758 research outputs found

    Implementation of a Real-Time Beamforming System on Field Programmable Gate Array

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    Beamforming is an important technique in array signal processing and wireless communication systems. In this project, we investigate the Minimum Variance Distortionless Response (MVDR) beamforming technique and its implementation. The QR-RLS algorithm is chosen because of its advantages of numerical stability and systolic array architecture. The team successfully implemented the real-time beamforming of a linear array with 3 receiving antennas on a Xilinx Virtex-5 FPGA platform. Both the simulation and hardware implementation results are presented in this report

    Rapid prototyping from algorithm to FPGA prototype

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    Abstract. Wireless data usage continuously increases in today’s world setting higher requirements for wireless networks. Ever increasing requirements result in more complex hardware (HW) implementation, especially telecommunication System-on-Chips (SoC) performance is playing a key-role in this development. Complexity increases design workload, therefore, it makes design flow times longer. High-Level Synthesis (HLS) tools have been designed to automate and accelerate design by moving manual work on a higher level. This Master’s Thesis studies MathWorks HLS workflow usage for rapid prototyping of Wireless Communication SoC Intellectual Property (IP). This thesis introduces design and FPGA prototyping flow of Application-Specific Integrated Circuit (ASIC). It presents good design practices targeted for HLS. It also studies MathWorks Hardware Description Language (HDL) generation flow with HDL Coder, possible problems during the flow and solutions to overcome the problems. The HLS flow is examined with an example design that scales and limits the power of IQ-data. This work verifies the design in a Field-Programmable Gate Array (FPGA) environment. It concentrates on evaluating the usage and benefits of MathWorks HLS workflow targeted for rapid prototyping of SoCs. The Example IP is a Simulink model containing MATLAB algorithms and System Objects. The design is optimized on algorithm level and synthesized into VHDL. The generated Register-Transfer Level (RTL) is verified in co-simulation against the algorithm model. Optimization and verification methods are evaluated. The HDL model is further processed through logic-synthesis using the 3rd party synthesis tool run automatically with a script created by MathWorks workflow. The generated design is tested on FPGA with FPGA-in-the-loop simulation configuration. FPGA prototyping flow benefits for rapid prototyping are evaluated. Coding styles to generate synthesizable HDL code and simulation methods to improve simulation speed of hardware-like algorithm were discussed. MathWorks HLS workflow was evaluated for rapid prototype purposes from algorithm to FPGA. Optimization methods and capability for production quality RTL for ASIC target were also discussed. MathWorks’ tool flow provided promising results for rapid prototyping. It generated human-readable HDL that was successfully synthesized on FPGA. The FPGA model was simulated in FPGA-in-the-loop configuration successfully. It also provided good area and speed results for the ASIC target when the algorithm was written strictly from the hardware perspective. The process was found to be distinct and efficient.Nopea prototypointi algoritmista FPGA-prototyypiksi. Tiivistelmä. Langattoman datan käyttö kasvaa jatkuvasti nykymaailmassa ja asettaa korkeammat vaatimukset langattomille verkoille. Kasvavat vaatimukset tekevät laitteistototeutuksesta kompleksisempaa, erityisesti tietoliikenteessä käytettävien järjestelmäpiirien (SoC) tehokkuus on avainasemassa. Tämä kasvattaa suunnittelun työmäärää ja näin ollen suunnitteluvuohon kuluva aika pidentyy. Korkean tason synteesi (HLS) on kehitetty automatisoimaan ja nopeuttamaan digitaalisuunnittelua siirtämällä manuaalista työtä korkeammalle tasolle. Tämä diplomityö tutkii MathWorks:n HLS-vuon käyttöä langattomaan viestintään suunniteltavien SoC:ien tekijänoikeudenalaisten standardoitujen lohkojen (IP) nopeaan prototypointiin. Työ esittelee perinteisen asiakaspiirin (ASIC) suunnitteluvuon, FPGA-prototypointivuon ja suunnitteluperiaatteet HLS:ää varten. Työssä käydään läpi MathWorks:n laitteistokuvauskielen (HDL) generointivuo HDL Coder:lla, mahdollisia ongelmakohtia vuossa ja ratkaisuja ongelmiin. HLS-vuota tutkitaan esimerkkimallin avulla, joka skaalaa ja rajoittaa IQ-datan tehoa. Esimerkkimallin toiminta tarkistetaan ohjelmoitavan logiikkapiirin (FPGA) kanssa. Työ keskittyy arvioimaan MathWorks:n HLS-vuon käyttöä ja hyötyä nopeaan prototypointiin SoC:ien kehityksessä. Esimerkkinä käytetään Simulink-mallia, joka sisältää MATLAB-funktioita ja System Object-olioita. Algoritmitasolla optimoitu malli syntesoidaan VHDL:ksi ja rekisterinsiirtotason (RTL) mallin toiminta tarkistetaan yhteissimulaatiolla alkuperäistä algoritmimallia vasten. Optimointi- ja verifiointimenetelmien toimivuutta ja tehokkuutta arvioidaan. Generoitu HDL-malli syntesoidaan kolmannen osapuolen logiikkasynteesi-työkalulla, joka käynnistetään MathWorks:n työkaluvuon generoimalla komentosarjalla. Luotu malli ohjelmoidaan FPGA:lle ja sen toiminta tarkistetaan FPGA-simulaatiolla. Syntesoituvan HDL-koodin generointiin vaadittavia koodaustyylejä ja algoritmimallin simulointinopeutta parantavia menetelmiä tutkittiin. MathWorks:n HLS-vuon soveltuvuutta nopeaan prototypointiin algoritmista FPGA-prototyypiksi pohdittiin. Lisäksi optimointimenetelmiä ja vuon soveltuvuutta tuotantolaatuisen RTL:n generoimiseen arvioitiin. MathWorks:n työkaluvuo osoitti lupaavia tuloksia nopean prototypoinnin näkökulmasta. Se loi luettavaa HDL-koodia, joka syntesoitui FPGA:lle. Malli ajettiin onnistuneesti FPGA:lla. Vuon avulla saavutettiin hyviä tuloksia pinta-alan ja nopeuden suhteen, kun malli optimoitiin asiakaspiirille. Tämä vaati mallin kuvaamista tarkasti laitteiston näkökulmasta. Prosessi oli kokonaisuudessaan selkeä ja tehokas

