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检索条件"主题词=Compression Algorithms"

共 2074 条记录，以下是641-650 订阅

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ZIP-IO: Architecture for application-specific compression of Big Data

ZIP-IO: Architecture for application-specific compression of...

引用

IEEE International Conference on Field-Programmable Technology (FPT)

作者： Sang Woo Jun Kermin E. Fleming Michael Adler Joel Emer Computation Structures Group Massachusetts Institute of Technology VSSAD Group Intel Corporation

We have entered the “Big Data” age: scaling of networks and sensors has led to exponentially increasing amounts of data. compression is an effective way to deal with many of these large data sets, and application-specific compression algorithms have become popular in problems with large working sets. Unfortunately, these compression algorithms are often computationally difficult and can result in application-level slow-down when implemented in software. To address this issue, we investigate ZIP-IO, a framework for FPGA-accelerated compression. Using this system we demonstrate that an unmodified industrial software workload can be accelerated 3× while simultaneously achieving more than 1000× compression in its data set.

关键词： Field programmable gate arrays Hardware compression algorithms Computational modeling Computer architecture Operating systems

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Applying Radiation Hardening by Software to Fast Lossless compression Prediction on FPGAs

Applying Radiation Hardening by Software to Fast Lossless Co...

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IEEE Aerospace Conference

作者： Andrew G. Schmidt John Paul Walters Kenneth M. Zick Matthew French Didier Keymeulen Nazeeh Aranki Matthew Klimesh Aaron Kiely Information Sciences Institute University of Southern California Jet Propulsion Laboratory California Institute of Technology

ISBN: (纸本)9781457705564

As scientists endeavor to learn more about the world's ecosystems, engineers are pushed to develop more sophisticated instruments. With these advancements comes an increase in the amount of data generated. For satellite based instruments the additional data requires sufficient bandwidth be available to transmit the data. Alternatively, compression algorithms can be employed to reduce the bandwidth requirements. This work is motivated by the proposed HyspIRI mission, which includes two imaging spectrometers measuring from visible to short wave infrared (VSWIR) and thermal infrared (TIR) that saturate the projected bandwidth allocations. We present a novel investigation into the capability of using FPGAs integrated with embedded PowerPC processors to adequately perform the predictor function of the Fast Lossless (FL) compression algorithm for multispectral and hyperspectral imagery. Furthermore, our design includes a multi-PowerPC implementation which incorporates recently developed Radiation Hardening by Software (RHBSW) techniques to provide software-based fault tolerance to commercial FPGA devices. Our results show low performance overhead (4-8percent) while achieving a speedup of 1.97X when utilizing both PowerPCs. Finally, the evaluation of the proposed system includes resource utilization, performance metrics, and an analysis of the vulnerability to Single Event Upsets (SEU) through the use of a hardware based fault injector.

关键词： Radiation hardening Field programmable gate arrays compression algorithms computer software bandwidth allocation Single event upsets lossless compression Speeding Fault tolerance Engineers imaging spectrometers

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Content dependent effect of H.264/AVC video compression on CT image quality

Content dependent effect of H.264/AVC video compression on C...

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International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Lawrence W.C. Chan Derek So Yolanda Shiu David Sin Ben Chan Tao Chan Department of Health Technology and Informatics Hong Kong Polytechnic University Hong Kong China Department of diagnostic radiology Medical Imaging Department Union Hospital University of Hong Kong Hong Kong China

Image compression helps perfecting the utilization of limited storage and network resources for medical imaging. In many recent studies, H.264 video compression was deemed to be a promising option. This study was the first of its kind in studying the effect of H.264 compression on the image quality of the CT abdominal images acquired in 12-bit density resolution. In this study, 67 sets of abdominal CT scans were used for quantitative image quality analysis, and indicated that the H.264 algorithm worked on a content dependent manner, especially at high compression levels.

关键词： Image coding Image quality Computed tomography PSNR Diseases Biomedical imaging compression algorithms

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Approaching optimal compression with fast update for large scale routing tables 12

Approaching optimal compression with fast update for large s...

