1,972 research outputs found

    Optimizations for a Current-Controlled Memristor-based Neuromorphic Synapse Design

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    The synapse is a key element of neuromorphic computing in terms of efficiency and accuracy. In this paper, an optimized current-controlled memristive synapse circuit is proposed. Our proposed synapse demonstrates reliability in the face of process variation and the inherent stochastic behavior of memristors. Up to an 82% energy optimization can be seen during the SET operation over prior work. In addition, the READ process shows up to 54% energy savings. Our current-controlled approach also provides more reliable programming over traditional programming methods. This design is demonstrated with a 4-bit memory precision configuration. Using a spiking neural network (SNN), a neuromorphic application analysis was performed with this precision configuration. Our optimized design showed up to 82% improvement in control applications and a 2.7x improvement in classification applications compared with other design cases

    Modified Level Restorers Using Current Sink and Current Source Inverter Structures for BBL-PT Full Adder

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    Full adder is an essential component for the design and development of all types of processors like digital signal processors (DSP), microprocessors etc. In most of these systems adder lies in the critical path that affects the overall speed of the system. So enhancing the performance of the 1-bit full adder cell is a significant goal. In this paper, we proposed two modified level restorers using current sink and current source inverter structures for branch-based logic and pass-transistor (BBL-PT) full adder [1]. In BBL-PT full adder, there lies a drawback i.e. voltage step existence that could be eliminated in the proposed logics by using the current sink inverter and current source inverter structures. The proposed full adders are compared with the two standard and well-known logic styles, i.e. conventional static CMOS logic and Complementary Pass transistor Logic (CPL), demonstrated the good delay performance. The implementation of 8-bit ripple carry adder based on proposed full adders are finally demonstrated. The CPL 8-bit RCA and as well as the proposed ones is having better delay performance than the static CMOS and BBL-PT 8-bit RCA. The performance of the proposed BBL-PT cell with current sink & current source inverter structures are examined using PSPICE and the model parameters of a 0.13 µm CMOS process

    Asymmetric clock driver for improved power and noise performances

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    One of the most important sources of switching noise and power consumption in large VLSI circuits is the clock generation and distribution tree. This paper analyzes how the use of an asymmetric clock can be an important solution to reduce the switching noise generated by the global clock, with a very reduced degradation in performances and reliability. The suited sizing of clock generators and the design of asymmetric clock tree cells, show the benefits of the proposed technique, validated through a design example where a 50% of noise reduction is achieved with 10% of loss in operation frequency and no penalty, even saving, in power consumption.Ministerio de Educación y Ciencia TEC2004-01509Junta de Andalucía TIC2006-63

    Effective network grid synthesis and optimization for high performance very large scale integration system design

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    制度:新 ; 文部省報告番号:甲2642号 ; 学位の種類:博士(工学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新480

    Embracing Low-Power Systems with Improvement in Security and Energy-Efficiency

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    As the economies around the world are aligning more towards usage of computing systems, the global energy demand for computing is increasing rapidly. Additionally, the boom in AI based applications and services has already invited the pervasion of specialized computing hardware architectures for AI (accelerators). A big chunk of research in the industry and academia is being focused on providing energy efficiency to all kinds of power hungry computing architectures. This dissertation adds to these efforts. Aggressive voltage underscaling of chips is one the effective low power paradigms of providing energy efficiency. This dissertation identifies and deals with the reliability and performance problems associated with this paradigm and innovates novel energy efficient approaches. Specifically, the properties of a low power security primitive have been improved and, higher performance has been unlocked in an AI accelerator (Google TPU) in an aggressively voltage underscaled environment. And, novel power saving opportunities have been unlocked by characterizing the usage pattern of a baseline TPU with rigorous mathematical analysis

    Barrel Shifter Physical Unclonable Function Based Encryption

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    Physical Unclonable Functions (PUFs) are circuits designed to extract physical randomness from the underlying circuit. This randomness depends on the manufacturing process. It differs for each device enabling chip-level authentication and key generation applications. We present a protocol utilizing a PUF for secure data transmission. Parties each have a PUF used for encryption and decryption; this is facilitated by constraining the PUF to be commutative. This framework is evaluated with a primitive permutation network - a barrel shifter. Physical randomness is derived from the delay of different shift paths. Barrel shifter (BS) PUF captures the delay of different shift paths. This delay is entangled with message bits before they are sent across an insecure channel. BS-PUF is implemented using transmission gates; their characteristics ensure same-chip reproducibility, a necessary property of PUFs. Post-layout simulations of a common centroid layout 8-level barrel shifter in 0.13 {\mu}m technology assess uniqueness, stability and randomness properties. BS-PUFs pass all selected NIST statistical randomness tests. Stability similar to Ring Oscillator (RO) PUFs under environment variation is shown. Logistic regression of 100,000 plaintext-ciphertext pairs (PCPs) failed to successfully model BS- PUF behavior

    SIRENA: A CAD environment for behavioural modelling and simulation of VLSI cellular neural network chips

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    This paper presents SIRENA, a CAD environment for the simulation and modelling of mixed-signal VLSI parallel processing chips based on cellular neural networks. SIRENA includes capabilities for: (a) the description of nominal and non-ideal operation of CNN analogue circuitry at the behavioural level; (b) performing realistic simulations of the transient evolution of physical CNNs including deviations due to second-order effects of the hardware; and, (c) evaluating sensitivity figures, and realize noise and Monte Carlo simulations in the time domain. These capabilities portray SIRENA as better suited for CNN chip development than algorithmic simulation packages (such as OpenSimulator, Sesame) or conventional neural networks simulators (RCS, GENESIS, SFINX), which are not oriented to the evaluation of hardware non-idealities. As compared to conventional electrical simulators (such as HSPICE or ELDO-FAS), SIRENA provides easier modelling of the hardware parasitics, a significant reduction in computation time, and similar accuracy levels. Consequently, iteration during the design procedure becomes possible, supporting decision making regarding design strategies and dimensioning. SIRENA has been developed using object-oriented programming techniques in C, and currently runs under the UNIX operating system and X-Windows framework. It employs a dedicated high-level hardware description language: DECEL, fitted to the description of non-idealities arising in CNN hardware. This language has been developed aiming generality, in the sense of making no restrictions on the network models that can be implemented. SIRENA is highly modular and composed of independent tools. This simplifies future expansions and improvements.Comisión Interministerial de Ciencia y Tecnología TIC96-1392-C02-0
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