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检索条件"主题词=Compression algorithms"

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Exploiting Adaptive Data compression to Improve Performance and Energy-efficiency of Compute Workloads in Multi-GPU Systems 33

Exploiting Adaptive Data Compression to Improve Performance ...

引用

33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Tavana, Mohammad Khavari Sun, Yifan Agostini, Nicolas Bohm Kaeli, David Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA

ISBN: (纸本)9781728112466

Graphics Processing Unit (GPU) performance has relied heavily on our ability to scale of number of transistors on chip, in order to satisfy the ever-increasing demands for more computation. However, transistor scaling has become extremely challenging, limiting the number of transistors that can be crammed onto a single die. Manufacturing large, fast and energy-efficient monolithic GPUs, while growing the number of stream processing units on-chip, is no longer a viable solution to scale performance. GPU vendors are aiming to exploit multi-GPU solutions, interconnecting multiple GPUs in the single node with a high bandwidth network (such as NVLink), or exploiting Multi-Chip Module (MCM) packaging, where multiple GPU modules are integrated in a single package. The inter-GPU bandwidth is an expensive and critical resource for designing multi-GPU systems. The design of the inter-GPU network can impact performance significantly. To address this challenge, in this paper we explore the potential of hardware-based memory compression algorithms to save bandwidth and improve energy efficiency in multi-GPU systems. Specifically, we propose an adaptive inter-GPU data compression scheme to efficiently improve both performance and energy efficiency. Our evaluation shows that the proposed optimization on multi-GPU architectures can reduce the inter-GPU traffic up to 62%, improve system performance by up to 33%, and save energy spent powering the communication fabric by 45%, on average.

关键词： Multi-GPU system Multi-Chip-Module compression algorithms Bandwidth management Performance

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Light field image compression with random access

Light field image compression with random access

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Data compression Conference (DCC)

作者： Amirpour, Hadi Pinheiro, Antonio Pereira, Manuela Lopes, Fernando J. P. Ghanbari, Mohammad Inst Telecomunicacoes Covilha Portugal Univ Beira Interior Covilha Portugal Polytech Inst Coimbra ISEC Coimbra Portugal Univ Tehran Sch Elect & Comp Engn Tehran Iran Univ Essex Sch Comp Sci & Elect Engn Colchester Essex England

ISBN: (纸本)9781728106571

In light field compression, besides coding efficiency, providing random access to individual views is also a very significant factor. Highly efficient compression methods usually lack random access. Similarly, random access methods usually reduce the compression efficiency. To address this trade-off, a light field image encoding method is proposed in this paper which favors random access. In the proposed scheme 15x15 view images are divided into 25 independent 3x3 view images which are called Macro View Image (MVI). To encode MVIs, the central view image is used to compress its immediate neighboring view images using a hierarchical reference structure. To encode the central view of each MVI, the most central view image, along with the center of at most three MVIs, are used as the reference images for the disparity estimation. In addition, the proposed method enables the use of parallel computation to improve encoding/decoding time complexity. To reduce memory footprint in case a Region of Interest (ROI) is required, HEVC tile partitioning is used.

关键词： Image coding Data compression Rate-distortion Computer science compression algorithms Rendering (computer graphics) Decoding

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Design of context-free grammars for lossless data compression

Design of context-free grammars for lossless data compressio...

引用

IEEE Information Theory Workshop

作者： Kieffer, JC Yang, E Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

ISBN: (纸本)0780344081

Any context-free grammar G generates a language L(G). We are interested in context-free grammars G in which L(G) consists of exactly one string. Given a data string a: over a finite alphabet and a context-free grammar G such that L(G) = {x}, one call reduce G to a simpler grammar G' for which L(G') = {x} and for which certain constraints are satisfied. One then losslessly compresses x by losslessly compressing the grammar G'. The redundancy performance of this compression algorithm based upon reduced grammars is discussed.