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International Workshop on Quality of Service

作者： Tong Yang Bo Yuan Shenjiang Zhang Ting Zhang Ruian Duan Yi Wang Bin Liu Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781467312981

With the fast development of Internet, the size of routing tables in the backbone routers keeps a rapid growth in recent years. An effective solution to control the memory occupation of the ever-increased huge routing table is the Forwarding Information Base (FIB) compression. Existing optimal FIB compression algorithm ORTC suffers from high computational complexity and poor update performance, due to the loss of essential structure information during its compression process. To address this problem, we present two suboptimal FIB compression algorithms - EAR-fast and EAR-slow, respectively, based on our proposed Election and Representative (EAR) algorithm which is an optimal FIB compression algorithm. The two suboptimal algorithms preserve the structure information, and support fast incremental updates while reducing computational complexity. Experiments on an 18-month real data set show that compared with ORTC, the proposed EAR-fast algorithm requires only 9.8% compression time and 37.7% memory space, but supports faster update while prolonging the recompression interval remarkably. All these performance advantages come at a cost of merely a 1.5% loss in compression ratio compared with the theoretical optimal ratio.

关键词： Nominations and elections Ear Routing compression algorithms Solids Complexity theory Algorithm design and analysis

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Multi-channel EEG compression based on 3D decompositions

Multi-channel EEG compression based on 3D decompositions

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Justin Dauwels Srinivasan K. Ramasubba Reddy M. Andrzej Cichocki Nanyang Technological University Singapore Indian Institute of Technology Madras Chennai India Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Wako Japan RIKEN BSI Laboratory for Advanced Brain Signal Processing Wako-Shi Japan

Various compression algorithms for multi-channel electroencephalograms (EEG) are proposed and compared. The multi-channel EEG is represented as a three-way tensor (or 3D volume) to exploit both spatial and temporal correlations efficiently. A general two-stage coding framework is developed for multi-channel EEG compression. In the first stage, we consider (i) wavelet-based volumetric coding; (ii) energy-based lossless compression of wavelet subbands; (iii) tensor decomposition based coding. In the second stage, the residual is quantized and coded. Through such two-stage approach, one can control the maximum error (worst-case distortion). Numerical results for a standard EEG data set show that tensor-based coding achieves lower worst-case error and comparable average error than the wavelet- and energy-based schemes.

关键词： Electroencephalography Encoding Tensile stress Correlation Image coding Wavelet transforms compression algorithms

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Linear compression of Digital Ink via Point Selection

Linear Compression of Digital Ink via Point Selection

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IAPR International Workshop on Document Analysis Systems, DAS

作者： Vadim Mazalov Stephen M. Watt Ontario Research Centre for Computer Algebra Department of Computer Science University of Western Ontario London Canada

We present a method to compress digital ink based on piecewise-linear approximation within a given error threshold. The objective is to achieve good compression ratio with very fast execution. The method is especially effective on types of handwriting that have large portions with nearly linear parts, e.g. hand drawn geometric objects. We compare this method with an enhanced version of our earlier functional approximation method, finding the new technique to give slightly worse compression while performing significantly faster. This suggests the presented method can be used in applications where speed of processing is of higher priority than the compression ratio.

关键词： Ink Chebyshev approximation Approximation algorithms Linear approximation compression algorithms Vectors

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An ECG compression Algorithm Based on Gradient Difference for Body Sensor Networks

An ECG Compression Algorithm Based on Gradient Difference fo...

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International Conference on Biomedical Engineering and Biotechnology (iCBEB)

作者： Yuangui Zhang Y.T. Zhang Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Key Laboratory for Health Informatics Chinese Academy of Sciences Shenzhen China Joint Research Centre for Biomedical Engineering Department of Electronic Engineering The Chinese Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Key Laboratory for Health Informatics Chinese Academy of Science University of Hong Kong Sha Tin Hong Kong China

We propose a novel scheme for ECG compression based on Gradient difference used in BSN. As a newly emerged application, BSN can continuously monitor the patients' physiological signal without hindering their everyday life, however, it has some constraints, namely, size, power, capability of storage and computation. ECG is a nontrivial signal collected by BSN, continuous collection will bring huge data flow which is a burden both to sensor nodes and central node, therefore we have to do some compression to relieve the burden. As the constraints exist, most of the traditional algorithms are not adaptive enough, we need a simple, real-time and effective approach. This paper introduces an approach to meet those requirements, by conducting various experiments, we found that this approach can effectively compress ECG signal and meanwhile keep a good fidelity of the reconstructed signal, to prove that, we did some compare between our approach and traditional ones. Yet, this algorithm has not been tested on the clinical ECG signals and there is still room for the performance improvement.

