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检索条件"主题词=Compression algorithms"

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An efficient algorithm for lossless compression of IEEE float audio

An efficient algorithm for lossless compression of IEEE floa...

引用

Data compression Conference (DCC)

作者： F. Ghido Department of Computer Science Polytechnic University of Bucharest Romania

Audio data in the IEEE float format is used by the professional quality audio editors as the format of choice during the editing process and also for storing the intermediate results. The proposed algorithm transforms the floating-point values into integer values, in a completely portable way across architectures and compilers. The transform maintains all the important properties of the original values, such as magnitude relations, linear temporal relations and, most importantly, compressibility. It produces a sequence of integers and an additional binary stream used for lossless reconstruction of the original values. Furthermore, the proposed algorithm can be successfully applied to other areas such as medical, science and space data compression. Our algorithm obtains on average 7% better compression than the existing multimedia-aware compression algorithms, while being also faster.

关键词： Signal processing algorithms Quantization Signal to noise ratio Data compression Hardware Signal processing Phase change materials Computer science Streaming media compression algorithms

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A Highly Scalable Parallel Design for Data compression

A Highly Scalable Parallel Design for Data Compression

引用

IEEE Conference on High Performance Extreme Computing (HPEC)

作者： S. Biplab Raut AMD India Private Limited Bangalore India

ISBN: (数字)9798350387131

ISBN: (纸本)9798350387148

With ever-increasing use of digital data, many applications rely on data compression for their needs related to processing, storage and communication over the network of large volumes of data. While compression saves the memory/disk space and decreases the communication time, there is a considerable runtime spent in this process. Parallel compression algorithms and solutions that are developed to speed up the operations do not scale well on the multi-core CPUs. The data parallel schemes implemented by the prior arts are inefficient in partitioning the data and scaling the performance on the multi-core processors. Another major drawback of the existing multi-threaded compression solutions is the non-compliance to the single-threaded compression format. In this paper, we propose a set of novel and high-performance parallel compression and decompression schemes. We introduce novel designs for dynamic threading based parallel compression and random access point based parallel decompression. With our solution, we mitigate both the scaling issues on multi-core x86 CPUs and format compliance issues encountered in multi-threading the compression operations. Our test results demonstrate massive speedups by manyfolds and performance scaling never seen before on x86 CPUs especially AMD's “ZZn”-based recent processors that come with very high core counts.

关键词： Runtime Multicore processing Instruction sets Scalability Data compression Benchmark testing Parallel processing Libraries compression algorithms Digital information

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Thresholding wavelets for image compression

Thresholding wavelets for image compression

引用

compression and Complexity of Sequences Proceedings

作者： M.G. Albanesi Dipartimento di Informatica e Sistemistica University of Pavia Pavia Italy

The paper addresses the problem of thresholding wavelet coefficients in a transform-based algorithm for still image compression. Processing data before the quantization phase is a crucial step in a compression algorithm, especially in applications which require high compression ratios. In the paper, after a review on the applications of wavelets to image compression, a new solution to the problem of an accurate choice of thresholds is presented. It is based on the concept of local contrast and exploits the localization properties of wavelets and a maximization of the entropy to find the optimal threshold for the wavelet coefficients. The results are compared with standard thresholding techniques which do not include considerations about local distribution of pixel information within the image. At the end, examples of compression are given, where the algorithm includes the complete processing of transform coefficients (thresholding, quantization and coding).

关键词： Image coding Wavelet transforms Wavelet analysis Wavelet coefficients Quantization Digital filters Filter bank compression algorithms Entropy Pixel

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Energy optimization of distributed embedded processors by combined data compression and functional partitioning 03

Energy optimization of distributed embedded processors by co...

引用

IEEE International Conference on Computer-Aided Design

作者： Jinfeng Liu P.H. Chou Center for Embedded Computer Systems University of California Irvine CA USA

ISBN: (纸本)9781581137620

Transmitting compressed data can reduce inter-processor communication traffic and create new opportunities for DVS (dynamic voltage scaling) in distributed embedded systems. However, data compression alone may not be effective unless coordinated with functional partitioning. This paper presents a dynamic programming technique that combines compression and functional partitioning to minimize energy on multiple voltage-scalable processors running pipelined data-regular applications under performance constraints. Our algorithm computes the optimal functional partitioning, CPU speed for each node, and their respective compression ratios. We validate the algorithm's effectiveness on a real distributed embedded system running an image processing algorithm.

