Array operations are useful in a lot of important scientific codes, such as molecular dynamics, finite-element methods, atmosphere and ocean sciences, and etc. In recent years, more and more applications, such as geol...
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ISBN:
(纸本)9781509001552
Array operations are useful in a lot of important scientific codes, such as molecular dynamics, finite-element methods, atmosphere and ocean sciences, and etc. In recent years, more and more applications, such as geological analysis and medical images processing, are solved and processed by using array operations for three-dimensional (abbreviate to 3D) sparse arrays. Due to the huge computation time, it is necessary to compress the sparse arrays to compact structures in order to avoid unnecessary computations. Parallel processing is also a suitable solution to speed up the array operations based on multiprocessors, multicomputers and accelerators. How to compress the sparse arrays efficiently is the first task of designing parallel algorithms for practical applications with sparse array operations. Hence, efficient strategies of compressing 3D sparse arrays based on Intel XEON (multiprocessor) and Intel XEON Phi (accelerator) environments are proposed in this paper. For each environment, two strategies, inter-task parallelization and intra-task parallelization, are presented to compress a series of sparse arrays and single large sparse array, respectively. From experimental results, the inter-task parallelization strategy achieves 16x and 18x speedup ratios based on Intel XEON E5-2670 v2 and Intel Xeon Phi SE10X, respectively;4x and 5x speedup ratios, respectively, for the intra-task parallelization strategy.
The exponential growth of high-throughput DNA sequence data has brought great challenges in data processing, archive and transmission. How to improve compression techniques for large datasets of sequence read archive ...
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The exponential growth of high-throughput DNA sequence data has brought great challenges in data processing, archive and transmission. How to improve compression techniques for large datasets of sequence read archive has become a critical problem in store and analyzes biological data. The paper compared the existing data compression methods on five high-throughput sequence datasets, and proposed a novel method to compress high-throughput sequence read archive data. The experiment results show that the proposed compressionmethod could get good compression ration and implement higher processing speed.
The crucial residues of hBaxBH3 peptide for interaction with hBcl-B, an anti-apoptotic protein, were identified using molecular docking studies on the polypeptides and temperature-specific molecular dynamic simulation...
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The crucial residues of hBaxBH3 peptide for interaction with hBcl-B, an anti-apoptotic protein, were identified using molecular docking studies on the polypeptides and temperature-specific molecular dynamic simulations performed for the protein-peptide complex at near-physiological conditions (pH 7.0, 1 atmospheric pressure and 0.1 M NaCl). The data from the methods were examined by a 'strong residue contacts' filter strategy and the data analyses of the former and latter methods identified 10 (Q52, K57, S60, L63, K64, R65, G67, D68, D71 & S72) and 3 (S60, E61 & K64) crucial residues of the hBaxBH3 peptide for interacting with the protein, respectively. We have herein demonstrated that BH3-chemical mimetics screened using the pharmacophoric residues of hBaxBH3 obtained from the 'peptidodynmimetic method' were superior in terms of ligand efficiencies, bioavailability and pharmacokinetic properties vis-a-vis that of small molecule BH3-mimetics retrieved using the conventional 'peptidomimetic method'. The unique advantages of the 'peptidodynmimetic method' to identify efficient BH3-mimetics for modulating interfaces (composed of a large number of amino acids) of other anti-apoptotic proteins-BH3-only peptides have also been discussed in detail.
Web content is consumed on smart phones, tablets, and computers with a significant variation in device display resolution. Visualizing data is typically performed by extracting data from a database, packaging it as JS...
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ISBN:
(纸本)9781479900312
Web content is consumed on smart phones, tablets, and computers with a significant variation in device display resolution. Visualizing data is typically performed by extracting data from a database, packaging it as JSON or XML for transmission to the client and then visualizing with a client-side JavaScript library. A major challenge is to retrieve only the required data for visualization. Current approaches require programmers to manually modify their data extraction queries and do not adapt to client display characteristics. The contribution in this work is a configurable data compression method that automatically adapts the amount of data transmitted for client-side visualization based on device characteristics. We evaluate several different techniques for time series summarization and compression and show that the amount of data transmitted can be reduced by between 40% and 80% while preserving pixel-perfect visualization. Reducing data transmitted improves client responsiveness and allows flexible and responsive web content without programmer intervention. The approach is tested on a wide variety of data sets and is implemented as an add-on for a JavaScript visualization library.
Discrete-time stochastic processes generating elements of either a finite set (alphabet) or a real line interval are considered. Problems of estimating limiting (or stationary) probabilities and densities are consider...
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Discrete-time stochastic processes generating elements of either a finite set (alphabet) or a real line interval are considered. Problems of estimating limiting (or stationary) probabilities and densities are considered, as well as classification and prediction problems. We show that universal coding (or datacompression) methods can be used to solve these problems.
Array operations are useful in a large number of important scientific codes, such as molecular dynamics, finite-element methods, climate modeling, etc. It is a challenging problem to provide an efficient data distribu...
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Array operations are useful in a large number of important scientific codes, such as molecular dynamics, finite-element methods, climate modeling, etc. It is a challenging problem to provide an efficient data distribution for irregular problems. Multi-dimensional (AM) sparse array operations can be used in atmosphere and ocean sciences, image processing, etc., and have been an extensively investigated problem. In our previous work, a data distribution scheme, Encoding-Decoding (ED), was proposed for two-dimensional (2D) sparse arrays. In this paper, ED is extended to be useful for MD sparse arrays first. Then, the performance of ED is compared with that of Send Followed Compress (SFC) and Compress Followed Send (CFS). Both theoretical analysis and experimental tests were conducted and then shown that ED is superior to SFC and CFS for all of evaluated criteria.
In this paper, a multilead ECG data compression method is presented. First, a linear transform is applied to the standard ECG lead signals which are highly correlated with each other. In this way a set of uncorrelated...
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In this paper, a multilead ECG data compression method is presented. First, a linear transform is applied to the standard ECG lead signals which are highly correlated with each other. In this way a set of uncorrelated transform domain signals is obtained. Then, resulting transform domain signals are compressed using various coding methods, including multirate signal processing and transform domain coding techniques.
A fan data compression method is presented that tripled laser printer speed for Bode and simulation plots with many points. This reduced printer delays without the expense of a faster laser printer, and it saved compu...
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A fan data compression method is presented that tripled laser printer speed for Bode and simulation plots with many points. This reduced printer delays without the expense of a faster laser printer, and it saved computer time as well. The authors describe their problem, solution, and conclusions. They give the fan algorithm and present its performance for several applications. They include a pseudocode implementation.
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