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Jul, 24

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

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. […]
Jul, 24

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

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.
Jul, 22

On the use of deep Boltzmann machines for road signs classification

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 […]
Jul, 22

Boosting GPU Virtualization Performance with Hybrid Shadow Page Tables

The increasing adoption of Graphic Process Unit (GPU) to computation-intensive workloads has stimulated a new computing paradigm called GPU cloud (e.g., Amazon’s GPU Cloud), which necessitates the sharing of GPU resources to multiple tenants in a cloud. However, state-of-the-art GPU virtualization techniques such as gVirt still suffer from non-trivial performance overhead for graphics memory-intensive workloads […]
Jul, 22

Raspberry Pi based System for Visual Object Detection and Tracking

The aim of this thesis is to explore different methods for helping computers interpret the real world visually, investigate solutions to those methods offered by the open-sourced computer vision library, OpenCV, and implement some of these in a Raspberry Pi based application for detecting and keeping track of objects. The main focus rests on the […]
Jul, 22

An algebraic parallel treecode in arbitrary dimensions

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 […]
Jul, 22

Generating Binary Optimal Codes Using Heterogeneous Parallel Computing

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 […]
Jul, 20

Improving performance portability for GPU-specific OpenCL kernels on multi-core/many-core CPUs by analysis-based transformations

OpenCL is an open heterogeneous programming framework. Although OpenCL programs are functionally portable, it does not provide performance portability, so code transformation often plays an irreplaceable role. When adapting GPU-specific OpenCL kernels to run on multi-core/many-core CPUs, coarsening the thread granularity is necessary and thus extensively used. However, locality concerns exposed in GPU-specific OpenCL code […]
Jul, 20

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

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 […]
Jul, 20

Performance Analysis of GPU-Accelerated Filter-Based Source Finding for HI Spectral Line Image Data

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 […]
Jul, 20

Accelerating a Movie Recommender System Using VirtualCL on a Heterogeneous GPU Cluster

Present day market offers a large number of movies which overwhelm people with choices. In order to quickly navigate through all the possible movies and find the interesting ones, the user can take advantage of recommender systems for movies. This thesis studies a movie recommender system which uses image processing and computer vision algorithms. The […]
Jul, 20

Parallel Programming in Actor-Based Applications via OpenCL

GPU and multicore hardware architectures are commonly used in many different application areas to accelerate problem solutions relative to single CPU architectures. The typical approach to accessing these hardware architectures requires embedding logic into the programming language used to construct the application; the two primary forms of embedding are: calls to API routines to access […]

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