关键词： Electrocardiography Redundancy Biomedical monitoring compression algorithms Data compression Biomedical engineering Monitoring

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compression scheme for increasing the lifetime of wireless intelligent sensor networks

Compression scheme for increasing the lifetime of wireless i...

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European Signal Processing Conference (EUSIPCO)

作者： Dragos Ioan Sacaleanu Rodica Stoian Dragos Mihai Ofrim Nikos Deligiannis Faculty of Electronics Telecommunications and Information Technology Universitatea Politehnica din Bucuresti Bucharest Romania Department of Electronics and Informatics Vrije Universiteit Brussel Brussels Belgium Interdisciplinary Institute for BroadBand Technology Ghent Belgium

Wireless intelligent sensor networks (WISN) are characterized by the ability of self-organization and autocoordination for long periods of time. In most cases, the limitation of time function is given by the energy supply of the sensors. Taking into account that the greatest amount of energy is spent in transmission, many studies are concentrated on minimizing the amount of transmitted bits. In order to perform this, data compression algorithms are introduced in data processing. This paper presents a scheme that combines a new extrapolation prediction algorithm and a simple Huffman compression algorithm in order to prolong the lifetime of the WISN. Compared with other data compression schemes, the new scheme has obtained better experimental results in terms of number of bits transmitted and compression ratio.

关键词： Prediction algorithms Heuristic algorithms Sensors Wireless sensor networks Data compression Extrapolation compression algorithms

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compression of GPS trajectories using optimized approximation

Compression of GPS trajectories using optimized approximatio...

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International Conference on Pattern Recognition

作者： Minjie Chen Mantao Xu Pasi Fränti University of Eastern Finland Finland Shanghai Dianji University China

ISBN: (纸本)9781467322164

A large number of GPS trajectories, which include users' spatial and temporal information, are collected by geo-positioning mobile phones in recent years. The massive volumes of trajectory data bring about heavy burdens for both network transmission and data storage. To overcome these difficulties, GPS trajectory compression algorithm (GTC) was proposed recently that optimizes both the data reduction by trajectory simplification and the coding procedure using the quantized data. In this paper, instead of using greedy solution in GTC algorithm, the approximation process is optimized jointly with the encoding step via dynamic programming. In addition, Bayes' theorem is applied to improve the robustness of probability estimation for encoded values. The proposed solution has the same time complexity with GTC algorithm in the decoding procedure and experimental results show that its bitrate is around 80% comparing with GTC algorithm.

关键词： Trajectory Global Positioning System Encoding Approximation methods Image coding Time complexity compression algorithms

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Assessing the Impact of Network compression on Molecular Dynamics and Finite Element Methods

Assessing the Impact of Network Compression on Molecular Dyn...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Branimir Dickov Miquel Pericàs Guillaume Houzeaux Nacho Navarro Eduard Ayguadé Universitat Politècnica de Catalunya Spain Barcelona Supercomputing Center Spain Tokyo Institute of Technology Japan

Efficient communication in parallel applications is one of the main challenges for the scalability of supercomputers, both in weak and strong scaling environments. In the past, several compression techniques have been proposed as a way to improve the performance and scalability of parallel applications. Those works have shown significant speed-ups when applying compressors to the MPI transfers of certain algorithmic kernels. However, these techniques have not seen widespread adoption in current supercomputers. This paper evaluates the bottlenecks of network compression that have precluded their generalized adoption in HPC environments. In order to evaluate their impact on real applications we integrated multiple MPI compression schemes into two production applications: a computational mechanics code dominated by point-to-point communication, and a molecular dynamics code dominated by collective communications. While the applications observe some improvements when applying aggressive lossy compression schemes on systems ranging from 4 to 256 processors, the overall results seem to contradict earlier research. We conclude that HPC data traffic tends to be too statistically random to be captured by general lossless compressors, and that the size of MPI message is most often not the limiting component of these communication-bound applications. We also observed that aggressive lossy compression worked well and did not distort the results of the evaluated applications. This suggests that reducing network bandwidth in conjunction with message compression may be an interesting technique to increase energy efficiency in HPC systems.

关键词： Program processors Kernel Compressors compression algorithms Accuracy Bandwidth Scalability

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