Design and Analysis of an Asynchronous Microcontroller

This dissertation presents the design of the most complex MTNCL circuit to date. A fully functional MTNCL MSP430 microcontroller is designed and benchmarked against an open source synchronous MSP430. The designs are compared in terms of area, active energy, and leakage energy. Techniques to reduce MTNCL pipeline activity and improve MTNCL register file area and power consumption are introduced. The results show the MTNCL design to have superior leakage power characteristics. The area and active energy comparisons highlight the need for better MTNCL logic synthesis techniques

ULTRA ENERGY-EFFICIENT SUB-/NEAR-THRESHOLD COMPUTING: PLATFORM AND METHODOLOGY

Ph.DDOCTOR OF PHILOSOPH

Design and Analysis of an Adaptive Asynchronous System Architecture for Energy Efficiency

Power has become a critical design parameter for digital CMOS integrated circuits. With performance still garnering much concern, a central idea has emerged: minimizing power consumption while maintaining performance. The use of dynamic voltage scaling (DVS) with parallelism has shown to be an effective way of saving power while maintaining performance. However, the potency of DVS and parallelism in traditional, clocked synchronous systems is limited because of the strict timing requirements such systems must comply with. Delay-insensitive (DI) asynchronous systems have the potential to benefit more from these techniques due to their flexible timing requirements and high modularity. This dissertation presents the design and analysis of a real-time adaptive DVS architecture for paralleled Multi-Threshold NULL Convention Logic (MTNCL) systems. Results show that energy-efficient systems with low area overhead can be created using this approach

Design Methodologies and CAD Tools for Leakage Power Optimization in FPGAs

The scaling of the CMOS technology has precipitated an exponential increase in both subthreshold and gate leakage currents in modern VLSI designs. Consequently, the contribution of leakage power to the total chip power dissipation for CMOS designs is increasing rapidly, which is estimated to be 40% for the current technology generations and is expected to exceed 50% by the 65nm CMOS technology. In FPGAs, the power dissipation problem is further aggravated when compared to ASIC designs because FPGA use more transistors per logic function when compared to ASIC designs. Consequently, solving the leakage power problem is pivotal to devising power-aware FPGAs in the nanometer regime. This thesis focuses on devising both architectural and CAD techniques for leakage mitigation in FPGAs. Several CAD and architectural modifications are proposed to reduce the impact of leakage power dissipation on modern FPGAs. Firstly, multi-threshold CMOS (MTCMOS) techniques are introduced to FPGAs to permanently turn OFF the unused resources of the FPGA, FPGAs are characterized with low utilization percentages that can reach 60%. Moreover, such architecture enables the dynamic shutting down of the FPGA idle parts, thus reducing the standby leakage significantly. Employing the MTCMOS technique in FPGAs requires several changes to the FPGA architecture, including the placement and routing of the sleep signals and the MTCMOS granularity. On the CAD level, the packing and placement stages are modified to allow the possibility of dynamically turning OFF the idle parts of the FPGA. A new activity generation algorithm is proposed and implemented that aims to identify the logic blocks in a design that exhibit similar idleness periods. Several criteria for the activity generation algorithm are used, including connectivity and logic function. Several versions of the activity generation algorithm are implemented to trade power savings with runtime. A newly developed packing algorithm uses the resulting activities to minimize leakage power dissipation by packing the logic blocks with similar or close activities together. By proposing an FPGA architecture that supports MTCMOS and developing a CAD tool that supports the new architecture, an average power savings of 30% is achieved for a 90nm CMOS process while incurring a speed penalty of less than 5%. This technique is further extended to provide a timing-sensitive version of the CAD flow to vary the speed penalty according to the criticality of each logic block. Secondly, a new technique for leakage power reduction in FPGAs based on the use of input dependency is developed. Both subthreshold and gate leakage power are heavily dependent on the input state. In FPGAs, the effect of input dependency is exacerbated due to the use of pass-transistor multiplexer logic, which can exhibit up to 50% variation in leakage power due to the input states. In this thesis, a new algorithm is proposed that uses bit permutation to reduce subthreshold and gate leakage power dissipation in FPGAs. The bit permutation algorithm provides an average leakage power reduction of 40% while having less than 2% impact on the performance and no penalty on the design area. Thirdly, an accurate probabilistic power model for FPGAs is developed to quantify the savings from the proposed leakage power reduction techniques. The proposed power model accounts for dynamic, short circuit, and leakage power (including both subthreshold and gate leakage power) dissipation in FPGAs. Moreover, the power model accounts for power due to glitches, which accounts for almost 20% of the dynamic power dissipation in FPGAs. The use of probabilities in the power model makes it more computationally efficient than the other FPGA power models in the literature that rely on long input sequence simulations. One of the main advantages of the proposed power model is the incorporation of spatial correlation while estimating the signal probability. Other probabilistic FPGA power models assume spatial independence among the design signals, thus overestimating the power calculations. In the proposed model, a probabilistic model is proposed for spatial correlations among the design signals. Moreover, a different variation is proposed that manages to capture most of the spatial correlations with minimum impact on runtime. Furthermore, the proposed power model accounts for the input dependency of subthreshold and gate leakage power dissipation. By comparing the proposed power model to HSpice simulation, the estimated power is within 8% and is closer to HSpice simulations than other probabilistic FPGA power models by an average of 20%

