Modeling the Temperature Bias of Power Consumption for Nanometer-Scale CPUs in Application Processors

We introduce and experimentally validate a new macro-level model of the CPU temperature/power relationship within nanometer-scale application processors or system-on-chips. By adopting a holistic view, this model is able to take into account many of the physical effects that occur within such systems. Together with two algorithms described in the paper, our results can be used, for instance by engineers designing power or thermal management units, to cancel the temperature-induced bias on power measurements. This will help them gather temperature-neutral power data while running multiple instance of their benchmarks. Also power requirements and system failure rates can be decreased by controlling the CPU's thermal behavior. Even though it is usually assumed that the temperature/power relationship is exponentially related, there is however a lack of publicly available physical temperature/power measurements to back up this assumption, something our paper corrects. Via measurements on two pertinent platforms sporting nanometer-scale application processors, we show that the power/temperature relationship is indeed very likely exponential over a 20{\deg}C to 85{\deg}C temperature range. Our data suggest that, for application processors operating between 20{\deg}C and 50{\deg}C, a quadratic model is still accurate and a linear approximation is acceptable.Comment: Submitted to SAMOS 2014; International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS XIV

Straintronics: A Leap towards Ultimate Energy Efficiency of Magnetic Memory and Logic

After decades of exponential growth of the semiconductor industries, predicted by Moore’s Law, the complementary metal-oxide semiconductor (CMOS) circuits are approaching their end of the road, as the feature sizes reach sub-10nm regimes, leaving electrical engineers with a profusion of design challenges in terms of energy limitations and power density. The latter has left the road for alternative technologies wide open to help CMOS overcome the present challenges. Magnetic random access memories (MRAM) are one of the candidates to assist with aforesaid obstacles. Proposed in the early 90’s, MRAM has been under research and development for decades. The expedition for energy efficient MRAM is carried out by the fact that magnetic logic, potentially, has orders of magnitude lower switching energy compared to a charge-based CMOS logic since, in a nanomagnet, magnetic domains would self-align with each other. Regrettably, conventional methods for switching the state of the cell in an MRAM, field induced magnetization switching (FIMS) and spin transfer torque (STT), use electric current (flow of charges) to switch the state of the magnet, nullifying the energy advantage, stated above. In order to maximize the energy efficiency, the amount of charge required to switch the state of the MTJ should be minimized. To this end, straintronics, as an alternative energy efficient method to FIMS and STT to switch the state of a nanomagnet, is proposed recently. The method states that by combining piezoelectricity and inverse magnetostriction, the magnetization state of the device can flip, within few nano-seconds while reducing the switching energy by orders of magnitude compared to STT and FIMS. This research focuses on analysis, design, modeling, and applications of straintronics-based MTJ. The first goal is to perform an in-depth analysis on the static and dynamic behavior of the device. Next, we are aiming to increase the accuracy of the model by including the effect of temperature and thermal noise on the device’s behavior. The goal of performing such analysis is to create a comprehensive model of the device that predicts both static and dynamic responses of the magnetization to applied stress. The model will be used to interface the device with CMOS controllers and switches in large systems. Next, in an attempt to speed up the simulation of such devices in multi-megabyte memory systems, a liberal model has been developed by analytically approximating a solution to the magnetization dynamics, which should be numerically solved otherwise. The liberal model demonstrates more than two orders of magnitude speed improvement compared to the conventional numerical models. Highlighting the applications of the straintronics devices by combining such devices with peripheral CMOS circuitry is another goal of the research. Design of a proof-of-concept 2 kilo-bit nonvolatile straintronics-based memory was introduced in our recent work. To highlight the potential applications of the straintronics device, beyond data storage, the use of the principle in ultra-fast yet low power true random number generation and neuron/synapse design for artificial neural networks have been investigated. Lastly, in an attempt to investigate the practicality of the straintronics principle, the effect of process variations and interface imperfections on the switching behavior of the magnetization is investigated. The results reveal the destructive aftermath of fabrication imperfections on the switching pattern of the device, leaving careful pulse-shaping, alternative topologies, or combination with STT as the last resorts for successful strain-based magnetization switching.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137010/1/barangi_1.pd