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Data compression Conference (DCC)

作者： Satoshi Yoshida Takuya Kida Graduate School of Information Science and Technology Hokkaido University Sapporo Japan

Summary form only given. We address the problem of improving variable-length-to-fixed-length codes (VF codes). A VF code is an encoding scheme that uses a fixed-length code, and thus, one can easily access the compressed data. However, conventional VF codes usually have an inferior compression ratio to that of variable-length codes. Although a method proposed by T. Uemura et al. in 2010 achieves a good compression ratio comparable to that of gzip, it is very time consuming. In this study, we propose a new VF coding method that applies a fixed-length code to the set of rules extracted by the Re-Pair algorithm, proposed by N. J. Larsson and A. Moffat in 1999. The Re-Pair algorithm is a simple off-line grammar-based compression method that has good compression-ratio performance with moderate compression speed. Moreover, we present several experimental results to show that the proposed coding is superior to the existing VF coding.

关键词： Pattern matching Encoding Educational institutions Data compression Information science compression algorithms Workstations

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Development of high performance wireless sensor node for acoustic applications

Development of high performance wireless sensor node for aco...

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IEEE International Conference on Green High Performance Computing (ICGHPC)

作者： A Arul Prabahar Centre for Development of Advanced Computing Juhu Maharashtra IN

This paper describes a design of wireless sensor network node (WSN node) for the purpose of voice based applications. For implementing voice based WSN, wireless sensor nodes should be capable of capturing voice, processing it and transmitting it over RF (Radio Frequency) channel. Common WSN applications handle few bytes of data over wireless network. Acoustic WSN applications deal with high data rate voice. Acoustic WSN applications require high performance WSN nodes to accomplish capturing and processing voice. This paper explains how to make high performance WSN nodes by incorporating Digital Signal Processing (DSP) chip with the WSN node and how to implement suitable speech processing algorithm on it. The bottle neck arisen due to usage of DSP chip on WSN node is high power consumption. The techniques which are adopted to reduce the power consumption of DSP chip are described in this paper. The design of hardware is based on ultra low power DSP chip to improve the battery operating time of the WSN node.

关键词： Wireless sensor networks Digital signal processing Speech Batteries Speech coding compression algorithms Codecs

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Saving Time in a Program Robustness Evaluation

Saving Time in a Program Robustness Evaluation

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Joao Gramacho Dolores Rexachs Emilio Luque Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona Barcelona Spain

ISBN: (纸本)9781479914449

The risk of having a program execution corrupted by transient faults is growing as computer processors are using more transistors, are becoming denser and are operating at lower voltages. This risk is multiplied when we take into account High Performance Computing with its hundreds or thousands of processors working together to solve a single problem. To evaluate how program executions behave in presence of transient faults we have proposed the concept of robustness against transient faults. This concept can be used to determine the more significant parts of a program with respect to the risk of misbehavior by transient faults for further study of improvement. The robustness concept can also be used as a metric to compare different approaches applied to a program to make it less likely of producing corrupted results. In this work we present why and how is possible to simplify a fraction of a program's robustness by taking into account the repetition of sequences of instructions. The simplified analysis obtains the exact same result as a full program robustness evaluation (exhaustively and without estimations). By simplifying the analysis we were able to reduce in up to 192 times our previously published robustness analysis time and also were able to evaluate larger programs in feasible time (unimaginable by using executions in a fault injection capable environment).

关键词： Robustness Transient analysis Registers Program processors Computer architecture compression algorithms Absorption

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Dynamic-CoMPI: dynamic optimization techniques for MPI parallel applications

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JOURNAL OF SUPERCOMPUTING 2012年第1期59卷 361-391页

作者： Filgueira, Rosa Carretero, Jesus Singh, David E. Calderon, Alejandro Nunez, Alberto Univ Carlos III Madrid Dept Comp Sci Madrid Spain

This work presents an optimization of MPI communications, called Dynamic-CoMPI, which uses two techniques in order to reduce the impact of communications and non-contiguous I/O requests in parallel applications. These techniques are independent of the application and complementaries to each other. The first technique is an optimization of the Two-Phase collective I/O technique from ROMIO, called Locality aware strategy for Two-Phase I/O (LA-Two-Phase I/O). In order to increase the locality of the file accesses, LA-Two-Phase I/O employs the Linear Assignment Problem (LAP) for finding an optimal I/O data communication schedule. The main purpose of this technique is the reduction of the number of communications involved in the I/O collective operation. The second technique, called Adaptive-CoMPI, is based on run-time compression of MPI messages exchanged by applications. Both techniques can be applied on every application, because both of them are transparent for the users. Dynamic-CoMPI has been validated by using several MPI benchmarks and real HPC applications. The results show that, for many of the considered scenarios, important reductions in the execution time are achieved by reducing the size and the number of the messages. Additional benefits of our approach are the reduction of the total communication time and the network contention, thus enhancing, not only performance, but also scalability.

