Main digital calibration techniques for interstage gain nonlinearity in low-power, high-speed pipelined analog to digital converter (ADC) designs published in recent years are overviewed in this paper. Two novel digit...
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Main digital calibration techniques for interstage gain nonlinearity in low-power, high-speed pipelined analog to digital converter (ADC) designs published in recent years are overviewed in this paper. Two novel digital calibration techniques are proposed and compared with other main digital calibration techniques in terms of the efficiency, convergence time, complexity, limitations, and cost.
To play the advantages of a variety of remote sensing data, the application of remote sensing image fusion is a very important choice. Remote sensing image fusion is large in computing capacity and time-consuming, and...
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To play the advantages of a variety of remote sensing data, the application of remote sensing image fusion is a very important choice. Remote sensing image fusion is large in computing capacity and time-consuming, and withthe development of modern remote sensing technology, the amount of various remote sensing data obtained is larger and larger, how to fuse remote sensing image quickly and accurately and getting useful information is becoming more and more urgent especially in some remote sensing applications such as disaster prevention and relief quick, etc. Based on the advantage of wavelet transform in information processing and the advantage of parallel computing in high-performance computing, a parallel fusion algorithm of remote sensing images based on wavelet transform is proposed in the paper. In the method, based on parallel computing, the low-frequency components of wavelet decomposition are fused withthe fusion rule based on the feature matching, and the high-frequency components of wavelet decomposition are fused withthe fusion rule based on the sub region variance. then the low-frequency components and the high-frequency components after fusion are processing withthe inverse wavelet transform, and the fused image is gotten. the result shows that the proposed method can get better fusion results and faster computing speed.
We develop a parallel algorithm, by using CUDA, for calculating the concentration of multifunctional magnetic nanoparticles in capillaries under the influences of magnetic force, blood flow and diffusion process. the ...
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ISBN:
(纸本)9781479908059
We develop a parallel algorithm, by using CUDA, for calculating the concentration of multifunctional magnetic nanoparticles in capillaries under the influences of magnetic force, blood flow and diffusion process. the task of computing particle, concentration on the considered plane is distributed to computational threads. the continuity equation describing the time rate of change of the multifunctional particle concentration in each small element on the considered plane is solved via the explicit finite different method. the simulation results show the distributions of particle concentration on the focused plane in the blood vessel which are useful visualization for the biomedical researchers. the performance of parallel computing is also examined.
In this paper we present an integral image algorithm that can run in real-time on a Graphics processing Unit (GPU). Our system exploits the parallelisms in computation via the NVIDA CUDA programming model, which is a ...
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ISBN:
(纸本)9781467364591
In this paper we present an integral image algorithm that can run in real-time on a Graphics processing Unit (GPU). Our system exploits the parallelisms in computation via the NVIDA CUDA programming model, which is a software platform for solving non-graphics problems in a massively parallel high performance fashion. We compare the performance of the parallel approach running on the GPU withthe sequential CPU implementation across a range of image sizes.
In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such ...
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ISBN:
(纸本)9781479909735
In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such as link prediction, friend recommendation and personalized searching. Personalized Page Rank, which ranks nodes according to the probabilities that a random walk starting from a personalized node stops at all nodes, is one of the most popular metrics for influence analysis. In this paper, we study the problem of inverse influence in online social networks. Different from Personalized Page Rank, the inverse influence for a personalized node ranks nodes according to the probabilities that all nodes stop at the personalized node in limited steps. We propose two computation models for inverse influence, i.e., the random walk based and the path based. Both of the models have high computation complexity, and cannot be used in large graphs, so we propose a Monte Carlo based approximation algorithm. Experiments from synthetic and real world datasets show that, our algorithm has equivalent or even better accuracy than related researches in link prediction, and thus can be used in friend recommendation in online social networks.
Currently, higher resolutions and faster frame rates are more and more demanded in real time video application. Consequently, encoder complexity and performance are the main penalties for such requirements. the emergi...