Digital implementation of a wavelet-based event detector for cardiac pacemakers

This paper presents a digital hardware implementation of a novel wavelet-based event detector suitable for the next generation of cardiac pacemakers. Significant power savings are achieved by introducing a second operation mode that shuts down 2/3 of the hardware for long time periods when the pacemaker patient is not exposed to noise, while not degrading performance. Due to a 0.13-mu m CMOS technology and the low clock frequency of 1 kHz, leakage power becomes the dominating power source. By introducing sleep transistors in the power-supply rails, leakage power of the hardware being shut off is reduced by 97%. Power estimation on RTL-level shows that the overall power consumption is reduced by 67% with a dual operation mode. Under these conditions, the detector is expected to operate in the sub-mu W region. Detection performance is evaluated by means of databases containing electrograms to which five types of exogenic and endogenic interferences are added. The results show that reliable detection is obtained at moderate and low signal to noise-ratios (SNRs). Average detection performance in terms of detected events and false alarms for 25-dB SNR is P-D = 0.98 and P-FA = 0.014, respectively

On-chip NBTI and Gate-Oxide-Degradation Sensing and Dynamic Management in VLSI Circuits.

The VLSI industry has achieved advancement in technology by continuous process scaling which has resulted in large scale integration. However, scaling also poses new reliability challenges. Currently the industry ensures the reliability of chips by limiting the supply voltage and temperature, but these constraints limit the benefits that are obtained from new process nodes. This method of managing reliability during design time is called Static Reliability Management (SRM). While SRM ensures that all the chips meet the reliability specifications, it introduces extreme pessimism in the chips as it margins for worst process, voltage, temperature and circuit state (PVTS), which will not be required for the majority of chips. To reduce the pessimism of SRM, the system needs to be made aware of its reliability by employing degradation sensors or degradation detection techniques. Using the degradation measurements, the system can estimate its lifetime and can adjust its operating points (supply voltage and temperature limits) dynamically and trade excess reliability slack with performance. This method of reliability management is called Dynamic Reliability Management (DRM). In this work we investigate different methods of DRM. We focus on two critical degradation mechanisms: Negative Bias Temperature Instability (NBTI) and Gate-oxide degradation. We propose NBTI and Gate-oxide degradation sensors with low area and power overhead, which allows them to be deployed in large numbers on the chip enabling collection of degradation statistics. The sensors were designed in 130nm and 45nm process nodes and tested on two test-chips. We then used the sensors to perform DRM in a silicon test for the first time. We demonstrate that DRM eliminates excess reliability slack which allows for a boost in supply voltage and performance. We then propose in situ Bias Temperature Instability (BTI) and Gate-oxide wear-out detection techniques. The in situ technique measures the degradation in the actual devices in the core and removes all the layers of uncertainty which arise because of the statistical nature of degradation and its dependence on PVTS. We implemented and tested these techniques on two test chips in a 65nm process node. We then use the BTI sensing technique to perform DRM.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86281/1/prsingh_1.pd

MoRS: An approximate fault modelling framework for reduced-voltage SRAMs

On-chip memory (usually based on Static RAMs-SRAMs) are crucial components for various computing devices including heterogeneous devices, e.g, GPUs, FPGAs, ASICs to achieve high performance. Modern workloads such as Deep Neural Networks (DNNs) running on these heterogeneous fabrics are highly dependent on the on-chip memory architecture for efficient acceleration. Hence, improving the energy-efficiency of such memories directly leads to an efficient system. One of the common methods to save energy is undervolting i.e., supply voltage underscaling below the nominal level. Such systems can be safely undervolted without incurring faults down to a certain voltage limit. This safe range is also called voltage guardband. However, reducing voltage below the guardband level without decreasing frequency causes timing-based faults. In this paper, we propose MoRS, a framework that generates the first approximate undervolting fault model using real faults extracted from experimental undervolting studies on SRAMs to build the model. We inject the faults generated by MoRS into the on-chip memory of the DNN accelerator to evaluate the resilience of the system under the test. MoRS has the advantage of simplicity without any need for high-time overhead experiments while being accurate enough in comparison to a fully randomly-generated fault injection approach. We evaluate our experiment in popular DNN workloads by mapping weights to SRAMs and measure the accuracy difference between the output of the MoRS and the real data. Our results show that the maximum difference between real fault data and the output fault model of MoRS is 6.21%, whereas the maximum difference between real data and random fault injection model is 23.2%. In terms of average proximity to the real data, the output of MoRS outperforms the random fault injection approach by 3.21x.This work is partially funded by Open Transprecision Computing (OPRECOM) project, Summer of Code 2020.Peer ReviewedPostprint (author's final draft

