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Tobias Winchen, Marvin Gottowik, Julian Rautenberg
The Pierre Auger Observatory is the currently largest experiment dedicated to unveil the nature and origin of the highest energetic cosmic rays. The software framework ‘Offline’ has been developed by the Pierre Auger Collaboration for joint analysis of data from different independent detector systems used in one observatory. While reconstruction modules are specific to the […]
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Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara
We propose an approach to reverberant speech recognition adopting deep learning in the front-end as well as back-end of a reverberant speech recognition system, and a novel method to improve the dereverberation performance of the front-end network using phone-class information. At the front-end, we adopt a deep autoencoder (DAE) for enhancing the speech feature parameters, […]
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David Medina
Rapid evolution of computer processor architectures has spawned multiple programming languages and standards. This thesis strives to address the challenges caused by fast and cyclical changes in programming models. The novel contribution of this thesis is the introduction of an abstract unified framework which addresses portability and performance for programming manycore devices. To test this […]
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Ping Liu
XML has been used as a textual data format for transporting and storing information in many areas. However, the cost to process the large-scale XML file will become a serious issue for general processing methods. In this paper, we propose a design and implementation of a large-scale XML processing system on GPU cluster to address […]
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Hamed Khakzad, Yasaman Karami, Seyed Shahriar Arab
Protein tertiary structure prediction (PSP) is one of the most challenging problems in bioinformatics. Different methods have been introduced to solve this problem so far, but PSP is computationally intensive and belongs to the NP-hard class. One of the best solutions to accelerate PSP is the use of a massively parallel processing architecture, such graphical […]
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Keiron O'Shea
Greedy Restrictive Boltzmann Machines yield an fairly low 0.72% error rate on the famous MNIST database of handwritten digits. All that was required to achieve this result was a high number of hidden layers consisting of many neurons, and a graphics card to greatly speed up the rate of learning.
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Baoguang Shi, Xiang Bai, Cong Yao
Image-based sequence recognition has been a long-standing research topic in computer vision. In this paper, we investigate the problem of scene text recognition, which is among the most important and challenging tasks in image-based sequence recognition. A novel neural network architecture, which integrates feature extraction, sequence modeling and transcription into a unified framework, is proposed. […]
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Carlo D'Eramo
The Deep Boltzmann Machine (DBM) has been proved to be one of the most effective machine learning generative models in discriminative tasks. They’ve been able to overcome other generative, and even discriminative models, on relatively simple tasks, such as digits recognition, and also on more complex tasks such as simple objects recognition. However, there’re only […]
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William B. March, Bo Xiao, Chenhan D. Yu, George Biros
We present a parallel treecode for fast kernel summation in high dimensions – a common problem in data analysis and computational statistics. Fast kernel summations can be viewed as approximation schemes for dense kernel matrices. Treecode algorithms (or simply treecodes) construct low-rank approximations of certain off-diagonal blocks of the kernel matrix. These blocks are identified […]
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Srajan Paliwal, Saurabh Tiwary, Bhaskar Chaudhury, Manish K. Gupta
Generation of optimal codes is a well known problem in coding theory. Many computational approaches exist in the literature for finding record breaking codes. However generating codes with long lengths n using serial algorithms is computationally very expensive, for example the worst case time complexity of a Greedy algorithm is O(n4^n). In order to improve […]
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Stefan Westerlund, Christopher Harris
Searching for sources of electromagnetic emission in spectral-line radio astronomy interferometric data is a computationally intensive process. Parallel programming techniques and High Performance Computing hardware may be used to improve the computational performance of a source finding program. However, it is desirable to further reduce the processing time of source finding in order to decrease […]
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Mark James Abraham, Teemu Murtola, Roland Schulz, Szilard Pall, Jeremy C. Smith, Berk Hess, Erik Lindahl
GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced […]
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