关键词： Data compression Voltage control Dynamic voltage scaling Image coding Embedded system Partitioning algorithms Parallel processing compression algorithms Embedded computing Message passing

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Data compression Scheme For Archiving Of Adeos Data

Data Compression Scheme For Archiving Of Adeos Data

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： K. Arai EARTH OBSERVATION CENTER National Space Development Agency of Japan Saitama Japan

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Symbol mapping and context filtering for lossless image compression

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IEEE International Conference on Image Processing

作者： Guang Deng Department of Electronic Engineering La Trobe University Bundoora VIC Australia

ISBN: (纸本)0818688211

Key building blocks of lossless image compression algorithms include adaptive prediction, context-based error feedback and adaptive entropy coding. This paper presents a new algorithm which includes two other building blocks-symbol mapping and context filtering. Experimental results show that the compression performance of the proposed algorithm is very close to that of CALIC and is better than that of LOGO and S+P. It is different from CALIC in the following aspects: (1) an adaptive median-FIR predictor, (2) a new error representation scheme using symbol mapping, (3) a different context calculation scheme for the prediction error, and (4) a new context filtering scheme.

关键词： Filtering Image coding Quantization Feedback Entropy coding Decoding Prediction algorithms Biomedical imaging compression algorithms Adaptive filters

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On strongly sequential compression of sources with abrupt changes in statistics

On strongly sequential compression of sources with abrupt ch...

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IEEE International Conference on Communications (ICC)

作者： G.I. Shamir The Department of Electrical Engineering University of Notre Dame Notre Dame IN USA

An asymptotically optimal low-complexity strongly sequential compression scheme is proposed for universal lossless coding of memoryless sources with piecewise stationary abruptly changing statistics. The scheme is shown to achieve the lower bound for this universal coding problem even in a strongly sequential regime, where the horizon (i.e., the length of the data sequence to be encoded) is unknown when the algorithm starts to compress the data. Simulation results support the analytical results.

关键词： Statistics Cities and towns Analytical models compression algorithms NASA Gas insulated transmission lines Computational complexity Arithmetic

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compression system architecture based on Lempel-Ziv algorithm with sliding window history buffer

Compression system architecture based on Lempel-Ziv algorith...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science

作者： A. Melnyk R. Bachinsky Lviv Polytechnic National University Lviv Ukraine

Base requirements to compression system and compression system architecture are proposed. compression processor architecture, based on random access memory is proposed in this chapter. One of the most important advantages of proposed architecture is its possibility to realize it on FPGA, that simplifies testing, reduces designing time and time for putting the system into operation.

关键词： History compression algorithms Field programmable gate arrays Data communication Minimization methods Data analysis Algorithm design and analysis Switches Hardware Random access memory

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A pyramid algorithm for fast fractal image compression

A pyramid algorithm for fast fractal image compression

引用

IEEE International Conference on Image Processing

作者： H. Lin A.N. Venetsanopoulos Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada University of Toronto Toronto ON CA Dept. of Electr. & Comput. Eng. Toronto Univ. Ont. Canada

We present a fast fractal image encoding algorithm which is based on a refinement of the fractal code from an initial coarse level of the pyramid. The pyramid search algorithm is quasi-optimal in terms of minimizing the mean square error. Assuming that the distribution of the matching error is described by an independent, identically distributed (i.i.d.) Laplacian random process, we derive the threshold sequence for the objective function in each pyramidal level. The computational efficiency depends on the depth of the pyramid and the search step size and could be improved up to two orders of magnitude compared with the full search of the original image.

关键词： Fractals Image coding Image resolution Electronic mail Mean square error methods Laplace equations Random processes Computational efficiency Redundancy compression algorithms

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An FPGA-Based Top-K Gradient compression Accelerator for Distributed Deep Learning Training

An FPGA-Based Top-K Gradient Compression Accelerator for Dis...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Ziyao Wang Jiayu Zhang Kunyue Li Jialei Sun Feng Dong Ke Chen Yong Qiao Jianfei Jiang National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai China Beijing iQlYI Science & Technology Co.. Ltd.. Shanghai China

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

In distributed neural network training with multiple machines and devices, communication limitations often create efficiency bottlenecks due to the frequent exchange of model parameters and gradient information between computing nodes. This paper proposes an FPGA-based accelerator leveraging the gradient compression algorithm Top-K sparsification, which enhances performance by offloading computationally intensive compression operations to the FPGA. Experimental results demonstrate that the FPGA compression accelerator designed in this study achieves superior computing performance and compression efficiency compared to compression algorithms implemented on CPUs and GPUs. Specifically, the FPGA compresses the same amount of data 3.3-3.7 times faster than parallel solutions on CPUs and 1.3-1.8 times faster than on GPUs.

关键词： Training Performance evaluation Integrated circuit technology Deep learning Computational modeling Neural networks Field programmable gate arrays compression algorithms

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