Time domain dynamic electrothermal macromodeling for thermally aware integrated system design

Time domain identification of reduced dynamic thermal models is pursued with well established macromodeling techniques, providing electrical equivalents to be integrated in standard circuit simulators. Self and mutual thermal impedances of electronic structures, preliminarily evaluated through accurate 3-D FEM thermal simulations, are directly identified with Time Domain Vector Fitting and synthesised in a lumped PSPICE circuit. Two relevant examples of dynamic electrothermal co-simulation are given, the results of which exhibit significant differences with respect to their isothermal counterpart

Lithium-ion Battery Pack Design for Electric Vehicles Using GT-AutoLion: Multi-Physics Simulation and Multi-Criteria Optimization Approach

High specific energy battery systems with improved thermal performance are required for large-scale introduction of electric vehicles (EVs) into the market. This study presents a comprehensive multi-physics simulation and multi-criteria optimization framework for Lithium-ion (Li-ion) battery pack design for EV applications. The battery cells are modeled by electrochemical thermally coupled approach using GT-AutoLion. Multi-objective optimization using genetic algorithm is employed to explore energy and thermally efficient cell design alternatives. The performances of the optimally designed cells are then evaluated under pack environment to account for inhomogeneities in large traction battery packs under realistic working scenarios. It is observed that considering the thermal efficiency of battery cells is crucial for obtaining improved battery pack performance. The integrated framework developed in this work provides systematic pack-aware guidelines for manufacturers already at the initial cell design stage. Moreover, the proposed design optimization methodology is generic, handing over valuable knowledge for future cell and pack designs for various applications

Cross-layer design of thermally-aware 2.5D systems

Over the past decade, CMOS technology scaling has slowed down. To sustain the historic performance improvement predicted by Moore's Law, in the mid-2000s the computing industry moved to using manycore systems and exploiting parallelism. The on-chip power densities of manycore systems, however, continued to increase after the breakdown of Dennard's Scaling. This leads to the `dark silicon' problem, whereby not all cores can operate at the highest frequency or can be turned on simultaneously due to thermal constraints. As a result, we have not been able to take full advantage of the parallelism in manycore systems. One of the 'More than Moore' approaches that is being explored to address this problem is integration of diverse functional components onto a substrate using 2.5D integration technology. 2.5D integration provides opportunities to exploit chiplet placement flexibility to address the dark silicon problem and mitigate the thermal stress of today's high-performance systems. These opportunities can be leveraged to improve the overall performance of the manycore heterogeneous computing systems. Broadly, this thesis aims at designing thermally-aware 2.5D systems. More specifically, to address the dark silicon problem of manycore systems, we first propose a single-layer thermally-aware chiplet organization methodology for homogeneous 2.5D systems. The key idea is to strategically insert spacing between the chiplets of a 2.5D manycore system to lower the operating temperature, and thus reclaim dark silicon by allowing more active cores and/or higher operating frequency under a temperature threshold. We investigate manufacturing cost and thermal behavior of 2.5D systems, then formulate and solve an optimization problem that jointly maximizes performance and minimizes manufacturing cost. We then enhance our methodology by incorporating a cross-layer co-optimization approach. We jointly maximize performance and minimize manufacturing cost and operating temperature across logical, physical, and circuit layers. We propose a novel gas-station link design that enables pipelining in passive interposers. We then extend our thermally-aware optimization methodology for network routing and chiplet placement of heterogeneous 2.5D systems, which consist of central processing unit (CPU) chiplets, graphics processing unit (GPU) chiplets, accelerator chiplets, and/or memory stacks. We jointly minimize the total wirelength and the system temperature. Our enhanced methodology increases the thermal design power budget and thereby improves thermal-constraint performance of the system

Modeling of thermally induced skew variations in clock distribution network

Clock distribution network is sensitive to large thermal gradients on the die as the performance of both clock buffers and interconnects are affected by temperature. A robust clock network design relies on the accurate analysis of clock skew subject to temperature variations. In this work, we address the problem of thermally induced clock skew modeling in nanometer CMOS technologies. The complex thermal behavior of both buffers and interconnects are taken into account. In addition, our characterization of the temperature effect on buffers and interconnects provides valuable insight to designers about the potential impact of thermal variations on clock networks. The use of industrial standard data format in the interface allows our tool to be easily integrated into existing design flow

Understanding the thermal implications of multicore architectures

Multicore architectures are becoming the main design paradigm for current and future processors. The main reason is that multicore designs provide an effective way of overcoming instruction-level parallelism (ILP) limitations by exploiting thread-level parallelism (TLP). In addition, it is a power and complexity-effective way of taking advantage of the huge number of transistors that can be integrated on a chip. On the other hand, today's higher than ever power densities have made temperature one of the main limitations of microprocessor evolution. Thermal management in multicore architectures is a fairly new area. Some works have addressed dynamic thermal management in bi/quad-core architectures. This work provides insight and explores different alternatives for thermal management in multicore architectures with 16 cores. Schemes employing both energy reduction and activity migration are explored and improvements for thread migration schemes are proposed.Peer ReviewedPostprint (published version

Assessment of Design Procedures for Vertical Borehole Heat Exchangers

The use of ground source energy systems is a well-established method to provide low cost heating to buildings, diversify the energy mix and help meeting increasingly stricter sustainability targets. However, considerable uncertainties remain over their efficient design, with several standards, guidelines and manuals being proposed over the last few years. This paper aims at providing insight into the implications to the design of a vertical borehole heat exchanger of the adoption of different design procedures. The hypothetical case of a typical dwelling located in London, UK, is analysed in order to highlight the impact on the final design of the chosen methodology. Moreover, a parametric study using an analytical design procedure was performed to point out the influence of various factors, such as borehole characteristics and thermal properties of the ground. It is shown that there are considerable discrepancies between design methods and that uncertainties in some input parameters, such as the thermal properties of the ground, which for relatively small systems are often selected from tables rather than measured in situ, may have a substantial influence on the length of borehole required

Thermal Recovery of Multi-Limbed Robots with Electric Actuators

The problem of finding thermally minimizing configurations of a humanoid robot to recover its actuators from unsafe thermal states is addressed. A first-order, data-driven, effort based, thermal model of the robots actuators is devised, which is used to predict future thermal states. Given this predictive capability, a map between configurations and future temperatures is formulated to find what configurations, subject to valid contact constraints, can be taken now to minimize future thermal states. Effectively, this approach is a realization of a contact-constrained thermal inverse-kinematics (IK) process. Experimental validation of the proposed approach is performed on the NASA Valkyrie robot hardware