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ISBN:
(纸本)9781467364591
Currently, higher resolutions and faster frame rates are more and more demanded in real time video application. Consequently, encoder complexity and performance are the main penalties for such requirements. the emerging Multiprocessor System on Chip (MPSoC) architecture is a promising way for following the evolving video encoding applications, which can overcome the limitation of real-time processing with a single processor. thus parallel computing for H.264/AVC encoder on multiprocessor is becoming a major research point that can resolve real time constraints. We contribute to this challenge by proposing MPSoC architecture for the intra prediction module, which is an important part of the H.264/AVC video encoder, using data level parallelism (DLP) approach. In this paper, we present an efficient partitioning of data for parallelprocessing for intra prediction; this approach is tested and evaluated on an open platform for virtual prototyping (SoCLiB). Experimental results show a gain of 74% in encoding speed when using four processors, and enabling minimum memory size and surface of MPSoC. Furthermore, our results highlight the relationship between the number of processors and the encoding run time.
this paper presents an implementation of H.264 decoder on a 24-core processor. H.264 provides many new features that require complex computations compared to the previous video coding standards, thus introduces great ...
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this paper presents an implementation of H.264 decoder on a 24-core processor. H.264 provides many new features that require complex computations compared to the previous video coding standards, thus introduces great challenges to implement it efficiently. Multiprocessor emerges as a good solution because it provides high parallelism rather than high clock frequency to improve the system performance energy efficiently. By utilizing hardware accelerators and different levels of parallelism mechanism including function-level parallelism, data-level parallelism and thread-level parallelism, our proposed H.264 decoder shows a throughput of 58fps@720p at 800MHz with 780mW power dissipation.
Geometric correction is a practical and effective barrel distortion correction method. It mainly consists of two stages: the first stage is to take coordinates mapping from distortion image to correction image, the se...
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Geometric correction is a practical and effective barrel distortion correction method. It mainly consists of two stages: the first stage is to take coordinates mapping from distortion image to correction image, the second stage is bilinear interpolation. It involves a certain amount of calculation, and the larger the image is, the more the quantity of calculation is. What's more, the processing speed of geometric correction implemented on central processing unit (CPU) can't meet the need of high-speed in real-time application fields. Compared with serial processing pipeline of CPU, graphics processing unit (GPU) has special parallelprocessing pipeline which is suitable and fast for mass data calculation in parallel. therefore, it can provide an implementation of geometric correction on GPU with considerable acceleration effect. the paper proposes an implementation of geometric correction on GPU by using open graphics library (OpenGL) and graphics library shading language (GLSL) for portability. the experiment results show that the full execution performance of the implementation on GPU is over 190 times speedup of that completely on CPU at most, which obtains a high-speed processing effect.
Uncountable loops (such as while loops in C) and if-conditions are some of the most common constructs in programming. While-loops are widely used to determine the convergence in linear algebra algorithms or goal findi...
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Uncountable loops (such as while loops in C) and if-conditions are some of the most common constructs in programming. While-loops are widely used to determine the convergence in linear algebra algorithms or goal finding problems from graph algorithms, to name a few. In general while-loops are used whenever the loop iteration space, the number of iterations a loop executes is unknown. Usually in while-loops, the execution of the next iteration is decided inside the current loop iteration (i.e. the execution of iteration i depends on the values computed in iteration i-1). this precludes their parallel execution in today's ubiquitous multi-core architectures. In this paper a technique to speculatively create parallel tasks from the next iterations before the current one completes is proposed. If consecutive loop-iterations are only control dependent, then multiple iterations can be executed simultaneously; later in the execution path, the runtime system will decide to either commit the results of such speculatively executed iterations or undo the changes made by them. Data dependences within or between non-speculative and speculative work are honored to guarantee correctness. the proposed technique is implemented in SMPSs, a task-based dataflow programming model for shared-memory multiprocessor architectures. the approach is evaluated on a set of applications from graph algorithms and linear algebra. Results are promising with an average increase in the speedup of 1.2x with 16 threads when compared to non speculative execution of the applications. the increase in the speedup is significant, since the performance gain is achieved over an already parallelized version of the benchmarks.
this paper presents a real-time stereo video processing system based on FPGA. the system takes rectification and histogram equalization as its pre-processing, and the depth detection of this system is using generalize...
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this paper presents a real-time stereo video processing system based on FPGA. the system takes rectification and histogram equalization as its pre-processing, and the depth detection of this system is using generalized census transform and block matching method. Withthe help of on-line generated projected pattern by the pattern controller inside FPGA, this system can be used in various environments. the median filter is used as the post-processing step of depth map. In comparison to the software solution method, this system takes the advantage of the parallel nature of FPGA and got higher speed in generating the depth map. therefore, it can be applied to the applications demanded for better performance.
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