Power Aware Computing on GPUs

Energy and power density concerns in modern processors have led to significant computer architecture research efforts in power-aware and temperature-aware computing. With power dissipation becoming an increasingly vexing problem, power analysis of Graphical Processing Unit (GPU) and its components has become crucial for hardware and software system design. Here, we describe our technique for a coordinated measurement approach that combines real total power measurement and per-component power estimation. To identify power consumption accurately, we introduce the Activity-based Model for GPUs (AMG), from which we identify activity factors and power for microarchitectures on GPUs that will help in analyzing power tradeoffs of one component versus another using microbenchmarks. The key challenge addressed in this thesis is real-time power consumption, which can be accurately estimated using NVIDIA\u27s Management Library (NVML) through Pthreads. We validated our model using Kill-A-Watt power meter and the results are accurate within 10\%. The resulting Performance Application Programming Interface (PAPI) NVML component offers real-time total power measurements for GPUs. This thesis also compares a single NVIDIA C2075 GPU running MAGMA (Matrix Algebra on GPU and Multicore Architectures) kernels, to a 48 core AMD Istanbul CPU running LAPACK

PROCESSOR TEMPERATURE AND RELIABILITY ESTIMATION USING ACTIVITY COUNTERS

With the advent of technology scaling lifetime reliability is an emerging threat in high-performance and deadline-critical systems. High on-chip thermal gradients accelerates localised thermal elevations (hotspots) which increases the aging rate of the semiconductor devices. As a result, reliable operation of the processors has become a challenging task. Therefore, cost effective schemes for estimating temperature and reliability are crucial. In this work we present a reliability estimation scheme that is based on a light-weight temperature estimation technique that monitors hardware events. Unlike previously pro- posed hardware counter-based approaches, our approach involves a linear-temporal-feedback estimator, taking into account the effects of thermal inertia. The proposed approach shows an average absolute error of We then present a counter-based technique to estimate the thermal accelerated aging factor (TAAF), which is an indicator of lifetime reliability. Results demonstrate that the estimation error is within [−3, +5]

Optimization and Control of Cyber-Physical Vehicle Systems

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined

EVALUATION OF DIGITAL TWIN APPROACHES FOR THERMAL MODELING AND ENERGY OPTIMIZATION FOR EXISTING BUILDINGS

Residential, commercial, and industrial building sectors in the United States were responsible for 42% of the nation’s consumption of 100.2 quadrillion BTUs of energy in 2019 [1]. 80% of the nation’s energy is sourced from fossil fuels, including coal, natural gas, and petroleum. Fossil fuels are known contributors to carbon emissions and climate change, making energy reduction vital. Consequently, New Jersey Department of Military and Veterans Affairs (NJDMAVA) is tasked with evaluating energy consumption and efficiency in all New Jersey Army National Guard (NJARNG) facilities, as mandated by TAG Policy Letter 18-5, Executive Order 13990, and the Energy Independence and Security Act of 2007. This research investigates three building energy consumption modeling (BEM) approaches for colder weather: eQUEST, degree-day modeling, and resistance-capacitance (RC) modeling. Each method has distinct advantages and limitations, but BEM holds promise in identifying cost-effective energy-saving measures, aligning with the goals of government entities like NJDMAVA. Specifically, eQUEST proves valuable for experienced users in energy modeling. Degree-day modeling excels at detecting operational shifts and benchmarking similar facilities. The RC model was able to accurately predict energy savings as a result of changes to thermostat setting

Low power design of 16-bit synchronous counter by introducing effective clock monitoring circuits

Most of the system-level designs contain sequential circuits. Power optimization of these circuits at many levels is required to build a portable device with a long battery life. A dynamic clock gating technique was used in this work to reduce the power and temperature of a 16-bit counter. The simulation was performed on cadence SCL 180 nm technology, for a supply voltage of 1.8 V at a frequency of 500 MHz. With the proposed approach, a 77.16% power reduction was achieved at the cost of 14.83% in area overhead. Moreover, the layout of the circuits was also designed in the Innovus tool to obtain a more accurate silicon area and gate count. The Innovus output files ".flp file" and ".pptrace file" were used as inputs to the HotSpot tool for determining the absolute temperature of the integrated circuits (ICs). The obtained temperature results were compared with the ordinary 16-bit counter, and it was found that the proposed approach was able to reduce temperature by 14.34%