Addressing On-Chip Power Conversion and Dissipation Issues in Many-Core System-on-a-Chip based on Conventional Silicon and Emerging Nanotechnologies

Title from PDF of title page viewed August 27, 2018Dissertation advisor: Masud H ChowdhuryVitaIncludes bibliographical references (pages 158-163)Thesis (Ph.D.)--School of Computing and Engineering and Department of Physics and Astronomy. University of Missouri--Kansas City, 2017Integrated circuits (ICs) are moving towards system-on-a-chip (SOC) designs. SOC allows various small and large electronic systems to be implemented in a single chip. This approach enables the miniaturization of design blocks that leads to high density transistor integration, faster response time, and lower fabrication costs. To reap the benefits of SOC and uphold the miniaturization of transistors, innovative power delivery and power dissipation management schemes are paramount. This dissertation focuses on on-chip integration of power delivery systems and managing power dissipation to increase the lifetime of energy storage elements. We explore this problem from two different angels: On-chip voltage regulators and power gating techniques. On-chip voltage regulators reduce parasitic effects, and allow faster and efficient power delivery for microprocessors. Power gating techniques, on the other hand, reduce the power loss incurred by circuit blocks during standby mode. Power dissipation (Ptotal = Pstatic and Pdynamic) in a complementary metal-oxide semiconductor (CMOS) circuit comes from two sources: static and dynamic. A quadratic dependency on the dynamic switching power and a more than linear dependency on static power as a form of gate leakage (subthreshold current) exist. To reduce dynamic power loss, the supply power should be reduced. A significant reduction in power dissipation occurs when portions of a microprocessor operate at a lower voltage level. This reduction in supply voltage is achieved via voltage regulators or converters. Voltage regulators are used to provide a stable power supply to the microprocessor. The conventional off-chip switching voltage regulator contains a passive floating inductor, which is difficult to be implemented inside the chip due to excessive power dissipation and parasitic effects. Additionally, the inductor takes a very large chip area while hampering the scaling process. These limitations make passive inductor based on-chip regulator design very unattractive for SOC integration and multi-/many-core environments. To circumvent the challenges, three alternative techniques based on active circuit elements to replace the passive LC filter of the buck convertor are developed. The first inductorless on-chip switching voltage regulator architecture is based on a cascaded 2nd order multiple feedback (MFB) low-pass filter (LPF). This design has the ability to modulate to multiple voltage settings via pulse with modulation (PWM). The second approach is a supplementary design utilizing a hybrid low drop-out scheme to lower the output ripple of the switching regulator over a wider frequency range. The third design approach allows the integration of an entire power management system within a single chipset by combining a highly efficient switching regulator with an intermittently efficient linear regulator (area efficient), for robust and highly efficient on-chip regulation. The static power (Pstatic) or subthreshold leakage power (Pleak) increases with technology scaling. To mitigate static power dissipation, power gating techniques are implemented. Power gating is one of the popular methods to manage leakage power during standby periods in low-power high-speed IC design. It works by using transistor based switches to shut down part of the circuit block and put them in the idle mode. The efficiency of a power gating scheme involves minimum Ioff and high Ion for the sleep transistor. A conventional sleep transistor circuit design requires an additional header, footer, or both switches to turn off the logic block. This additional transistor causes signal delay and increases the chip area. We propose two innovative designs for next generation sleep transistor designs. For an above threshold operation, we present a sleep transistor design based on fully depleted silicon-on-insulator (FDSOI) device. For a subthreshold circuit operation, we implement a sleep transistor utilizing the newly developed silicon-on ferroelectric-insulator field effect transistor (SOFFET). In both of the designs, the ability to control the threshold voltage via bias voltage at the back gate makes both devices more flexible for sleep transistors design than a bulk MOSFET. The proposed approaches simplify the design complexity, reduce the chip area, eliminate the voltage drop by sleep transistor, and improve power dissipation. In addition, the design provides a dynamically controlled Vt for times when the circuit needs to be in a sleep or switching mode.Introduction -- Background and literature review -- Fully integrated on-chip switching voltage regulator -- Hybrid LDO voltage regulator based on cascaded second order multiple feedback loop -- Single and dual output two-stage on-chip power management system -- Sleep transistor design using double-gate FDSOI -- Subthreshold region sleep transistor design -- Conclusio

Energy autonomous systems : future trends in devices, technology, and systems

The rapid evolution of electronic devices since the beginning of the nanoelectronics era has brought about exceptional computational power in an ever shrinking system footprint. This has enabled among others the wealth of nomadic battery powered wireless systems (smart phones, mp3 players, GPS, …) that society currently enjoys. Emerging integration technologies enabling even smaller volumes and the associated increased functional density may bring about a new revolution in systems targeting wearable healthcare, wellness, lifestyle and industrial monitoring applications