关键词： MPI library Parallel techniques Clusters architectures compression algorithms Collective I/O Adaptive systems Heuristics

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Lossless Embedded compression Algorithm with Context-based Error Compensation for Video Application

Lossless Embedded Compression Algorithm with Context-based E...

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IEEE 16th International Symposium on Consumer Electronics (ISCE)

作者： Jeong, Hyerim Kim, Jaehyun Lee, Kyohyuk Yoo, Kiwon Kim, Jaemoon Samsung Elect DMC R&D Ctr Suwon South Korea

ISBN: (纸本)9781467313568

With the increase of image resolution in video application, the memory bandwidth is a critical problem in video coding. An embedded compression algorithm is a technique that can compress the frame data when stored in memory. It is possible to reduce memory requirements. In this paper, we propose a lossless embedded compression algorithm with context-based error compensation to reduce the memory bandwidth requirement. Experimental results have shown at least 50% memory bandwidth reduction on average and the data reduction ratio of the proposed algorithm is up to 5% higher than previously proposed lossless embedded compression algorithm [2].

关键词： compression algorithms Error compensation memory bandwidth image resolution Lossless embedding Videotapes deceleration rate memory requirements

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Learning Based Screen Image compression

Learning Based Screen Image Compression

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14th IEEE International Workshop on Multimedia Signal Processing (MMSP)

作者： Yang, Huan Lin, Weisi Deng, Chenwei Nanyang Technol Univ Sch Comp Engn Singapore Singapore

ISBN: (纸本)9781467345729

There are usually two components in computer screen images: textual and pictorial parts. The pictorial part can be compressed efficiently by classical coding approaches (e. g. JPEG, JPEG2000), while the compression of the textual part is still far away from being satisfactory for the reason that the textual content is usually of high-frequency. In this paper, a learning approach is used to construct a tailored dictionary for text representation. Based on the learned dictionary, a novel screen image compression algorithm is proposed through adopting different basis functions for the textual and pictorial components respectively. The screen images are firstly segmented into textual and pictorial parts. Then we employ traditional discrete cosine transformation (DCT) to facilitate the compression of pictorial part, while the learned dictionary is used to represent the textual part in screen images. Experimental results demonstrate the effectiveness of the proposed compression algorithm.

关键词： Screen text representation compression algorithms Dictionaries as Topic Image compression Data compression JPEG compression image compression algorithm High frequency images

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A High-Performance FPGA-Based Implementation of the LZSS compression Algorithm

A High-Performance FPGA-Based Implementation of the LZSS Com...

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26th IEEE International Parallel and Distributed Processing Symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Shcherbakov, Ivan Weis, Christian Wehn, Norbert TU Kaiserslautern Microelect Syst Design Res Grp Kaiserslautern Germany

ISBN: (纸本)9780769546766

The increasing growth of embedded networking applications has created a demand for high-performance logging systems capable of storing huge amounts of high-bandwidth, typically redundant data. An efficient way of maximizing the logger performance is doing a real-time compression of the logged stream. In this paper we present a flexible high-performance implementation of the LZSS compression algorithm capable of processing up to 50 MB/s on a Virtex-5 FPGA chip. We exploit the independently addressable dual-port block RAMs inside the FPGA chip to achieve an average performance of 2 clock cycles per byte. To make the compressed stream compatible with the ZLib library [1] we encode the LZSS algorithm output using a fixed Huffman table defined by the Deflate specification [2]. We also demonstrate how changing the amount of memory allocated to various internal tables impacts the performance and compression ratio. Finally, we provide a cycle-accurate estimation tool that allows finding a trade-off between FPGA resource utilization, compression ratio and performance for a specific data sample.

