Simulation, Validation and FPGA Implementation of a Ring Oscillator Sensor for Thermal Management and Monitoring

Oukaira, Aziz; Ettahri, Ouafaa; Tabaa, Mohamed; Taheri, Shamsodin; Lakhssassi, Ahmed

doi:10.1016/j.procs.2019.08.015

Cited by 13 publications

(5 citation statements)

References 11 publications

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“…Now we can calculate the temperature gradient along a known distance as given by [37] and shown in Equation (6). For more details about GDS, please refer to [34,35,37].…”

Section: Description Of the Gds Techniquementioning

confidence: 99%

“…The GDS method is based on the detection of isotherms using two cells, and it has been successfully applied in [34,35] to detect a single heat source in the IC. From a theoretical point of view, the authors do not discuss the influence of parameters H and R on the accuracy of the method.…”

Section: Description Of the Gds Techniquementioning

confidence: 99%

“…Moreover, the proposed approach can only find the right location when the workload is fixed, which is not practical. In [34,35], the gradient direction sensor (GDS) technique was used to detect overheating spots on FPGAs; however, the authors did not address the problem of multiple overheating spots.…”

Section: Introductionmentioning

confidence: 99%

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Accurate On-Chip Thermal Peak Detection Based on Heuristic Algorithms and Embedded Temperature Sensors

et al. 2023

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The reliability and lifetime of systems-on-chip (SoCs) are being seriously threatened by thermal issues. In modern SoCs, dynamic thermal management (DTM) uses the thermal data captured by thermal sensors to constantly track the hot spots and thermal peak locations in real time. Estimating peak temperatures and the location of these peaks can play a crucial role for DTM systems, as temperature underestimation can cause SoCs to fail and have shortened lifetime. In this paper, a novel sensor allocation algorithm (called thermal gradient tracker, TGT), based on the recursive elimination of regions that likely do not contain any thermal peaks, is proposed for determining regions that potentially contain thermal peaks. Then, based on an empirical source temperature detection technique called GDS (gradient direction sensor), a hybrid algorithm for detecting the position and temperature of thermal peaks is also proposed to increase the accuracy of temperature sensing while trying to keep the number of thermal sensors to a minimum. The essential parameters, H and R, of the GDS technique are determined using an automated search algorithm based on simulated annealing. The proposed algorithm has been applied in a system-on-chip (SoC) in which four heat sources are present, and for temperatures ranging between 45 °C and 115 °C, in a chip area equal to 25 mm2. The simulation results show that our proposed sensor allocation scheme can detect on-chip peaks with a maximum error of 1.48 °C and an average maximum error of 0.49 °C by using 15 thermal sensors.

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“…Now we can calculate the temperature gradient along a known distance as given by [37] and shown in Equation (6). For more details about GDS, please refer to [34,35,37].…”

Section: Description Of the Gds Techniquementioning

confidence: 99%

Section: Description Of the Gds Techniquementioning

confidence: 99%

See 1 more Smart Citation

Accurate On-Chip Thermal Peak Detection Based on Heuristic Algorithms and Embedded Temperature Sensors

et al. 2023

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“…The evaluation of thermal performance in electronic systems often relies on simulation techniques supported by specialized preprocessing and postprocessing tools. Finite Element Method (FEM) solvers are extensively utilized for heat transfer analysis [39][40][41]. Figure 10 depicts the temperature outcomes obtained from the model without CCLC.…”

Section: Heat Analysis Of Sips Based On Cclcmentioning

confidence: 99%

Advanced Thermal Control Using Chip Cooling Laminate Chip (CCLC) with Finite Element Method for System-in-Package (SiP) Technology

et al. 2023

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This paper introduces a novel approach to address thermal management challenges in system-in-package (SiP) technology, which is a significant concern in various advanced technologies. The main objective is to assess the electrical and thermal performance of the SiP model by utilizing Chip Cooling Laminate Chip (CCLC) technology. To achieve this, we employed finite element method (FEM) analysis using COMSOL Multiphysics® and MATLAB® to compare the results of electrical and thermal SiP models with and without CCLC technology. The numerical simulations revealed that, as opposed to the traditional model, the temperature variation decreased significantly with a uniform temperature distribution when employing the CCLC technology. Additionally, the thermal conduction performance of the packaging system using CCLC demonstrated remarkable reliability and resolution with cost-effective micro-devices, particularly in micro-medicine applications. The analysis of the electrical and thermal models reported a maximum error between them of 1.15 ∘C.

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“…In [ 22 , 23 ], a method for dynamically inserting, operating, and eliminating thermal sensors of FPGA-based systems is proposed. In this paper, we present an integrated peak detection algorithm for thermal monitoring of silicon arrays.…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Thermal Monitoring System Intended for Embedded Sensors Interfaces

Ettahri

Oukaira

Ali

et al. 2020

Sensors

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This paper proposes a real-time thermal monitoring method using embedded integrated sensor interfaces dedicated to industrial integrated system applications. Industrial sensor interfaces are complex systems that involve analog and mixed signals, where several parameters can influence their performance. These include the presence of heat sources near sensitive integrated circuits, and various heat transfer phenomena need to be considered. This creates a need for real-time thermal monitoring and management. Indeed, the control of transient temperature gradients or temperature differential variations as well as the prediction of possible induced thermal shocks and stress at early design phases of advanced integrated circuits and systems are essential. This paper addresses the growing requirements of microelectronics applications in several areas that experience fast variations in high-power density and thermal gradient differences caused by the implementation of different systems on the same chip, such as the new-generation 5G circuits. To mitigate adverse thermal effects, a real-time prediction algorithm is proposed and validated using the MCUXpresso tool applied to a Freescale embedded sensor board to monitor and predict its temperature profile in real time by programming the embedded sensor into the FRDM-KL26Z board. Based on discrete temperature measurements, the embedded system is used to predict, in advance, overheating situations in the embedded integrated circuit (IC). These results confirm the peak detection capability of the proposed algorithm that satisfactorily predicts thermal peaks in the FRDM-KL26Z board as modeled with a finite element thermal analysis tool (the Numerical Integrated elements for System Analysis (NISA) tool), to gauge the level of local thermomechanical stresses that may be induced. In this paper, the FPGA implementation and comparison measurements are also presented. This work provides a solution to the thermal stresses and local system overheating that have been a major concern for integrated sensor interface designers when designing integrated circuits in various high-performance technologies or harsh environments.

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Simulation, Validation and FPGA Implementation of a Ring Oscillator Sensor for Thermal Management and Monitoring

Cited by 13 publications

References 11 publications

Accurate On-Chip Thermal Peak Detection Based on Heuristic Algorithms and Embedded Temperature Sensors

Accurate On-Chip Thermal Peak Detection Based on Heuristic Algorithms and Embedded Temperature Sensors

Advanced Thermal Control Using Chip Cooling Laminate Chip (CCLC) with Finite Element Method for System-in-Package (SiP) Technology

A Real-Time Thermal Monitoring System Intended for Embedded Sensors Interfaces

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