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检索条件"主题词=Compression algorithms"

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GPU-accelerated adaptive compression framework for genomics data

GPU-accelerated adaptive compression framework for genomics ...

引用

IEEE International Conference on Big Data

作者： GuiXin Guo Shuang Qiu ZhiQiang Ye BingQiang Wang Lin Fang Mian Lu Simon See Rui Mao BGI-Shenzhen Shenzhen P.R. China A *STAR Institute of HPC Singapore BGI-NVIDIA Joint Innovation Lab Shenzhen P.R. China Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen University Shenzhen P.R. China

Genomics data is being produced at an unprecedented rate, especially in the context of clinical applications and grand challenge questions. There are various types of data in genomics research, most of which are stored as plain text tables. A data compression framework tailored to this file type is introduced in this paper, featuring a combination of generic compression algorithms, GPU acceleration, and column-major storage. This approach is the first to achieve both compression and decompression rates of around 100MB/s on commodity hardware without compromising compression ratio. By selecting appropriate compression schemes for each column of data, this framework efficiently exploits data redundancy while remaining applicable to a wide range of formats. The GPU-accelerated implementation also properly exploits the parallelism of compression algorithms. Finally, this paper presents a novel first-order Markov model based transformation, with evidence that it is at least as effective as Burrows-Wheeler and Move-To-Front in some contexts.

关键词： Graphics processing units Bioinformatics Genomics Markov processes Transforms compression algorithms Acceleration

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An information theoretic model for adaptive lossy compression

An information theoretic model for adaptive lossy compressio...

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： R. Zamir K. Rose Department Electrical Engineering Systems Tel-Aviv University Tel-Aviv Israel Department of ECE University of California Santa Barbara CA USA

We investigate the underlying mechanism of universal sequential, fixed distortion, lossy source coding algorithms, through the "eyes" of a random code. We model the adaptive codebook as a "mixed type" random code whose codeword type distribution evolves with time while its dimension goes to infinity. The evolution law in our model has a structure of a tree; a type inherits its frequency in the code from its parent-types matching probabilities. We find that this mechanism naturally selects the "good" codeword types for compressing the (unknown) source. As a consequence, the code becomes optimal for the source, and approaches the rate-distortion function as the time, and hence the dimension, go to infinity. Beyond its analytical interest, this model also provides guidelines for developing lossy string matching (Lempel-Ziv-like) algorithms.

关键词： H infinity control Frequency Algorithm design and analysis compression algorithms Source coding Pressing Rate-distortion Speech analysis Guidelines Speech coding

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A Low Power 16-bit RISC with Lossless compression Accelerator for Body Sensor Network System

A Low Power 16-bit RISC with Lossless Compression Accelerato...

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IEEE Asian Conference on Solid-State Circuits (ASSCC)

作者： Hyejung Kim Sungdae Choi Hoi-Jun Yoo Department of Electrical Engineering and Computer Science Semiconductor System Laboratory KAIST Daejeon South Korea

A low power 16-bit RISC is proposed for body sensor network system. The proposed IPEEP scheme provides zero overhead for the wakeup operation. The lossless compression accelerator is embedded in the RISC to support the low energy data compression. The accelerator consists of 16times16-bit storage array which has vertical and horizontal access path. By using the accelerator the energy consumption of the lossless compression operation is reduced by 93.8%. The RISC is implemented by 1-poly 6-metal 0.18 um CMOS technology with 16 k gates. It operates at 4 MHz and consumes 24.2 uW at 0.6 V supply voltage.

关键词： Reduced instruction set computing Body sensor networks Base stations Energy consumption Registers Data compression Sensor systems CMOS technology compression algorithms Wireless sensor networks

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QualityNet: Error-bounded Lossy compression Quality Prediction via Deep Surrogate

QualityNet: Error-bounded Lossy Compression Quality Predicti...