关键词： compression algorithms compression ratio Field programmable gate arrays average performance Growth acceleration Time compression Real time compression

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A Zerotree Coding for compression of ECG Signal Using EZW and SPIHT

A Zerotree Coding for Compression of ECG Signal Using EZW an...

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38th Annual Conference on IEEE-Industrial-Electronics-Society (IECON )

作者： Ktata, S. Mahjoubi, H. Univ Tunis El Manar Higher Inst Med Technol Biophys & Med Technol Res Lab Tunis 1006 Tunisia

ISBN: (纸本)9781467324212

Biomedical waveforms, such as electrocardiogram (ECG), always posses a lot of important clinical information in medicine and are usually recorded in a long period of time in the application of telemedicine. Due to the huge amount of data to compress the ECG is vital. This paper evaluates the compression performance and characteristics of zerotree coding compression schemes of ECG applications. Two methods, namely the Embedded Zerotree Wavelet (EZW) and the Set Partitioning In Hierarchical Tree (SPIHT) are proposed. The EZW is one of the first algorithms to show the full power of wavelet based image compression. The SPIHT algorithm is a highly refined version of the EZW algorithm. EZW and SPIHT have achieved notable success in still image coding. We modified these algorithms for applied it to compression of ECG data. Both methodologies were evaluated using the percent root mean square difference (PRD) and the compression Ratio (CR). Theoretical results are contrasted with a simulation study with actual ECG signals from MIT-BIH arrhythmia database. The simulation results show that the both methods achieve a very significant improvement in the performances of compression ratio and error measurement for ECG, as compared with some other compression methods.

关键词： compression algorithms Electrocardiogram Discrete Wavelet transforms EZW SPIHT

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Memory Efficient Lossless compression of Image Sequences with JPEG-LS and Temporal Prediction

Memory Efficient Lossless Compression of Image Sequences wit...

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29th Picture Coding Symposium (PCS)

作者： Wang, Zhe Chanda, Debasish Simon, Sven Richter, Thomas Univ Stuttgart Dept Parallel Syst Univ Str 38 D-70569 Stuttgart Germany Univ Stuttgart RUS Comp Ctr D-70550 Stuttgart Germany

ISBN: (纸本)9781457720482

In this paper, a lossless encoder for image sequences based on JPEG-LS defined for still images with temporal-extended prediction and context modeling is proposed. As embedded systems are one important field of application of the codec, on-line lossy reference frame compression is used to reduce the encoder's memory requirement. Variations of the pixel values in the reference frame due to lossy compression are acceptable since the predictor provides only estimations of the pixel values being encoded in the current frame. Larger variations decrease the final lossless compression performance of the encoder such that a trade-off between the memory requirement and the overall compression ratio is required. Different compression algorithms for the reference frame, including JPEG, JPEG 2000 and near-lossless JPEG-LS, and their impacts on the memory requirement and the overall lossless compression ratio have been studied. Experimental results show 9.6% or more gain in lossless compression ratio compared to applying the standard JPEG-LS frame-by-frame and 80% reduction in the encoder buffer size compared to storing the uncompressed reference frame.

关键词： REFERENCE FRAMES lossless compression memory requirements ENCODER image sequences compression ratio compression algorithms Context modeling JPEG lossy compression Still images codecs

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Kronecker Compressive Sensing

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2012年第2期21卷 494-504页

作者： Duarte, Marco F. Baraniuk, Richard G. Rice Univ Dept Elect & Comp Engn Houston TX 77005 USA

Compressive sensing (CS) is an emerging approach for the acquisition of signals having a sparse or compressible representation in some basis. While the CS literature has mostly focused on problems involving 1-D signals and 2-D images, many important applications involve multidimensional signals;the construction of sparsifying bases and measurement systems for such signals is complicated by their higher dimensionality. In this paper, we propose the use of Kronecker product matrices in CS for two purposes. First, such matrices can act as sparsifying bases that jointly model the structure present in all of the signal dimensions. Second, such matrices can represent themeasurement protocols used in distributed settings. Our formulation enables the derivation of analytical bounds for the sparse approximation of multidimensional signals and CS recovery performance, as well as a means of evaluating novel distributed measurement schemes.

关键词： Compressed sensing compression algorithms hyperspectral imaging multidimensional signal processing video compression

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