2024-03-19T05:26:49Zhttps://keep.lib.asu.edu/oai/requestoai:keep.lib.asu.edu:node-1503602021-08-30T18:49:46Zoai_pmh:all150360
https://hdl.handle.net/2286/R.I.14383
2011
99 p
Doctoral Dissertation
Academic theses
Text
eng
Sinha, Saurabh
Cao, Yu
Bakkaloglu, Bertan
Yu, Hongbin
Christen, Jennifer B.
Arizona State University
Partial requirement for: Ph.D., Arizona State University, 2011
Field of study: Electrical engineering
A workload-aware low-power neuromorphic controller for dynamic power and thermal management in VLSI systems is presented. The neuromorphic controller predicts future workload and temperature values based on the past values and CPU performance counters and preemptively regulates supply voltage and frequency. System-level measurements from stateof-the-art commercial microprocessors are used to get workload, temperature and CPU performance counter values. The controller is designed and simulated using circuit-design and synthesis tools. At device-level, on-chip planar inductors suffer from low inductance occupying large chip area. On-chip inductors with integrated magnetic materials are designed, simulated and fabricated to explore performance-efficiency trade offs and explore potential applications such as resonant clocking and on-chip voltage regulation. A system level study is conducted to evaluate the effect of on-chip voltage regulator employing magnetic inductors as the output filter. It is concluded that neuromorphic power controller is beneficial for fine-grained per-core power management in conjunction with on-chip voltage regulators utilizing scaled magnetic inductors.
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Electrical Engineering
DVFS
Magnetic materials
Microprocessors
Neuromorphics
on-chip inductors
power converters
Electronic controllers
Microprocessors
Electric inductors
DC-to-DC converters
Neuromorphic controller for low power systems from devices to circuits