A Nanowatt Smart Temperature Sensor for Dynamic Thermal Management

Performance evaluation metrics for ring-oscillator-based temperature sensors on FPGAs: A quality factor

Dynamic thermal management (DTM) techniques of three‐dimensional (3D) Network‐on‐Chips (NoCs) are employed to rescue the chip from thermal difficulties. Reactive routing algorithms, which utilise router throttling technique as a popular DTM, disregard distribution of heat generation of routers resulting in more throttled routers as well as long packet delays in throttled processing elements. This study proposes a reactive routing algorithm for 3D NoCs to (i) dynamically detour packets from hot zones containing throttled routers and (ii) minimise the number of required router throttling in the network. The proposed routing algorithm defines two virtual networks to enhance the path diversity for packets in each layer of 3D NoCs. The selection of diverse paths distributes heat generation to alleviate the thermal variance. The proposed routing algorithm is analysed by turn model to achieve deadlock freedom. Access Noxim simulator is also used to evaluate the performance and the thermal behaviour of the proposed routing algorithm in the variety of conditions. Results show that the proposed routing algorithm improves temperature variance by 9–39% and reduces number of throttled routers by 16–86%, which is achieved at the cost of one extra virtual channel per each physical channel in the XY ‐plane.

Designing temperature-aware microarchitectures for microprocessors at new technologies is becoming a critical requirement due to the exponentially increasing on-chip power density. Extremely high power density, thus the very high on-chip temperature, not only significantly increases the packaging and cooling costs, but also creates tremendous difficulties in chip leakage control and reliability. Being a major contributor to chip transistor budget and die area, caches account for a significant share of the overall processor power consumption, including both dynamic and leakage power. This work analyzes the thermal behavior of subarrays within a conventional data cache when running a set of applications from the SPEC2000 benchmark suite, and proposes two new subarraying schemes, namely, the separated scheme and the interleaved scheme, to improve the thermal behavior of subarrays in terms of more predictable behavior and reduced subarray temperatures. These optimizations can be also combined with dynamic thermal management (DTM) techniques to further improve the efficiency of thermal management. The impact of leakage control on the subarray thermal behavior is also evaluated.

The three-dimensional Network-on-Chip (3D NoC) has been proposed to solve the complex on-chip communication issues. However, the thermal problems become more exacerbated because of the larger power density and the heterogeneous thermal conductance in different silicon layer of 3D NoC. To regulate the system temperature, the Dynamic Thermal Management (DTM) techniques will be triggered when the device is thermal-emergent. However, these kinds of reactive DTM schemes result in significant system performance degradation. In this paper, we propose a proactive DTM with vertical throttling (PDTM-VT) scheme, which is controlled by the distributed Thermal Management Unit (TMU) of each NoC node. Based on the expected temperature resulted from the proposed thermal prediction model, the TMU can early control the temperature of the thermal-emergent device. The experimental results show that the proposed thermal prediction model has less than 0.25% prediction error against actual temperature measurement within 50ms. Besides, the PDTM-VT can reduce 11.84%~23.18% thermal-emergent nodes and improve 0.47%~47.90% network throughput.

Multi-core processors have become an integral part of mainstream high performance computer systems. In parallel, exponentially increasing power density and packaging costs have necessitated system level thermal management solutions for multi-core systems. Dynamic thermal management (DTM) techniques monitor on-chip temperature continuously and typically employs dynamic voltage and frequency scaling (DVFS) to lower the temperature when it exceeds a pre-defined threshold. State-of-the-art DTM solutions for multi-core systems include distributed DVFS (where each core can scale the voltage/frequency individually) and global DVFS (where all cores scale voltage/frequency simultaneously). Distributed DVFS generally offers higher performance than global DVFS, but it is hard to implement and has major scalability issues.

Increasing on-chip temperature in SoC designs has reinforced the need for Dynamic Thermal Management (DTM). The conventional DTM techniques adopted in microprocessors based on DVFS are not suitable in the context of SoCs as they tend to have multiple voltage and frequency domains. In this paper we propose a reactive and a predictive DTM technique using bus arbitration. Based on the thermal profile the bus grants and hence the bus transactions are controlled. This regulates the data flow which reduces the activity in the functional units. The results show that the on-chip temperature can be maintained 3–5°C below the chip temperature threshold with a worst case performance penalty of 5% and a fast response time of at most 5 clock cycles. The hardware cost of implementing the proposed scheme is 3619.7μm2 in 45nm technology, which is less than 0.06% of the chip area. Apart from its simplicity, lower cost and effectiveness, the solution is non-intrusive on the design and scalable to many cores.