Power-Thermal Modeling and Control of Energy-Efficient Servers and Datacenters

Recently, the energy-efficiency constraints have become the dominant limiting factor for datacenters due to their unprecedented increase of growing size and electrical power demands. In this chapter we explain the power and thermal modeling and control solutions which can play a key role to reduce the power consumption of datacenters considering time-varying workload characteristics while maintaining the performance requirements and the maximum temperature constraints. We first explain simple-yet-accurate power and temperature models for computing servers, and then, extend the model to cover computing servers and cooling infrastructure of datacenters. Second, we present the power and thermal management solutions for servers manipulating various control knobs such as voltage and frequency of servers, workload allocation, and even cooling capability, especially, flow rate of liquid cooled servers). Finally, we present the solution to minimize the server clusters of datacenters by proposing a solution which judiciously allocates virtual machines to servers considering their correlation, and then, the joint optimization solution which enables to minimize the total energy consumption of datacenters with hybrid cooling architecture (including the computing servers and the cooling infrastructure of datacenters)

Coordination in Service Value Networks - A Mechanism Design Approach

The fundamental paradigm shift from traditional value chains to agile service value networks (SVN) implies new economic and organizational challenges. This work provides an auction-based coordination mechanism that enables the allocation and pricing of service compositions in SVNs. The mechanism is multidimensional incentive compatible and implements an ex-post service level enforcement. Further extensions of the mechanism are evaluated following analytical and numerical research methods

The effects of carbon nanotubes on cpu cooling

Computers today have evolved from being big bulky machines that took up rooms of space into small simple machines for net browsing and into small but complicated multi-core servers and supercomputing architectures. This has been possible due to the evolution of the processors. Today processors have reached 45nm specifications with millions of transistors. Transistors produce heat when they run. Today more than ever we have a growing need for managing this heat efficiently. It is indicated that increasing power density can cause a difficulty in managing temperatures on a chip. It is also mentioned that we need to move to a more temperature aware architecture. In this research we try and address the issue of handling the heat produced by processors in an efficient manner. We have tried to see if the use of carbon nanotubes will prove useful in dissipating the heat produced by the processor in a more efficient way. In the process we have also tried to come up with a repeatable experimental setup as there is not work that we have been able to find describing this exact procedure. The use of carbon nanotubes seemed natural as they have a very high thermal conductivity value. Also one of the uncertain aspects of the experiment is the use of carbon nanotubes as they are still under study and their properties have not been completely understood and there has been some inconsistency in the theoretical values of their properties and the experimental results obtained so far. The results that we got were not exactly what we expected but were close, and were in the right direction indicating that more work in future would show better and consistent results

Providing QoS with Reduced Energy Consumption via Real-Time Voltage Scaling on Embedded Systems

Low energy consumption has emerged as one of the most important design objectives for many modern embedded systems, particularly the battery-operated PDAs. For some soft real-time applications such as multimedia applications, occasional deadline misses can be tolerated. How to leverage this feature to save more energy while still meeting the user required quality of service (QoS) is the research topic this thesis focuses on. We have proposed a new probabilistic design methodology, a set of energy reduction techniques for single and multiple processor systems by using dynamic voltage scaling (DVS), the practical solutions to voltage set-up problem for multiple voltage DVS system, and a new QoS metric. Most present design space exploration techniques, which are based on application's worst case execution time, often lead to over-designing systems. We have proposed the probabilistic design methodology for soft real-time embedded systems by using detailed execution time information in order to reduce the system resources while delivering the user required QoS probabilistically. One important phase in the probabilistic design methodology is the offline/online resource management. As an example, we have proposed a set of energy reduction techniques by employing DVS techniques to exploit the slacks arising from the tolerance to deadline misses for single and multiple processor systems while meeting the user required completion ratio statistically. Multiple-voltage DVS system is predicted as the future low-power system by International Technology Roadmap for Semiconductors (ITRS). In order to find the best way to employ DVS, we have formulated the voltage set-up problem and provided its practical solutions that seek the most energy efficient voltage setting for the design of multiple-voltage DVS systems. We have also presented a case study in designing energy-efficient dual voltage soft real-time system with (m, k)-firm deadline guarantee. Although completion ratio is widely used as a QoS metric, it can only be applied to the applications with independent tasks. We have proposed a new QoS metric that differentiates firm and soft deadlines and considers the task dependency as well. Based on this new metric, we have developed a set of online scheduling algorithms that enhance quality of presentation (QoP) significantly, particularly for overloaded systems