962 resultados para Hardware gràfic


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Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

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This thesis is a study of new design methods for allowing evolutionary algorithms to be more effectively utilised in aerospace optimisation applications where computation needs are high and computation platform space may be restrictive. It examines the applicability of special hardware computational platforms known as field programmable gate arrays and shows that with the right implementation methods they can offer significant benefits. This research is a step forward towards the advancement of efficient and highly automated aircraft systems for meeting compact physical constraints in aerospace platforms and providing effective performance speedups over traditional methods.

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The usual practice to study a large power system is through digital computer simulation. However, the impact of large scale use of small distributed generators on a power network cannot be evaluated strictly by simulation since many of these components cannot be accurately modelled. Moreover, the network complexity makes the task of practical testing on a physical network nearly impossible. This study discusses the paradigm of interfacing a real-time simulation of a power system to real-life hardware devices. This type of splitting a network into two parts and running a real-time simulation with a physical system in parallel is usually termed as power-hardware-in-the-loop (PHIL) simulation. The hardware part is driven by a voltage source converter that amplifies the signals of the simulator. In this paper, the effects of suitable control strategy on the performance of PHIL and the associated stability aspects are analysed in detail. The analyses are validated through several experimental tests using an real-time digital simulator.

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This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

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A virtual power system can be interfaced with a physical system to form a power hardware-in-the-loop (PHIL) simulation. In this scheme, the virtual system can be simulated in a fast parallel processor to provide near real-time outputs, which then can be interfaced to a physical hardware that is called the hardware under test (HuT). Stable operation of the entire system, while maintaining acceptable accuracy, is the main challenge of a PHIL simulation. In this paper, after an extended stability analysis for voltage and current type interfaces, some guidelines are provided to have a stable PHIL simulation. The presented analysis have been evaluated by performing several experimental tests using a Real Time Digital Simulator (RTDS™) and a voltage source converter (VSC). The practical test results are consistent with the proposed analysis.

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This project develops the required guidelines to assure stable and accurate operation of Power-Hardware-in-the-Loop implementations. The proposals of this research have been theoretically analyzed and practically examined using a Real-Time Digital Simulator. In this research, the interaction between software simulated power network and the physical power system has been studied. The conditions for different operating regimes have been derived and the corresponding analyses have been presented.

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This paper introduces our dedicated authenticated encryption scheme ICEPOLE. ICEPOLE is a high-speed hardware-oriented scheme, suitable for high-throughput network nodes or generally any environment where specialized hardware (such as FPGAs or ASICs) can be used to provide high data processing rates. ICEPOLE-128 (the primary ICEPOLE variant) is very fast. On the modern FPGA device Virtex 6, a basic iterative architecture of ICEPOLE reaches 41 Gbits/s, which is over 10 times faster than the equivalent implementation of AES-128-GCM. The throughput-to-area ratio is also substantially better when compared to AES-128-GCM. We have carefully examined the security of the algorithm through a range of cryptanalytic techniques and our findings indicate that ICEPOLE offers high security level.

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Hardware ventures are emerging entrepreneurial firms that create new market offerings based on development of digital devices. These ventures are important elements in the global economy but have not yet received much attention in the literature. Our interest in examining hardware ventures is specifically in the role that information system (IS) resources play in enabling them. We ask how the role of IS resources for hardware ventures can be conceptualized and develop a framework for assessment. Our framework builds on the distinction of operand and operant resources and distinguishes between two key lifecycle stages of hardware ventures: start-up and growth. We show how this framework can be used to discuss the role, nature, and use of IS for hardware ventures and outline empirical research strategies that flow from it. Our work contributes to broadening and enriching the IS field by drawing attention to its role in significant and novel phenomena.

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Grid-connected systems when put to use at the site would experience scenarios like voltage sag, voltage swell, frequency deviations and unbalance which are common in the real world grid. When these systems are tested at laboratory, these scenarios do not exist and an almost stiff voltage source is what is usually seen. But, to qualify the grid-connected systems to operate at the site, it becomes essential to test them under the grid conditions mentioned earlier. The grid simulator is a hardware that can be programmed to generate some of the typical conditions experienced by the grid-connected systems at site. It is an inverter that is controlled to act like a voltage source in series with a grid impedance. The series grid impedance is emulated virtually within the inverter control rather than through physical components, thus avoiding the losses and the need for bulky reactive components. This paper describes the design of a grid simulator. Control implementation issues are highlighted in the experimental results.