With ever-increasing power densities, Dynamic Thermal Management (DTM) techniques have become mainstream in today's systems. An important component of such techniques is the thermal trigger. It has been shown that predictive thermal triggers can outperform reactive ones. In this paper, we present a novel trade-off space of predictive thermal triggers, and compare different approaches proposed in the literature. We argue that run-time adaptability is a crucial parameter of interest. We present a run-time adaptable thermal simulator compatible with arbitrary sensor configuration based on the Neural Network (NN) simulator presented in. We present experimental results on Niagara UltraSPARC T1 chip with real-life benchmark applications. Our results quantitatively establish the effectiveness of the proposed simulator for reducing (by up to 90%), the otherwise unacceptably high errors, that can arise due to expected leakage current variation and design-time thermal modeling errors.

Due to technology advances and complexity of designs, thermal issue is a bottleneck in electronics designs. Various dynamic thermal management techniques have been proposed to address this issue. To effectively apply thermal management techniques, providing an accurate thermal map of chips is highly required. For this goal, a network of temperature sensors ought to be provided. There are various implementations for temperature sensors and network of sensors on Field Programmable Gate Arrays (FPGAs). This work defines and formulates four metrics and criteria, in terms of area, thermal, and power overheads and thermal map accuracy for exploring and evaluating efficiency of different implementations of Ring Oscillator-based Temperature Sensor (ROTS) networks on FPGAs and reports the comparison results for 12 networks with various sensor configurations. According to our metrics and experiments, the sensor that it is composed of NOT gates with open latches and RNS ring counter has lower thermal and power overheads compared to other configurations. Moreover, in this work, a new ROTS is presented that occupies 25% less resources than the most compact temperature sensor. Also, it provides 1.72 times higher sensitivity than the best sensitive ROTS design.

A smart temperature sensor has been realized using a Taiwan Semiconductor Manufacturing Company (TSMC) 0.18- $\mu\mbox{m}$ standard CMOS process. Substrate positive-negative-positive (PNP) transistors are used to extract the temperature information. Using the techniques of dynamic element matching, single-transistor approach, and offset cancellation, the process spread between batches on the transistors becomes the main inaccuracy sources of the temperature sensor. The sensor uses a single-point calibration method that reduces the process spread and simplifies trimming. The temperature sensor can realize an inaccuracy $(\pm 3 \delta)$ within ±0.1 °C in the temperature range from 20 °C to 50 °C after single-point calibration. The average power consumption of the sensor is 16 $\mu\mbox{W}$ at the conversion rate of 10 Hz. These properties allow the use of the temperature sensor in clinical electronic thermometers.

Dynamic Thermal Management (DTM) emerged as a solution to address the reliability challenges with thermal hotspots and unbalanced temperatures. DTM efficiency is highly affected by the accuracy of the temperature information presented to the DTM manager. This work aims to investigate the effect of inaccuracy caused by the deep sub-micron (DSM) noise during the transmission of temperature information to the manager on DTM efficiency. A simulation framework has been developed and results show up to 38% DTM performance degradation and 18% unattended cycles in emergency temperature under DSM noise. The finding highlights the importance of further research in providing reliable on-chip data transmission in DTM application.

