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Achal Shah, Angshul Majumdar
Solving linear inverse problems where the solution is known to be sparse is of interest to both signal processing and machine learning research. The standard algorithms for solving such problems are sequential in nature – they tend to be slow for large scale problems. In the past, researchers have used Graphics Processing Units to accelerate […]
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Xiangyu Guo, Xing Liu, Peng Xu, Zhihui Du, Edmond Chow
The particle-mesh spreading operation maps a value at an arbitrary particle position to contributions at regular positions on a mesh. This operation is often used when a calculation involving irregular positions is to be performed in Fourier space. We study several approaches for particle mesh spreading on GPUs. A central concern is the use of […]
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Lokendra Singh Panwar
Today, heterogeneous computing has truly reshaped the way scientists think and approach high-performance computing (HPC). Hardware accelerators such as general-purpose graphics processing units (GPUs) and Intel Many Integrated Core (MIC) architecture continue to make in-roads in accelerating large-scale scientific applications. These advancements, however, introduce new sets of challenges to the scientific community such as: selection […]
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Daniel Povey, Xiaohui Zhang, Sanjeev Khudanpur
We describe the neural-network training framework used in the Kaldi speech recognition toolkit, which is geared towards training DNNs with large amounts of training data using multiple GPU-equipped or multi-core machines. In order to be as hardware-agnostic as possible, we needed a way to use multiple machines without generating excessive network traffic. Our method is […]
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Tyler Rey Sorensen
Graphics Processing Units (GPUs) are highly parallel shared memory microprocessors, and as such, they are prone to the same concurrency considerations as their traditional multicore CPU counterparts. In this thesis, we consider shared memory consistency, i.e. what values can be read when issued concurrently with writes on current GPU hardware. While memory consistency has been […]
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Amirsaman Farrokhpanah, Hanif Montazeri, Javad Mostaghimi
Capabilities of using Graphic Processing Units (GPU) as a computational tool in CFD have been investigated here. Several solvers for solving linear matrix equations have been benchmarked on GPU and is shown that Gauss-Seidle gives the best performance for the GPU architecture. Compared to CPU on a case of lid-driven cavity flow, speedups of up […]
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Michelle Perry
This dissertation studies a graphical processing unit (GPU) construction of Bayesian neural networks (BNNs) using large training data sets. The goal is to create a program for the mapping of phenomenological Minimal Supersymmetric Standard Model (pMSSM) parameters to their predictions. This would allow for a more robust method of studying the Minimal Supersymmetric Standard Model, […]
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Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer
Using GPUs as general-purpose processors has revolutionized parallel computing by offering, for a large and growing set of algorithms, massive data-parallelization on desktop machines. As an obstacle to widespread adoption, programming GPUs has remained difficult due to the need of using low-level control of the hardware to achieve good performance. This paper suggests a programming […]
Shousheng Liu, Ge Chen, Chunyong Ma, Yong Han
The existing matrix palette algorithms for skeletal animation are accelerated by the technique GPGPU based on GLSL or CUDA. Because GLSL is extended from graphics library OpenGL, it couples the rendering and calculations together closely and forces itself not convenient to reuse, meanwhile CUDA is designed only for NVIDIA GPUs. In this paper GPGPU based […]
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Nikolay Pydiura, Pavel Karpov, Yaroslav Blume
The complexity and diversity of the computational biology tasks requires a deliberate approach to the computational resource management. We have analyzed the performance of the common CPU and hybrid CPU-GPU hardware configurations in molecular dynamics and homology modeling tasks. Our results show that on dual-processor nodes it is in overall more efficient to execute two […]
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Thomas Kovac
As multiple sclerosis is known to cause atrophy and deformation in the brain, it also influences the shape and size of the corpus callosum. Longitudinal studies try to quantify these changes using medical image analysis techniques for measuring and analyzing the shape and size of a corpus callosum cross-sechtion embedded in a specially selected measurement […]
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Jose M Gonzalez-Linares, Antonio Fuentes-Alventosa, Juan Gomez-Luna, Nicolas Guil
Data compression is the process of representing information in a compact form, in order to reduce the storage requirements and, hence, communication bandwidth. It has been one of the critical enabling technologies for the ongoing digital multimedia revolution for decades. In the variable-length encoding (VLE) compression method, most frequently occurring symbols are replaced by codes […]
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