neural networks), computer vision applications have shown great promises in a variety of domains for intelligent cyber-physical systems (CPSs), such as autonomous driving, medical imaging, and vision-based robotic systems. However, while many vision applications provide great on-paper performance, their...
Recent developments in deep learning have led to breakthroughs in rendering novel views from sparse input views of a scene.While the accuracy of these algorithms has improved dramatically, it has come at a huge computational cost.
While developments in graphics hardware have ameliorated some of the computational burdens, deep learning-based...