A hardware implementation of a run length encoding compression algorithm with parallel inputs

Trein, J.; Schwarzbacher, Andreas; Hoppe, Berthold; Noff, K.-H.

doi:10.1049/cp:20080685

Cited by 16 publications

(6 citation statements)

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“…The third data structure is a row buffer, which makes processed labels on one row available for processing the following row, and is a consequence of the window required for propagating labels and determining connectivity. The length of the row buffer generally corresponds to the width of the image (although it can be shorter if preprocessing is used to simplify the image contents by removing noise, and run-length encoding the relevant information [21]). The width of the row buffer is usually the width of a label (for propagating labels from one row to the next), although it can be reduced to a single bit for deterministic labelling [3,20].…”

Section: Comparison With Other Cca Algorithmsmentioning

confidence: 99%

Union-Retire for Connected Components Analysis on FPGA

Bailey

Klaiber

2022

J. Imaging

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The Union-Retire CCA (UR-CCA) algorithm started a new paradigm for connected components analysis. Instead of using directed tree structures, UR-CCA focuses on connectivity. This algorithmic change leads to a reduction in required memory, with no end-of-row processing overhead. In this paper we describe a hardware architecture based on UR-CCA and its realisation on an FPGA. The memory bandwidth and pipelining challenges of hardware UR-CCA are analysed and resolved. It is shown that up to 36% of memory resources can be saved using the proposed architecture. This translates directly to a smaller device for an FPGA implementation.

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Section: Comparison With Other Cca Algorithmsmentioning

confidence: 99%

Union-Retire for Connected Components Analysis on FPGA

Bailey

Klaiber

2022

J. Imaging

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“…They design the architecture to combine the communication, transmission and operation system for data compression, and achieved high throughput and speed gain. Other algorithms like run-length encoding algorithm were also implemented in hardware, as J. Trein et al described and analyzed [28]. They used on-chip dedicate logic to optimize parallel data processing, and achieved high performance through parallel input.…”

Section: Related Workmentioning

confidence: 99%

Astronomical Data Preprocessing Implementation Based on FPGA and Data Transformation Strategy for the FAST Telescope as a Giant CPS

et al. 2020

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The emergence of cyber-physical-social systems (CPSS) as a novel paradigm has revolutionized the relationship between humans, computers and the physical environment. CPSS extend cyber-physical systems (CPS) to include the social domain, which introduces a challenge of massive data processing. As a typically giant CPS, the Five-hundred-meter Aperture Spherical radio Telescope (FAST), the world's largest filled-aperture radio telescope, generates massive volume of data which poses a huge storage problem that CPSS face likewise and requires real-time data compressing to reduce data storage and movement overhead. The recently introduced Bitshuffle preprocessing algorithm is a novel approach towards exploiting spatial redundancy incorporation to improve the compression ratio with a specific compressor. However, the existing high-performance CPU-based solutions cannot satisfy the performance requirement and power budget requirement simultaneously. In the paper, we propose the implementation of this algorithm on Field Programmable Gate Array (FPGA) and present an unique data transformation strategy to turn raw FAST data in classic FITS format into another format to support huge file sizes, i.e. Hierarchical Data Format (HDF5). Evaluation results show that our implementation can achieve 3.2Gbyte/s throughput which can be equipped with LZ4 compressor to be high performance compressor. This makes Bitshuffle on FPGAs a candidate for meeting the computational and energy efficiency constraints of radio telescopes and provide reference for CPSS facing the same situation. INDEX TERMS CPSS, astronomical data, FPGA, Bitshuffle, FITS, HDF5. I. INTRODUCTION With the cyber-physical system (CPS) technologies evolution [1], lots of interesting application domains have been explored ranging from industry automation to aeronautics and astronautics. Taking human social characteristics into account, an emerging computing paradigm called cyberphysical-social system (CPSS) has focused on the exploration The associate editor coordinating the review of this manuscript and approving it for publication was Zahir Tari.

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“…It is a lossless compression scheme and develops a parallel algorithm of it [12]. It also gives fast compression result [13].…”

Section: Encodingmentioning

confidence: 99%

Run length encoding for speech data compression

Arif

Anand

2012

2012 IEEE International Conference on Computational Intelligence and Computing Research

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In this paper, run length encoding scheme have been applied on the speech signals of different languages to observe the effect on them. First of all, the speech signals from IPA data base in the category of American-English, German and Japanese of Conventions have taken into account on which this algorithmic scheme is applied. At the encoder end, the speech signal is compressed by this scheme to observe the effect. Further, the speech signal is reconstructed at the decoder end from the compressed speech signal. The hearing quality of the reconstructed speech signal is observed to be the same as the RLE technique is a loss less compression technique. Finally, a comparison of computed CRs of three languages is produced which reflects the relative performance of this encoding algorithmic scheme.

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A hardware implementation of a run length encoding compression algorithm with parallel inputs

Cited by 16 publications

References 0 publications

Union-Retire for Connected Components Analysis on FPGA

Union-Retire for Connected Components Analysis on FPGA

Astronomical Data Preprocessing Implementation Based on FPGA and Data Transformation Strategy for the FAST Telescope as a Giant CPS

Run length encoding for speech data compression

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