On-chip Noise Sensors Research Articles

On the Optimal Threshold Voltage Computation of On-Chip Noise Sensors

Runtime noise management systems typically rely on on-chip noise sensors to accurately capture voltage emergencies. As such, the threshold voltage for noise sensors to report emergencies serves as a critical tuning knob between the system failure rate and false alarms. Unfortunately, the problem of optimal threshold voltage computation remains open in literature despite its importance. The problem is further complicated by process variations, which introduce significant variations in load currents and thus in noise across different chips. A uniform noise margin may not work optimally for all the chips. In this paper, we first formulate the problem of minimizing the system alarm rate subject to a given system failure rate constraint. We then put forward a uniform scheme to find an optimal solution for all chips. Compared to a seemingly more intuitive approach which is too conservative, experimental results over a set of industrial designs show an average of 20.6% reduction in system alarm rate under the same system failure rate constraint. We further show that with the help of ${I} _{\mathrm {ddq}}$ measurements during testing which reveal process variation information, it is possible and efficient to compute a per-chip optimal threshold voltage threshold. It further reduces the alarm rate by 12.3% on average compared with uniform threshold approach. To the best of the authors knowledge, this is the first in-depth study on optimal threshold voltage computation for noise sensors. We hope that it shall point out new directions for systematic studies of on-chip noise sensor utilization.

On the Deployment of On-Chip Noise Sensors

Runtime noise management systems can enforce power integrity without significantly increasing design margins. These systems typically respond to on-chip noise sensors to accurately capture voltage emergencies. Unfortunately, it remains an open problem in the literature how to optimally place a given number of noise sensors for best voltage emergency detection, or how to best set the threshold voltage for these sensors. In this paper, we formally define the problem of noise sensor placement along with a novel sensing quality metric to be maximized. We then put forward an efficient algorithm to solve it, which is proven to attain the best result in the class of polynomial complexity approximations. We further solve the problem to minimize the system failure rate subject to a given runtime performance loss (RPL) constraint. Experimental results on a set of industrial power grid designs show that, compared to a simple average-noise based heuristic and two state-of-the-art temperature sensor placement algorithms aimed at recovering the full map or capturing the hot spots at all times, the proposed method on average can reduce the miss rate of voltage emergency detections by 7.4x, 15x, and 6.2x, respectively. The trade-off between the system failure rate and the RPL is also presented. To the best of the authors' knowledge, this is the very first in-depth work on noise sensor deployment.

On-Chip Noise Sensor for Integrated Circuit Susceptibility Investigations

With the growing concerns about electromagnetic compatibility of integrated circuits, the need for accurate prediction tools and models to reduce risks of noncompliance becomes critical for circuit designers. However, an on-chip characterization of noise is still necessary for model validation and design optimization. Although different on-chip measurement solutions have been proposed for emission issue characterization, no on-chip measurement methods have been proposed to address the susceptibility issues. This paper presents an on-chip noise sensor dedicated to the study of circuit susceptibility to electromagnetic interferences. A demonstration of the sensor measurement performances and benefits is proposed through a study of the susceptibility of a digital core to conducted interferences. Sensor measurements ensure a better characterization of actual coupling of interferences within the circuit and a diagnosis of failure origins.