    An Efficient Data Aggregation Algorithm for Cluster-based Sensor Network

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    Data aggregation in wireless sensor networks eliminates redundancy to improve bandwidth utilization and energy-efficiency of sensor nodes. One node, called the cluster leader, collects data from surrounding nodes and then sends the summarized information to upstream nodes. In this paper, we propose an algorithm to select a cluster leader that will perform data aggregation in a partially connected sensor network. The algorithm reduces the traffic flow inside the network by adaptively selecting the shortest route for packet routing to the cluster leader. We also describe a simulation framework for functional analysis of WSN applications taking our proposed algorithm as an exampl

    Performance Investigation of Digital Lowpass IIR Filter Based on Different Platforms

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    The work presented in this paper illuminates the design and simulation of a recursive or Infinite Impulse Response (IIR) filter. The proposed design algorithm employs the Genetic Algorithm to determine the filter coefficients to satisfy the required performance. The effectiveness of different platforms on filter design and performance has been studied in this paper. Three different platforms are considered to implement and verify the designed filter’s work through simulation. The first platform is the MATLAB/SIMULINK software package used to implement the Biquad form filter. This technique is the basis for the software implementation of the designed IIR filter. The HDL – Cosimulation technique is considered the second one; it inspired to take advantage of the existing tools in SIMULINK to convert the designed filter algorithm to the Very high-speed integrated circuit Hardware Description Language (VHDL) format. The System Generator is employed as the third technique, in which the designed filter is implemented as a hardware structure based on basic unit blocks provided by Xilinx System Generator. This technique facilitates the implementation of the designed filter in the FPGA target device. Simulation results show that the performance of the designed filter is remarkably reliable even with severe noise levels

    Can my chip behave like my brain?

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    Many decades ago, Carver Mead established the foundations of neuromorphic systems. Neuromorphic systems are analog circuits that emulate biology. These circuits utilize subthreshold dynamics of CMOS transistors to mimic the behavior of neurons. The objective is to not only simulate the human brain, but also to build useful applications using these bio-inspired circuits for ultra low power speech processing, image processing, and robotics. This can be achieved using reconfigurable hardware, like field programmable analog arrays (FPAAs), which enable configuring different applications on a cross platform system. As digital systems saturate in terms of power efficiency, this alternate approach has the potential to improve computational efficiency by approximately eight orders of magnitude. These systems, which include analog, digital, and neuromorphic elements combine to result in a very powerful reconfigurable processing machine.Ph.D

    Analog signal processing on a reconfigurable platform

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    The Cooperative Analog/Digital Signal Processing (CADSP) research group's approach to signal processing is to see what opportunities lie in adjusting the line between what is traditionally computed in digital and what can be done in analog. By allowing more computation to be done in analog, we can take advantage of its low power, continuous domain operation, and parallel capabilities. One setback keeping Analog Signal Processing (ASP) from achieving more wide-spread use, however, is its lack of programmability. The design cycle for a typical analog system often involves several iterations of the fabrication step, which is labor intensive, time consuming, and expensive. These costs in both time and money reduce the likelihood that engineers will consider an analog solution. With CADSP's development of a reconfigurable analog platform, a Field-Programmable Analog Array (FPAA), it has become much more practical for systems to incorporate processing in the analog domain. In this Thesis, I present an entire chain of tools that allow one to design simply at the system block level and then compile that design onto analog hardware. This tool chain uses the Simulink design environment and a custom library of blocks to create analog systems. I also present several of these ASP blocks, covering a broad range of functions from matrix computation to interfacing. In addition to these tools and blocks, the most recent FPAA architectures are discussed. These include the latest RASP general-purpose FPAAs as well as an adapted version geared toward high-speed applications.M.S.Committee Chair: Hasler, Paul; Committee Member: Anderson, David; Committee Member: Ghovanloo, Maysa

