548 research outputs found

    Power Optimization in Johnson Counter through Clock Gating with Static Energy Recovery Logic

    Get PDF
    In the latest designs of VLSI, power dissipation is the main charge to take care. The dependency on micro electronics is rising as the size of chip is being compact & also the systems with minimal power are being prioritized. The computer systems are comprised of sequential circuitries & this is the reason that designs having minimal power absorption gave gained priority. In this document, we have suggested a schema on minimal power of Johnson Counter by employing a clock gating system & pass transistors in D flip flop. By making few judgements on power in SPICE, it is presumed that he suggested system design leads to minimal power decadence & has simple interlinking in contrast to the complicated traditional designs. In this document we put the outcomes of power in contrast in four methods that are TG ADCL i.e. Adiabatic Dynamic CMOS Logic, TG QSERL i.e. Quai static energy recovery logic, TG normal & TG split level pulse. Power has risen too high in TG ADCL, TG QSERL & TG normal

    Energy Aware Design and Analysis for Synchronous and Asynchronous Circuits

    Get PDF
    Power dissipation has become a major concern for IC designers. Various low power design techniques have been developed for synchronous circuits. Asynchronous circuits, however. have gained more interests recently due to their benefits in lower noise, easy timing control, etc. But few publications on energy reduction techniques for asynchronous logic are available. Power awareness indicates the ability of the system power to scale with changing conditions and quality requirements. Scalability is an important figure-of-merit since it allows the end user to implement operational policy. just like the user of mobile multimedia equipment needs to select between better quality and longer battery operation time. This dissertation discusses power/energy optimization and performs analysis on both synchronous and asynchronous logic. The major contributions of this dissertation include: 1 ) A 2-Dimensional Pipeline Gating technique for synchronous pipelined circuits to improve their power awareness has been proposed. This technique gates the corresponding clock lines connected to registers in both vertical direction (the data flow direction) and horizontal direction (registers within each pipeline stage) based on current input precision. 2) Two energy reduction techniques, Signal Bypassing & Insertion and Zero Insertion. have been developed for NCL circuits. Both techniques use Nulls to replace redundant Data 0\u27s based on current input precision in order to reduce the switching activity while Signal Bypassing & Insertion is for non-pipelined NCI, circuits and Zero Insertion is for pipelined counterparts. A dynamic active-bit detection scheme is also developed as an expansion. 3) Two energy estimation techniques, Equivalent Inverter Modeling based on Input Mapping in transistor-level and Switching Activity Modeling in gate-level, have been proposed. The former one is for CMOS gates with feedbacks and the latter one is for NCL circuits

    Asynchronous Data Processing Platforms for Energy Efficiency, Performance, and Scalability

    Get PDF
    The global technology revolution is changing the integrated circuit industry from the one driven by performance to the one driven by energy, scalability and more-balanced design goals. Without clock-related issues, asynchronous circuits enable further design tradeoffs and in operation adaptive adjustments for energy efficiency. This dissertation work presents the design methodology of the asynchronous circuit using NULL Convention Logic (NCL) and multi-threshold CMOS techniques for energy efficiency and throughput optimization in digital signal processing circuits. Parallel homogeneous and heterogeneous platforms implementing adaptive dynamic voltage scaling (DVS) based on the observation of system fullness and workload prediction are developed for balanced control of the performance and energy efficiency. Datapath control logic with NULL Cycle Reduction (NCR) and arbitration network are incorporated in the heterogeneous platform for large scale cascading. The platforms have been integrated with the data processing units using the IBM 130 nm 8RF process and fabricated using the MITLL 90 nm FDSOI process. Simulation and physical testing results show the energy efficiency advantage of asynchronous designs and the effective of the adaptive DVS mechanism in balancing the energy and performance in both platforms

    Research on low power technology by AC power supply circuits

    Get PDF
    制度:新 ; 報告番号:甲3692号 ; 学位の種類:博士(工学) ; 授与年月日:2012/9/15 ; 早大学位記番号:新6060Waseda Universit

    A full-custom digital-signal-processing unit for real-time cortical blood flow monitoring

    Get PDF
    Master'sMASTER OF ENGINEERIN

    MorphIC: A 65-nm 738k-Synapse/mm2^2 Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning

    Full text link
    Recent trends in the field of neural network accelerators investigate weight quantization as a means to increase the resource- and power-efficiency of hardware devices. As full on-chip weight storage is necessary to avoid the high energy cost of off-chip memory accesses, memory reduction requirements for weight storage pushed toward the use of binary weights, which were demonstrated to have a limited accuracy reduction on many applications when quantization-aware training techniques are used. In parallel, spiking neural network (SNN) architectures are explored to further reduce power when processing sparse event-based data streams, while on-chip spike-based online learning appears as a key feature for applications constrained in power and resources during the training phase. However, designing power- and area-efficient spiking neural networks still requires the development of specific techniques in order to leverage on-chip online learning on binary weights without compromising the synapse density. In this work, we demonstrate MorphIC, a quad-core binary-weight digital neuromorphic processor embedding a stochastic version of the spike-driven synaptic plasticity (S-SDSP) learning rule and a hierarchical routing fabric for large-scale chip interconnection. The MorphIC SNN processor embeds a total of 2k leaky integrate-and-fire (LIF) neurons and more than two million plastic synapses for an active silicon area of 2.86mm2^2 in 65nm CMOS, achieving a high density of 738k synapses/mm2^2. MorphIC demonstrates an order-of-magnitude improvement in the area-accuracy tradeoff on the MNIST classification task compared to previously-proposed SNNs, while having no penalty in the energy-accuracy tradeoff.Comment: This document is the paper as accepted for publication in the IEEE Transactions on Biomedical Circuits and Systems journal (2019), the fully-edited paper is available at https://ieeexplore.ieee.org/document/876400

    Coupling Latency-Insensitivity with Variable-Latency for Better Than Worst Case Design: A RISC Case Study

    Get PDF
    The gap between worst and typical case delays is bound to increase in nanometer scale technologies due to the spread in process manufacturing parameters. To still profit from scaling, designs should tolerate worst case delays seamlessly and with a minimum performance degradation with respect to the typical case. We present a simple RISC core which tolerates worst case extra latency using the Latency-Insensitive Design approach coupled to a Variable-Latency mechanism. Stalls caused by excessive delay, by data and control hazards and by late memory access are dealt with in a uniform way. Compared to a pure worst-case approach, our design method permits to increase the core clock frequency by 23% in a 45 nm CMOS technology, without area and power penalty

    Low power predictable memory and processing architectures

    Get PDF
    Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally
    corecore