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Massively parallel SIMD computing is applied to obtain an order of magnitude improvement in the executional speed of an important algorithm in VLSI design automation. The physical design of a VLSI circuit involves logic module placement as a subtask. The paper is concerned with accelerating the well known Min-cut placement technique for logic cell placement. The inherent parallelism of the Min-cut algorithm is identified, and it is shown that a parallel machine based on the efficient execution of the placement procedure.

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The performance of a program will ultimately be limited by its serial (scalar) portion, as pointed out by Amdahl′s Law. Reported studies thus far of instruction-level parallelism have mixed data-parallel program portions with scalar program portions, often leading to contradictory and controversial results. We report an instruction-level behavioral characterization of scalar code containing minimal data-parallelism, extracted from highly vectorized programs of the PERFECT benchmark suite running on a Cray Y-MP system. We classify scalar basic blocks according to their instruction mix, characterize the data dependencies seen in each class, and, as a first step, measure the maximum intrablock instruction-level parallelism available. We observe skewed rather than balanced instruction distributions in scalar code and in individual basic block classes of scalar code; nonuniform distribution of parallelism across instruction classes; and, as expected, limited available intrablock parallelism. We identify frequently occurring data-dependence patterns and discuss new instructions to reduce latency. Toward effective scalar hardware, we study latency-pipelining trade-offs and restricted multiple instruction issue mechanisms.

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The 4ÃÂ4 discrete cosine transform is one of the most important building blocks for the emerging video coding standard, viz. H.264. The conventional implementation does some approximation to the transform matrix elements to facilitate integer arithmetic, for which hardware is suitably prepared. Though the transform coding does not involve any multiplications, quantization process requires sixteen 16-bit multiplications. The algorithm used here eliminates the process of approximation in transform coding and multiplication in the quantization process, by usage of algebraic integer coding. We propose an area-efficient implementation of the transform and quantization blocks based on the algebraic integer coding. The designs were synthesized with 90 nm TSMC CMOS technology and were also implemented on a Xilinx FPGA. The gate counts and throughput achievable in this case are 7000 and 125 Msamples/sec.

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Ensuring reliable operation over an extended period of time is one of the biggest challenges facing present day electronic systems. The increased vulnerability of the components to atmospheric particle strikes poses a big threat in attaining the reliability required for various mission critical applications. Various soft error mitigation methodologies exist to address this reliability challenge. A general solution to this problem is to arrive at a soft error mitigation methodology with an acceptable implementation overhead and error tolerance level. This implementation overhead can then be reduced by taking advantage of various derating effects like logical derating, electrical derating and timing window derating, and/or making use of application redundancy, e. g. redundancy in firmware/software executing on the so designed robust hardware. In this paper, we analyze the impact of various derating factors and show how they can be profitably employed to reduce the hardware overhead to implement a given level of soft error robustness. This analysis is performed on a set of benchmark circuits using the delayed capture methodology. Experimental results show upto 23% reduction in the hardware overhead when considering individual and combined derating factors.

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In large flexible software systems, bloat occurs in many forms, causing excess resource utilization and resource bottlenecks. This results in lost throughput and wasted joules. However, mitigating bloat is not easy; efforts are best applied where savings would be substantial. To aid this we develop an analytical model establishing the relation between bottleneck in resources, bloat, performance and power. Analyses with the model places into perspective results from the first experimental study of the power-performance implications of bloat. In the experiments we find that while bloat reduction can provide as much as 40% energy savings, the degree of impact depends on hardware and software characteristics. We confirm predictions from our model with selected results from our experimental study. Our findings show that a software-only view is inadequate when assessing the effects of bloat. The impact of bloat on physical resource usage and power should be understood for a full systems perspective to properly deploy bloat reduction solutions and reap their power-performance benefits.

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Video decoders used in emerging applications need to be flexible to handle a large variety of video formats and deliver scalable performance to handle wide variations in workloads. In this paper we propose a unified software and hardware architecture for video decoding to achieve scalable performance with flexibility. The light weight processor tiles and the reconfigurable hardware tiles in our architecture enable software and hardware implementations to co-exist, while a programmable interconnect enables dynamic interconnection of the tiles. Our process network oriented compilation flow achieves realization agnostic application partitioning and enables seamless migration across uniprocessor, multi-processor, semi hardware and full hardware implementations of a video decoder. An application quality of service aware scheduler monitors and controls the operation of the entire system. We prove the concept through a prototype of the architecture on an off-the-shelf FPGA. The FPGA prototype shows a scaling in performance from QCIF to 1080p resolutions in four discrete steps. We also demonstrate that the reconfiguration time is short enough to allow migration from one configuration to the other without any frame loss.