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IEEE International Conference on Big Data

作者： Khondoker Mirazul Mumenin Dong Dai Jinzhen Wang Sheng Di University of North Carolina Charlotte USA University of Delaware USA Argonne National Laboratory USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

As scientific simulations generate increasingly large datasets, efficient data compression becomes essential to mitigate storage and transmission challenges. Error-bounded Lossy compression algorithms reduce data volume at the expense of data fidelity. However, the evaluation of compressed data quality can be resource-intensive and time-consuming. This paper proposes a surrogate-based framework to predict key compression quality assessment metrics, allowing users to evaluate the quality of compressed data quickly without extensive trial and error. We evaluate our proposed framework on real-world scientific application datasets. Our surrogate-based framework shows superior prediction accuracy, with the RMSE generally lower than 5%. On the other hand, our framework demonstrates robust generalization for prediction across data fields within the same application. Our results show that our approach significantly reduces the error bound selection time and accelerates the downstream evaluation process for decompressed data, making it easier for domain scientists to select optimal error bounds of lossy compression while maintaining data quality that meets their needs. This work bridges the gap between compression ratio optimization and data fidelity, offering a scalable solution for scientific applications that rely on large-scale lossy compression.

关键词： Measurement Adaptation models Data integrity Computational modeling Predictive models Prediction algorithms Data models Quality assessment compression algorithms Optimization

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A Novel Dictionary Management Scheme of LZW compression Algorithm Based on Insignificant Dictionary Area

A Novel Dictionary Management Scheme of LZW Compression Algo...

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IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Xiaoyong Cheng Bing Li Jiaxin Wu Wenhui Li Chao Luo Jiayi Su School of Microelectronics Southeast University School of Cyber Science and Engineering Southeast University School of Software Engineering Southeast University Southeast University Shenzhen Research Institute China

ISBN: (纸本)9781665446006

In order to avoid the possible degradation of the compression ratio, the dictionary management scheme is employed when the dictionary of Lempel-Ziv-Welch (LZW) algorithm is filled. Dictionary reset (DR) and least recently used (LRU) are two dictionary management schemes widely used. However, DR trades compression ratio for less time overhead and LRU obtains a high compression ratio while time and memory are sacrificed. This paper proposes a novel insignificant dictionary area LZW (IDA-LZW) which has a high and stable compression ratio while maintaining acceptable compression time and excellent decompression time. The proposed dictionary management scheme called IDA consists of dictionary partition and impact factor (IF) which returns the dictionary area should be cleared for new entries. Three variants of IDA-LZW and LZW with DR and LRU are implemented and show that the proposed scheme achieves the best average compression while consuming reasonable resources. Furthermore, comparisons are made with the results in the paper recently published to prove the proposed scheme is valuable.

关键词： Degradation Dictionaries Image coding Conferences Memory management compression algorithms

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QLFC - a compression algorithm using the Burrows-Wheeler transform

QLFC - a compression algorithm using the Burrows-Wheeler tra...

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Data compression Conference (DCC)

作者： F. Ghido University Politehnica of Bucharest Romania

Summary form only given. In this paper, we propose a novel approach for the second step of the Burrows-Wheeler compression algorithm, based on the idea that the probabilities of events are not continuous valued, but are rather quantized with respect to a specific class of base functions. The first pass of encoding transforms the input sequence x into sequence x/spl tilde/. The second pass models and codes x/spl tilde/using entropy coding. The entropy decoding, modeling, and context updating for decoding x/spl tilde/ are the same as the ones used for encoding. We have proved that the quantized local frequency transform is optimal in the case of binary and ternary alphabet memoryless sources, showing that x and x/spl tilde/ have the same entropy; for larger alphabets, we verified this by simulation.

关键词： compression algorithms Frequency Decoding Encoding Context modeling Data compression Entropy coding Mathematics

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Multiresolution distance volumes for progressive surface compression

Multiresolution distance volumes for progressive surface com...