    A model-based design flow for embedded vision applications on heterogeneous architectures

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    The ability to gather information from images is straightforward to human, and one of the principal input to understand external world. Computer vision (CV) is the process to extract such knowledge from the visual domain in an algorithmic fashion. The requested computational power to process these information is very high. Until recently, the only feasible way to meet non-functional requirements like performance was to develop custom hardware, which is costly, time-consuming and can not be reused in a general purpose. The recent introduction of low-power and low-cost heterogeneous embedded boards, in which CPUs are combine with heterogeneous accelerators like GPUs, DSPs and FPGAs, can combine the hardware efficiency needed for non-functional requirements with the flexibility of software development. Embedded vision is the term used to identify the application of the aforementioned CV algorithms applied in the embedded field, which usually requires to satisfy, other than functional requirements, also non-functional requirements such as real-time performance, power, and energy efficiency. Rapid prototyping, early algorithm parametrization, testing, and validation of complex embedded video applications for such heterogeneous architectures is a very challenging task. This thesis presents a comprehensive framework that: 1) Is based on a model-based paradigm. Differently from the standard approaches at the state of the art that require designers to manually model the algorithm in any programming language, the proposed approach allows for a rapid prototyping, algorithm validation and parametrization in a model-based design environment (i.e., Matlab/Simulink). The framework relies on a multi-level design and verification flow by which the high-level model is then semi-automatically refined towards the final automatic synthesis into the target hardware device. 2) Relies on a polyglot parallel programming model. The proposed model combines different programming languages and environments such as C/C++, OpenMP, PThreads, OpenVX, OpenCV, and CUDA to best exploit different levels of parallelism while guaranteeing a semi-automatic customization. 3) Optimizes the application performance and energy efficiency through a novel algorithm for the mapping and scheduling of the application 3 tasks on the heterogeneous computing elements of the device. Such an algorithm, called exclusive earliest finish time (XEFT), takes into consideration the possible multiple implementation of tasks for different computing elements (e.g., a task primitive for CPU and an equivalent parallel implementation for GPU). It introduces and takes advantage of the notion of exclusive overlap between primitives to improve the load balancing. This thesis is the result of three years of research activity, during which all the incremental steps made to compose the framework have been tested on real case studie

    Architectural level delay and leakage power modelling of manufacturing process variation

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    PhD ThesisThe effect of manufacturing process variations has become a major issue regarding the estimation of circuit delay and power dissipation, and will gain more importance in the future as device scaling continues in order to satisfy market place demands for circuits with greater performance and functionality per unit area. Statistical modelling and analysis approaches have been widely used to reflect the effects of a variety of variational process parameters on system performance factor which will be described as probability density functions (PDFs). At present most of the investigations into statistical models has been limited to small circuits such as a logic gate. However, the massive size of present day electronic systems precludes the use of design techniques which consider a system to comprise these basic gates, as this level of design is very inefficient and error prone. This thesis proposes a methodology to bring the effects of process variation from transistor level up to architectural level in terms of circuit delay and leakage power dissipation. Using a first order canonical model and statistical analysis approach, a statistical cell library has been built which comprises not only the basic gate cell models, but also more complex functional blocks such as registers, FIFOs, counters, ALUs etc. Furthermore, other sensitive factors to the overall system performance, such as input signal slope, output load capacitance, different signal switching cases and transition types are also taken into account for each cell in the library, which makes it adaptive to an incremental circuit design. The proposed methodology enables an efficient analysis of process variation effects on system performance with significantly reduced computation time compared to the Monte Carlo simulation approach. As a demonstration vehicle for this technique, the delay and leakage power distributions of a 2-stage asynchronous micropipeline circuit has been simulated using this cell library. The experimental results show that the proposed method can predict the delay and leakage power distribution with less than 5% error and at least 50,000 times faster computation time compare to 5000-sample SPICE based Monte Carlo simulation. The methodology presented here for modelling process variability plays a significant role in Design for Manufacturability (DFM) by quantifying the direct impact of process variations on system performance. The advantages of being able to undertake this analysis at a high level of abstraction and thus early in the design cycle are two fold. First, if the predicted effects of process variation render the circuit performance to be outwith specification, design modifications can be readily incorporated to rectify the situation. Second, knowing what the acceptable limits of process variation are to maintain design performance within its specification, informed choices can be made regarding the implementation technology and manufacturer selected to fabricate the design
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