关键词： context-free grammars compression algorithms lossless compression syntax Cosmic strings

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Applying Selectively Parallel I/O compression to Parallel Storage Systems 1

引用

20th European Conference on Parallel Computing (Euro-Par)

作者： Filgueira, Rosa Atkinson, Malcolm Tanimura, Yusuke Kojima, Isao Univ Edinburgh Sch Informat Edinburgh EH8 9AB Midlothian Scotland AIST Informat Technol Res Inst Tsukuba Ibaraki Japan

ISBN: (数字)9783319098739

ISBN: (纸本)9783319098739;9783319098722

This paper presents a new I/O technique called Selectively Parallel I/O compression (SPIOC) for providing high-speed storage and access to data in QoS enabled parallel storage systems. SPIOC reduces the time of I/O operations by applying transparent compression between the computing and the storage systems. SPIOC can predict whether to compress or not at runtime, allowing parallel or sequential compression techniques, guaranteeing QoS and allowing partial and full reading by decompressing the minimum part of the file. SPIOC maximises the measured efficiency of data movement by applying run-time customising compression before storing data in the Papio storage system.

关键词： Parallel File System Data Intensive Computing compression algorithms Adaptive systems

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A High-performance FPGA-based Accelerator for Gradient compression

A High-performance FPGA-based Accelerator for Gradient Compr...

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Data compression Conference (DCC)

作者： Ren, Qingqing Zhu, Shuyong Meng, Xuying Zhang, Yujun Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Purple Mt Labs Purple Peoples R China Univ Chinese Acad Sci Nanjing Coll Beijing Peoples R China

ISBN: (纸本)9781665478939

Gradient compression technology has attracted much attention in recent years, due to its high effectiveness in alleviating the communication bottleneck of distributed deep learning. However, except for the communication reduction, it also brings in a significant increase of computational overhead, which limits or even eliminates the communication-reduction benefit brought by gradient compression. To solve the high computational overhead problem, we propose an FPGA-based accelerator for gradient compression in this paper. A high-performance and programmable accelerator architecture is developed for accelerating various gradient compression algorithms by offloading compute-intensive compression operations to FPGA. Also, we design and implement the FPGA-based accelerator based on the popular gradient compression algorithm top-k sparsification. Experimental results show that the new accelerator achieves up to hundreds of times faster than the compression algorithm implemented on CPU and GPU. What's more, the stable and controllable performance under different datasets demonstrates that the proposed accelerator is insensitive to data distribution, which is essential for time sensitive applications.

关键词： Deep learning Accelerator architectures Graphics processing units Data compression compression algorithms Field programmable gate arrays

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Electrocardiogram compression by Linear Prediction and Wavelet Sub-Band Coding Techniques

Electrocardiogram Compression by Linear Prediction and Wavel...

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Conference on Computing in Cardiology

作者： Ardhapurkar, Shubhada Manthalkar, Ramchandra Gajre, Suhas Int Ctr Excellence Engn & Managment Aurangabad Maharashtra India SGGS Inst Chem Technol Nanded Maharashtra India

ISBN: (纸本)9781457706110

Linear Predictive coding (LPC) is extensively used for analysis and compression of speech signal whereas the Discrete Wavelet Transform is widely preferred for electrocardiogram (ECG) compression. In this paper, we present LPC and wavelet based method to encode ECG signals. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database, MIT-BIH compression database and University of Glasgow noisy and normal database. The performance is quantified by computing distortion measures. The percentage root mean square difference (PRD) is found to be below 8% and wavelet-based weighted PRD (WWPRD) below 0.25. The upper quartile value of Wavelet energy based diagnostic distortion (WEDD) is less than 0.3 even for noisy data. It is observed that, a combination of LPC and wavelet subband coding offers fixed compression of 84.09%. Classification before decompression is achieved with accuracy of 97%.

关键词： subband coding linear prediction compression algorithms wavelets wavelet energy discrete wavelet transform noisy data compression Voice Signal

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An Efficient Lossless compression Algorithm for Electrocardiogram Signals 26

An Efficient Lossless Compression Algorithm for Electrocardi...

