Adaptive control: stability, convergence, and robustness
Adaptive control: stability, convergence, and robustness
Electromigration reliability enhancement via bus activity distribution
DAC '96 Proceedings of the 33rd annual Design Automation Conference
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Proceedings of the 40th annual Design Automation Conference
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Temperature-aware microarchitecture: Modeling and implementation
ACM Transactions on Architecture and Code Optimization (TACO)
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IEEE Transactions on Dependable and Secure Computing
Circuit Failure Prediction and Its Application to Transistor Aging
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Design techniques for cross-layer resilience
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Adaptive Power Control with Online Model Estimation for Chip Multiprocessors
IEEE Transactions on Parallel and Distributed Systems
Leakage-aware Kalman filter for accurate temperature tracking
IGCC '11 Proceedings of the 2011 International Green Computing Conference and Workshops
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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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There is a growing concern about the increasing vulnerability of future computing systems to errors in the underlying hardware due to manufacturing process variability, exponentially increasing power dissipation and heating, as well as drastic and harsh environments such systems may have to operate in. This research proposes the concept of cross-layer virtual observers and actuations with the aim of achieving improved reliability, performance, thermal stability, and reduced power and energy consumption applied across different layers of system stack. Cross-layer resilient systems, which distribute the responsibility for tolerating errors, device variation, and aging across the system stack, have the potential to provide the resilience required to implement reliable, high-performance, low-power systems in future fabrication processes at significantly lower cost. By using redundant, complementary, or more timely information from multiple sensors at different layers, virtual observers can provide more reliable and accurate information, specific inferences, context, and conditions as well as accurate assessment of the surrounding environment, while identifying malfunction and dangers (e.g thermal overheating or hotspot) in diverse kind of system including emerging Cyber-physical and Multiprocessor system-on-chips (MPSoCs). Virtual observer enabled self-awareness allows a system to observe it's own internal behaviors as well as external systems it interacts with such that it is capable of making judicious decision to optimize performance and other quality of service (QoS) metrics. With the ability to discover potential present action and predict future actions as well as evaluate past actions and behaviors, these computer systems will be capable of adapting their behavior and resources to automatically find the best way to accomplish a given goal despite changing environmental conditions and demands. We demonstrate the effectiveness and applicability of these concepts specifically overcoming the vulnerabilities introduced by faults and process variability using two case studies: one using virtual observer to estimate temperature of unmeasured core and the other to predict the failure rate of the unmeasured core using the estimated temperature using concepts drawn from embedded multiprocessor systems on a single chip (MPSoC) respectively.