Cooling power constitutes a large portion of the total electrical power consumption in data centers. Approximately 25%∼40% of the electricity used within a production data center is consumed by the cooling system. Improving the cooling energy efficiency has attracted a great deal of research attention. Many strategies have been proposed for cutting the data center energy costs. One of the effective strategies for increasing the cooling efficiency is using dynamic thermal management. Another effective strategy is placing cooling devices (heat exchangers) closer to the source of heat. This is the basic design principle of many hybrid cooling systems and liquid cooling systems for data centers. Dynamic thermal management of data centers is a huge challenge, due to the fact that data centers are operated under complex dynamic conditions, even during normal operating conditions. In addition, hybrid cooling systems for data centers introduce additional localized cooling devices, such as in row cooling units and overhead coolers, which significantly increase the complexity of dynamic thermal management. Therefore, it is of paramount importance to characterize the dynamic responses of data centers under variations from different cooling units, such as cooling air flow rate variations. In this study, a detailed computational analysis of an in row cooler based hybrid cooled data center is conducted using a commercially available computational fluid dynamics (CFD) code. A representative CFD model for a raised floor data center with cold aisle-hot aisle arrangement fashion is developed. The hybrid cooling system is designed using perimeter CRAH units and localized in row cooling units. The CRAH unit supplies centralized cooling air to the under floor plenum, and the cooling air enters the cold aisle through perforated tiles. The in row cooling unit is located on the raised floor between the server racks. It supplies the cooling air directly to the cold aisle, and intakes hot air from the back of the racks (hot aisle). Therefore, two different cooling air sources are supplied to the cold aisle, but the ways they are delivered to the cold aisle are different. Several modeling cases are designed to study the transient effects of variations in the flow rates of the two cooling air sources. The server power and the cooling air flow variation combination scenarios are also modeled and studied. The detailed impacts of each modeling case on the rack inlet air temperature and cold aisle air flow distribution are studied. The results presented in this work provide an understanding of the effects of air flow variations on the thermal performance of data centers. The results and corresponding analysis is used for improving the running efficiency of this type of raised floor hybrid data centers using CRAH and IRC units.

This paper presents a thermal sensing and VLSI thermal management scheme using an array of on-chip all-digital delay-line based temperature sensors. A fully digital self-calibration method that removes the temperature sensors' sensitivities to supply voltage and process variations is proposed. The proposed calibration method assigns a unique correction factor, N C to each sensor, making all the sensors' calibrated outputs to be the same at start-up. The correction factor is updated when supply voltage variations are detected. Only one calibration block is required to calibrate multiple delay-line based temperature sensors sequentially. For each additional sensor, only additional registers for storing N C are required. The proposed self-calibrated temperature sensors are demonstrated on an Altera Cyclone IV FPGA based VLSI thermal management system. Runtime thermal profiles for four cores mapped on the Cyclone IV FPGA chip using a hybrid dynamic thermal management (DTM) method are obtained. The percentage of time that each core spent in a particular temperature range is plotted in a histogram. A comparison of different DTM techniques demonstrates that the proposed hybrid DTM reduces the amount of time that the MPSoC spent at higher temperatures and larger thermal gradients, by 10% and 21%, respectively. In addition, the proposed hybrid DTM offers a 10% improvement in the average processing rate (instructions per second) when compared with the conventional global DFS approach.

A standard CMOS optical interconnect is proposed, including an octagonal-annular emitter, a field oxide, metal 1-PSG/BPSG-metal 2 dual waveguide, and an ultra high-sensitivity optical receiver integrated with a fingered P+/N-well/P-sub dual photodiode detector. The optical interconnect is implemented in a Chartered 3.3-V 0.35-μm standard analog CMOS process with two schemes for the research of the substrate noise coupling effect on the optical interconnect performance: with or without a GND-guardring around the emitter. The experiment results show that the optical interconnect can work at 100 kHz, and it is feasible to implement optical interconnects in standard CMOS processes.

Register files are responsible for the majority of thermal emergencies in high performance processors. In this paper, we propose compiler-microarchitecture cooperative techniques to reduce the performance penalty incurred by existing thermal management schemes. Our experiments show that an existing dynamic thermal management (DTM) scheme may result in 47% performance degradation at 45 nm technology node as compared to the ideal case where the processor can sustain any thermal emergency and no DTM is applied. We also evaluate performance degradation of a couple of other DTMs and demonstrate that our cooperative policy can bring down this performance penalty. Our approach shows the consistent effectiveness even with the technology scaling.

in increased on-chip temperature leading to serious concerns about lifetime reliability of micro-processors. Though dynamic thermal management techniques can control peak temperature, they often fail to meet the reliability targets due to the complex interplay between temperature and reliability. In this paper, we propose a dynamic reliability management (DRM) technique that exploits architectural adaptation in conjunction with dynamic voltage/frequency scaling (DVFS). We employ an online Bayesian classifier that can efficiently detect the reliable configurations, while a performance prediction model selects the one with best performance among all the reliable configurations. We later extend our approach to meet both reliability and thermal constraints. Experimental results reveal that our adaptive DRM technique achieves reliability targets while reducing performance overhead by 42.30 % compared to DVFS and 28.68 % compared to DVFS with fetch gating. I.