752 research outputs found

    Coarse-grained reconfigurable array architectures

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    Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code

    A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

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    Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude

    Identification of dynamic circuit specialization opportunities in RTL code

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    Dynamic Circuit Specialization (DCS) optimizes a Field-Programmable Gate Array (FPGA) design by assuming a set of its input signals are constant for a reasonable amount of time, leading to a smaller and faster FPGA circuit. When the signals actually change, a new circuit is loaded into the FPGA through runtime reconfiguration. The signals the design is specialized for are called parameters. For certain designs, parameters can be selected so the DCS implementation is both smaller and faster than the original implementation. However, DCS also introduces an overhead that is difficult for the designer to take into account, making it hard to determine whether a design is improved by DCS or not. This article presents extensive results on a profiling methodology that analyses Register-Transfer Level (RTL) implementations of applications to check if DCS would be beneficial. It proposes to use the functional density as a measure for the area efficiency of an implementation, as this measure contains both the overhead and the gains of a DCS implementation. The first step of the methodology is to analyse the dynamic behaviour of signals in the design, to find good parameter candidates. The overhead of DCS is highly dependent on this dynamic behaviour. A second stage calculates the functional density for each candidate and compares it to the functional density of the original design. The profiling methodology resulted in three implementations of a profiling tool, the DCS-RTL profiler. The execution time, accuracy, and the quality of each implementation is assessed based on data from 10 RTL designs. All designs, except for the two 16-bit adaptable Finite Impulse Response (FIR) filters, are analysed in 1 hour or less

    Parametric Dense Stereovision Implementation on a System-on Chip (SoC)

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    This paper proposes a novel hardware implementation of a dense recovery of stereovision 3D measurements. Traditionally 3D stereo systems have imposed the maximum number of stereo correspondences, introducing a large restriction on artificial vision algorithms. The proposed system-on-chip (SoC) provides great performance and efficiency, with a scalable architecture available for many different situations, addressing real time processing of stereo image flow. Using double buffering techniques properly combined with pipelined processing, the use of reconfigurable hardware achieves a parametrisable SoC which gives the designer the opportunity to decide its right dimension and features. The proposed architecture does not need any external memory because the processing is done as image flow arrives. Our SoC provides 3D data directly without the storage of whole stereo images. Our goal is to obtain high processing speed while maintaining the accuracy of 3D data using minimum resources. Configurable parameters may be controlled by later/parallel stages of the vision algorithm executed on an embedded processor. Considering hardware FPGA clock of 100 MHz, image flows up to 50 frames per second (fps) of dense stereo maps of more than 30,000 depth points could be obtained considering 2 Mpix images, with a minimum initial latency. The implementation of computer vision algorithms on reconfigurable hardware, explicitly low level processing, opens up the prospect of its use in autonomous systems, and they can act as a coprocessor to reconstruct 3D images with high density information in real time

    Design of a Cost-Efficient Reconfigurable Pipeline ADC

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    Power budget is very critical in the design of battery-powered implantable biomedical instruments. High speed, high resolution and low power usually cannot be achieved at the same time. Therefore, a tradeoff must be made to compromise every aspect of those features. As the main component of the bioinstrument, high conversion rate, high resolution ADC consumes most of the power. Fortunately, based on the operation modes of the bioinstrument, a reconfigurable ADC can be used to solve this problem. The reconfigurable ADC will operate at 10-bit 40 MSPS for the diagnosis mode and at 8-bit 2.5 MSPS for the monitor mode. The ADC will be completely turned off if no active signal comes from sensors or if an off command is received from the antenna. By turning off the sample hold stage and the first two stages of the pipeline ADC, a significant power saving is achieved. However, the reconfigurable ADC suffers from two drawbacks. First, the leakage signals through the extra off-state switches in the third stage degrade the performance of the data converter. This situation tends to be even worse for high speed and high-resolution applications. An interference elimination technique has been proposed in this work to solve this problem. Simulation results show a significant attenuation of the spurious tones. Moreover, the transistors in the OTA tend to operate in weak inversion region due to the scaling of the bias current. The transistor in subthreshold is very slow due to the small transit frequency. In order to get a better tradeoff between the transconductance efficiency and the transit frequency, reconfigurable OTAs and scalable bias technique are devised to adjust the operating point from weak inversion to moderate inversion. The figure of merit of the reconfigurable ADC is comparable to the previously published conventional pipeline ADCs. For the 10-bit, 40 MSPS mode, the ADC attains a 56.9 dB SNDR for 35.4 mW power consumption. For the 8-bit 2.5 MSPS mode, the ADC attains a 49.2 dB SNDR for 7.9 mW power consumption. The area for the core layout is 1.9 mm2 for a 0.35 micrometer process
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