Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review

The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER

Siwa: A custom RISC-V based system on chip (SOC) for low power medical applications

This work introduces the development of Siwa, a RISC-V RV32I 32-bit based core, intended as a flexible control platform for highly integrated implantable biomedical applications, and implemented on a commercial 0.18 m high voltage (HV) CMOS technology. Simulations show that Siwa can outperform commercial micro-controllers commonly used in the medical industry as control units for implantable devices, with energy requirements below the 50 pJ per clock cycle.Agencia Nacional de Investigación e Innovació

Re-designing Main Memory Subsystems with Emerging Monolithic 3D (M3D) Integration and Phase Change Memory Technologies

Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental trade-off. Pushing for a higher density inevitably increases access latency, and pushing for a reduced access latency often leads to a decreased density. This trade-off is so fundamental in DRAM based main memory subsystems that merely looking to re-architect DRAM subsystems cannot improve this trade-off, unless disruptive technological advancements are realized for implementing main memory subsystems. In this thesis, we focus on two key contributions to overcome the density (represented as the total chip area for the given capacity) and access latency related challenges in main memory subsystems. First, we show that the fundamental area-latency trade-offs in DRAM can be significantly improved by redesigning the DRAM cell-array structure using the emerging monolithic 3D (M3D) integration technology. A DRAM bank structure can be split across two or more M3D-integrated tiers on the same DRAM chip, to consequently be able to significantly reduce the total on-chip area occupancy of the DRAM bank and its access peripherals. This approach is fundamentally different from the well known approach of through-silicon vias (TSVs)-based 3D stacking of DRAM tiers. This is because the M3D integration based approach does not require a separate DRAM chip per tier, whereas the 3D-stacking based approach does. Our evaluation results for PARSEC benchmarks show that our designed M3D DRAM cellarray organizations can yield up to 9.56% less latency and up to 21.21% less energy-delay product (EDP), with up to 14% less DRAM die area, compared to the conventional 2D DDR4 DRAM. Second, we demonstrate a pathway for eliminating the write disturbance errors in single-level-cell PCM, thereby positioning the PCM technology, which has inherently more relaxed density and latency trade-off compared to DRAM, as a more viable option for replacing the DRAM technology. We introduce low-temperature partial-RESET operations for writing ‘0’s in PCM cells. Compared to traditional operations that write \u270\u27s in PCM cells, partial-RESET operations do not cause disturbance errors in neighboring cells during PCM writes. The overarching theme that connects the two individual contributions into this single thesis is the density versus latency argument. The existing PCM technology has 3 to 4× higher write latency compared to DRAM; nevertheless, the existing PCM technology can store 2 to 4 bits in a single cell compared to one bit per cell storage capacity of DRAM. Therefore, unlike DRAM, it becomes possible to increase the density of PCM without consequently increasing PCM latency. In other words, PCM exhibits inherently improved (more relaxed) density and latency trade-off. Thus, both of our contributions in this thesis, the first contribution of re-designing DRAM with M3D integration technology and the second contribution of making the PCM technology a more viable replacement of DRAM by eliminating the write disturbance errors in PCM, connect to the common overarching goal of improving the density and latency trade-off in main memory subsystems. In addition, we also discuss in this thesis possible future research directions that are aimed at extending the impacts of our proposed ideas so that they can transform the performance of main memory subsystems of the future

Carbon nanotubes as interconnect for next generation network on chip

Multi-core processors provide better performance when compared with their single-core equivalent. Recently, Networks-on-Chip (NoC) have emerged as a communication methodology for multi core chips. Network-on-Chip uses packet based communication for establishing a communication path between multiple cores connected via interconnects. Clock frequency, energy consumption and chip size are largely determined by these interconnects. According to the International Technology Roadmap for Semiconductors (ITRS), in the next five years up to 80% of microprocessor power will be consumed by interconnects. In the sub 100nm scaling range, interconnect behavior limits the performance and correctness of VLSI systems. The performance of copper interconnects tend to get reduced in the sub 100nm range and hence we need to examine other interconnect options. Single Wall Carbon Nanotubes exhibit better performance in sub 100nm processing technology due to their very large current carrying capacity and large electron mean free paths. This work suggests using Single Wall Carbon Nanotubes (SWCNT) as interconnects for Networks-on-Chip as they consume less energy and gives more throughput and bandwidth when compared with traditional Copper wires

A Micro Power Hardware Fabric for Embedded Computing

Field Programmable Gate Arrays (FPGAs) mitigate many of the problemsencountered with the development of ASICs by offering flexibility, faster time-to-market, and amortized NRE costs, among other benefits. While FPGAs are increasingly being used for complex computational applications such as signal and image processing, networking, and cryptology, they are far from ideal for these tasks due to relatively high power consumption and silicon usage overheads compared to direct ASIC implementation. A reconfigurable device that exhibits ASIC-like power characteristics and FPGA-like costs and tool support is desirable to fill this void. In this research, a parameterized, reconfigurable fabric model named as domain specific fabric (DSF) is developed that exhibits ASIC-like power characteristics for Digital Signal Processing (DSP) style applications. Using this model, the impact of varying different design parameters on power and performance has been studied. Different optimization techniques like local search and simulated annealing are used to determine the appropriate interconnect for a specific set of applications. A design space exploration tool has been developed to automate and generate a tailored architectural instance of the fabric.The fabric has been synthesized on 160 nm cell-based ASIC fabrication process from OKI and 130 nm from IBM. A detailed power-performance analysis has been completed using signal and image processing benchmarks from the MediaBench benchmark suite and elsewhere with comparisons to other hardware and software implementations. The optimized fabric implemented using the 130 nm process yields energy within 3X of a direct ASIC implementation, 330X better than a Virtex-II Pro FPGA and 2016X better than an Intel XScale processor

