An area efficient on-chip static IR drop detector/evaluator

Wu, Tung-Yeh; Gharahi, Samaneh; Abraham, Jacob A.

doi:10.1109/iscas.2009.5118186

Cited by 9 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The flow of current throughout the PDN results in a voltage decline in accordance with Ohm's law, whereby the magnitude of voltage reduction is defined as V=I.R. Due to technology scaling, chip functionality is significantly impacted by even the slightest drop in supply voltage [14]. Therefore, IR drop analysis has become an indispensable procedure in chip signoff.…”

Section: The Ir-dropmentioning

confidence: 99%

Machine learning in physical design

Yu,

Li,

Liu

et al. 2023

TNS

View full text Add to dashboard Cite

Machine learning is a highly effective instrument in constructing models that can expeditiously produce accurate prognostications. As the complexity of integrated circuit design continues to increase and process nodes continue to evolve, and physical design faces more challenges from modeling and optimization. To address these challenges, machine learning has been introduced into physical design. Thus, in this paper, we discuss the application of machine learning in physical design, covering topics such as Clock Tree Synthesis (CTS), Placement and Routing, IR-Drop and Static Timing Analysis (STA). The essay explores how machine learning can be used to overcome challenges in these areas, such as reducing peak current and clock skew in CTS, optimizing placement parameters and decision-making, predicting routability and reducing IR-drop effects. This paper also discusses various machine learning techniques (ML), such as reinforcement learning, convolutional neural networks and transfer learning. To conclude, we provide insights into how machine learning can be applied to improve various aspects of physical design.

show abstract

Section: The Ir-dropmentioning

confidence: 99%

Machine learning in physical design

Yu,

Li,

Liu

et al. 2023

TNS

View full text Add to dashboard Cite

show abstract

“…The basic approach is to sample ring oscillator frequencies during normal system operation, then briefly pause the activity of interest, and then immediately sample the frequencies again. The change in frequency represents the size of local IR drop due to switching current [Abuhamdeh et al 2007;Wu et al 2009]:…”

Section: Switching-induced Ir Dropmentioning

confidence: 99%

Low-cost sensing with ring oscillator arrays for healthier reconfigurable systems

Zick

Hayes

2012

ACM Trans. Reconfigurable Technol. Syst.

View full text Add to dashboard Cite

Electronic systems on a chip increasingly suffer from component variation, voltage noise, thermal hotspots, and other subtle physical phenomena. Systems with reconfigurability have unique opportunities for adapting to such effects. Required, however, are low-cost, fine-grained methods for sensing physical parameters. This article presents powerful, novel approaches to online sensing, including methods for designing compact reconfigurable sensors, low-cost threshold detection, and several enhanced measurement procedures. Together, the approaches help enable systems to autonomously uncover a wealth of physical information. A highly efficient counter and improved ring oscillator are introduced, enabling an entire sensor node in just 8 Virtex-5 LUTs. We describe how variations can be measured in delay, temperature, switching-induced IR drop, and leakage-induced IR drop. We demonstrate the proposed approach with an experimental system based on a Virtex-5, instrumented with over 100 sensors at an overhead of only 1.3%. Results from thermally controlled experiments provide some surprising insights and illustrate the utility of the approach. Online sensing can help open the door to physically adaptive computing, including fine-grained power, reliability, and health management schemes for systems on a chip. ACM Reference Format:Zick, K. M. and Hayes, J. P. 2012. Low-cost sensing with ring oscillator arrays for healthier reconfigurable systems.

show abstract

SAM: A comprehensive mechanism for accessing embedded sensors in modern SoCs

Tehranipoor

2014

2014 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)

View full text Add to dashboard Cite

An area efficient on-chip static IR drop detector/evaluator

Cited by 9 publications

References 8 publications

Machine learning in physical design

Machine learning in physical design

Low-cost sensing with ring oscillator arrays for healthier reconfigurable systems

SAM: A comprehensive mechanism for accessing embedded sensors in modern SoCs

Contact Info

Product

Resources

About