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International Symposium on 3D Data Processing Visualization and Transmission

作者： D. Laney M. Bertram M. Duchaineau N. Max U.C. Davis Department of Applied Science University of California Davis USA University of Kaiserslautern Kaiserslautern Germany Lawrence Livemore National Laboratory Livermore CA USA U.C. Davis Department of Applied Science

We present a surface compression method that stores surfaces as wavelet-compressed signed-distance volumes. Our approach enables the representation of surfaces with complex topology and arbitrary numbers of components within a single multiresolution data structure. This data structure elegantly handles topological modification at high compression rates. Our method does not require the costly and sometimes infeasible base mesh construction step required by subdivision surface approaches. We present several improvements over previous attempts at compressing signed-distance functions, including an O(n) distance transform, a zero set initialization method for triangle meshes, and a specialized thresholding algorithm. We demonstrate the potential of sampled distance volumes for surface compression and progressive reconstruction for complex high genus surfaces.

关键词： Surface reconstruction Surface waves Topology Wavelet coefficients Data structures compression algorithms Encoding Spline Laboratories Visualization

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Deployment of IPv6 robust header compression profiles 1 and 2

Deployment of IPv6 robust header compression profiles 1 and ...

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Mexican International Conference on Computer Science (ENC)

作者： A. Minaburo L. Toutain L. Nuaymi ENST de bretagne Rennes France

The use of interactive services in a low bandwidth link leads to a weak performance because of the large size of encapsulations. The performance could be increased using a header compression algorithm. The IETF ROHC working group has defined a new header compression algorithm used in low bandwidth links with high-level errors. This paper gives a description of the proposed infrastructure for ROHC and the differences between the profile 1 and profile 2 based profiles that are used. The results are based on our IPv6 ROHC implementation.

关键词： Robustness compression algorithms Redundancy Bandwidth Radio link Land mobile radio cellular systems Transport protocols TCPIP Bit error rate Encapsulation

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An MCMC Approach to Lossy compression of Continuous Sources

An MCMC Approach to Lossy Compression of Continuous Sources

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Data compression Conference (DCC)

作者： Dror Baron Tsachy Weissman Electrical Engineering Department Technion-Israel Institute of Technology Haifa Israel Department of Electrical Engineering University of Stanford Stanford CA USA

ISBN: (纸本)9781424464258

Motivated by the Markov chain Monte Carlo (MCMC) relaxation method of Jalali and Weissman, we propose a lossy compression algorithm for continuous amplitude sources that relies on a finite reproduction alphabet that grows with the input length. Our algorithm asymptotically achieves the optimum rate distortion (RD) function universally for stationary ergodic continuous amplitude sources. However, the large alphabet slows down the convergence to the RD function, and is thus an impediment in practice. We thus propose an MCMC-based algorithm that uses a (smaller) adaptive reproduction alphabet. In addition to computational advantages, the reduced alphabet accelerates convergence to the RD function, and is thus more suitable in practice.

关键词： Image coding Convergence compression algorithms Statistical distributions Rate-distortion Impedance Acceleration Vector quantization Entropy coding Adaptive algorithm

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compression Techniques Used in Iot: A Comparitive Study

Compression Techniques Used in Iot: A Comparitive Study

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International Conference on New Trends in Computing Sciences (ICTCS)

作者： Salam Hamdan Arafat Awaian Sufyan Almajali Princess Sumaya University for Tecnology Amman Jordan

Due to the improvement of technology, most of the devices used nowadays are connected to the internet, therefore a huge amount of data is generated, transmitted, and used by these devices. In general, these devices are limited in resources such as memory, processors, and battery lifetime. Reducing the data size reduces the energy required to process this data, minimizes the storage of this, data and the energy required to transmit this data. The need for applying data compression techniques on these devices will come in handy. This paper provides a survey and a comparative study among most commonly used IoT compression techniques. The study addresses the techniques in terms of different attributes such as the compression type, lossless or lossy, the limitations of the compression technique, the location of where the compression is applied, and the implementation of the compression technique.

关键词： Data compression Batteries compression algorithms Temperature dependence Servers Indexes Machine learning

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