Center for Aeronautics and Space Information Sciences

This report summarizes the research done during 1991/92 under the Center for Aeronautics and Space Information Science (CASIS) program. The topics covered are computer architecture, networking, and neural nets

High Performance Optical Transmitter Ffr Next Generation Supercomputing and Data Communication

High speed optical interconnects consuming low power at affordable prices are always a major area of research focus. For the backbone network infrastructure, the need for more bandwidth driven by streaming video and other data intensive applications such as cloud computing has been steadily pushing the link speed to the 40Gb/s and 100Gb/s domain. However, high power consumption, low link density and high cost seriously prevent traditional optical transceiver from being the next generation of optical link technology. For short reach communications, such as interconnects in supercomputers, the issues related to the existing electrical links become a major bottleneck for the next generation of High Performance Computing (HPC). Both applications are seeking for an innovative solution of optical links to tackle those current issues. In order to target the next generation of supercomputers and data communication, we propose to develop a high performance optical transmitter by utilizing CISCO Systems®\u27s proprietary CMOS photonic technology. The research seeks to achieve the following outcomes: 1. Reduction of power consumption due to optical interconnects to less than 5pJ/bit without the need for Ring Resonators or DWDM and less than 300fJ/bit for short distance data bus applications. 2. Enable the increase in performance (computing speed) from Peta-Flop to Exa-Flops without the proportional increase in cost or power consumption that would be prohibitive to next generation system architectures by means of increasing the maximum data transmission rate over a single fiber. 3. Explore advanced modulation schemes such as PAM-16 (Pulse-Amplitude-Modulation with 16 levels) to increase the spectrum efficiency while keeping the same or less power figure. This research will focus on the improvement of both the electrical IC and optical IC for the optical transmitter. An accurate circuit model of the optical device is created to speed up the performance optimization and enable co-simulation of electrical driver. Circuit architectures are chosen to minimize the power consumption without sacrificing the speed and noise immunity. As a result, a silicon photonic based optical transmitter employing 1V supply, featuring 20Gb/s data rate is fabricated. The system consists of an electrical driver in 40nm CMOS and an optical MZI modulator with an RF length of less than 0.5mm in 0.13&mu m SOI CMOS. Two modulation schemes are successfully demonstrated: On-Off Keying (OOK) and Pulse-Amplitude-Modulation-N (PAM-N N=4, 16). Both versions demonstrate signal integrity, interface density, and scalability that fit into the next generation data communication and exa-scale computing. Modulation power at 20Gb/s data rate for OOK and PAM-16 of 4pJ/bit and 0.25pJ/bit are achieved for the first time of an MZI type optical modulator, respectively

Energy-aware synthesis for networks on chip architectures

The Network on Chip (NoC) paradigm was introduced as a scalable communication infrastructure for future System-on-Chip applications. Designing application specific customized communication architectures is critical for obtaining low power, high performance solutions. Two significant design automation problems are the creation of an optimized configuration, given application requirement the implementation of this on-chip network. Automating the design of on-chip networks requires models for estimating area and energy, algorithms to effectively explore the design space and network component libraries and tools to generate the hardware description. Chip architects are faced with managing a wide range of customization options for individual components, routers and topology. As energy is of paramount importance, the effectiveness of any custom NoC generation approach lies in the availability of good energy models to effectively explore the design space. This thesis describes a complete NoC synthesis flow, called NoCGEN, for creating energy-efficient custom NoC architectures. Three major automation problems are addressed: custom topology generation, energy modeling and generation. An iterative algorithm is proposed to generate application specific point-to-point and packet-switched networks. The algorithm explores the design space for efficient topologies using characterized models and a system-level floorplanner for evaluating placement and wire-energy. Prior to our contribution, building an energy model required careful analysis of transistor or gate implementations. To alleviate the burden, an automated linear regression-based methodology is proposed to rapidly extract energy models for many router designs. The resulting models are cycle accurate with low-complexity and found to be within 10% of gate-level energy simulations, and execute several orders of magnitude faster than gate-level simulations. A hardware description of the custom topology is generated using a parameterizable library and custom HDL generator. Fully reusable and scalable network components (switches, crossbars, arbiters, routing algorithms) are described using a template approach and are used to compose arbitrary topologies. A methodology for building and composing routers and topologies using a template engine is described. The entire flow is implemented as several demonstrable extensible tools with powerful visualization functionality. Several experiments are performed to demonstrate the design space exploration capabilities and compare it against a competing min-cut topology generation algorithm

Advanced digital SAR processing study

A highly programmable, land based, real time synthetic aperture radar (SAR) processor requiring a processed pixel rate of 2.75 MHz or more in a four look system was designed. Variations in range and azimuth compression, number of looks, range swath, range migration and SR mode were specified. Alternative range and azimuth processing algorithms were examined in conjunction with projected integrated circuit, digital architecture, and software technologies. The advaced digital SAR processor (ADSP) employs an FFT convolver algorithm for both range and azimuth processing in a parallel architecture configuration. Algorithm performace comparisons, design system design, implementation tradeoffs and the results of a supporting survey of integrated circuit and digital architecture technologies are reported. Cost tradeoffs and projections with alternate implementation plans are presented