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26th European Signal Processing Conference (EUSIPCO)

作者： Campobello, Giuseppe Segreto, Antonino Zanafi, Sarah Serrano, Salvatore Univ Messina Dept Engn Messina Italy Univ Abdelmalek Essaadi Fac Sci Tetouan Tetouan Morocco

ISBN: (纸本)9789082797015

This paper focuses on a novel lossless compression algorithm which can be efficiently used for compression of electrocardiogram (ECG) signals. The proposed algorithm has low memory requirements and relies on a simple and efficient encoding scheme which can be implemented with elementary counting operations. Thus it can be easily implemented even in resource constrained microcontrollers as those commonly used in several low-cost ECG monitoring systems. Despite its simplicity, simulation results carried out on real-world ECG signals show that the proposed algorithm achieves higher compression ratios as even compared to other more complex state-of-the-art solutions.

关键词： compression algorithms Signal processing algorithms Encoding Electrocardiography Microcontrollers Prediction algorithms Matrix decomposition

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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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Customizable compression architecture for efficient configuration in CGRAs 22

Customizable compression architecture for efficient configur...

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22nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines ((FCCM)

作者： Jafri, Syed M. A. H. Tajammul, Adeel Daneshtalab, Masoud Hemani, Ahmed Paul, Kolin Ellervee, Peeter Plosila, Juha Tenhunen, Hannu Turku Ctr Comp Sci Turku Finland Tallinn Univ Technol Tallinn Estonia Univ Turku Turku Finland Royal Inst Technol Stockholm Sweden Indian Inst Technol Delhi India

ISBN: (纸本)9781479951116

Today, Coarse Grained Reconfigurable Architectures (CGRAs) host multiple applications. Novel CGRAs allow each application to exploit runtime parallelism and time sharing. Although these features enhance the power and silicon efficiency, they significantly increase the configuration memory overheads. As a solution to this problem researchers have employed statistical compression, intermediate compact representation, and multicasting. Each of these techniques has different properties, and is therefore best suited for a particular class of applications. However, existing research only deals with these methods separately. In this paper we propose a morphable compression architecture that interleaves these techniques in a unique platform.

关键词： compression algorithms Computer architecture Educational institutions Hardware Multicast communication Silicon Software Coarse grained reconfigurable architectures compression configuration compression energy aware systems multicast communication compression algorithms Computer Architecture Educational institutions Computer hardware Silicon computer software compression Coarse-grained Reconfigurable Architecture time sharing

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CSI compression and Feedback for Network MIMO 81

CSI Compression and Feedback for Network MIMO

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81st IEEE Vehicular Technology Conference (VTC Spring)

作者： Kurras, Martin Jaeckel, Stephan Thiele, Lars Braun, Volker Heinrich Hertz Inst Nachrichtentech Berlin GmbH Fraunhofer Inst Telecommun Einsteinufer 37 D-10587 Berlin Germany Alcatel Lucent Bell Labs Stuttgart Germany

ISBN: (纸本)9781479980888

We consider the downlink of a multi-cell system where base stations and users are equipped with multiple antennas. Therein, a cluster of base stations employ joint transmission with linear zero-forcing beamforming based on compressed channel state information (CSI) feedback. For propagation we assume a realistic 3D channel model including antenna patterns. We discuss in detail a novel compression algorithm exploiting the spatial and frequency domain and also present a feedback data format. We evaluate the proposed compression algorithm in the presence of channel estimation error in terms of throughput and feedback rate and compare it with the perfect CSI case. The proposed algorithm and feedback scheme is shown to reduce the feedback rate to less than 1 % of uncompressed feedback and at the same time increasing the sum throughput significantly.

关键词： Feedback compression algorithms BASE STATION antenna radiation patterns channel model Throughput multiple antenna multiple input multiple output systems channel estimation

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