Gitta Kutyniok, Wang-Q Lim, Rafael Reisenhofer
Wavelets and their associated transforms are highly efficient when approximating and analyzing one-dimensional signals. However, multivariate signals such as images or videos typically exhibit curvilinear singularities, which wavelets are provably deficient of sparsely approximating and also of analyzing in the sense of, for instance, detecting their direction. Shearlets are a directional representation system extending the […]
View View   Download Download (PDF)   
Andre Kessler
We investigate compression of large-volume spatial data using the wavelet transform, computed massively in parallel on NVIDIA graphics processing units (GPUs). In particular, Haar basis wavelets are used to achieve compression ratios of [100x] or more. Computation is done over a set of computing nodes consisting of multiple nodes and multiple GPUs per node. Significantly […]
View View   Download Download (PDF)   
Manas Arora, Neha Maurya
Mars Rovers are the unmanned machines on planet MARS which are send to analyze and provide details about the planet. GPU and Genetic Algorithms are upcoming technologies used in Mars Rovers for analyzing and sending the data back to the Earth base station. GPU stands for Graphics Processing Unit in which Image compression is the […]
View View   Download Download (PDF)   
Zhou Haifang, Xu Rulin, Jiang Jingfei
Image registration is a crucial step of many remote sensing related applications. As the scale of data and complexity of algorithm keep growing, image registration faces great challenges of its processing speed. In recent years, the computing capacity of GPU improves greatly. Taking the benefits of using GPU to solve general propose problem, we research […]
View View   Download Download (PDF)   
Bartlomiej Szczepaniak
Wavelet transform have a wide area of application in many scientific areas, for example signal processing, image compression [6] or data mining [4] [5]. Present requirements demand preforming large amount of calculations in the minimum time. For that reason the goal of this paper is to present an approach that will fulfill mentioned requirements, by […]
View View   Download Download (PDF)   
Paul Rosen
We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by […]
View View   Download Download (PDF)   
Fernando Amat, Philipp J. Keller
Object detection and classification are key tasks in computer vision that can facilitate high-throughput image analysis of microscopy data. We present a set of local image descriptors for three-dimensional (3D) microscopy datasets inspired by the well-known Haar wavelet framework. We add orientation, illumination and scale information by assuming that the neighborhood surrounding points of interests […]
View View   Download Download (PDF)   
V. Galiano, O. Lopez-Granado, M.P. Malumbres, H. Migallon
Three-dimensional wavelet transform (3D-DWT) has focused the attention of the research community, most of all in areas such as video watermarking, compression of volumetric medical data, multispectral image coding, 3D model coding and video coding. In this work, we present several strategies to speed-up the 3D-DWT computation through multicore processing. An in depth analysis about […]
View View   Download Download (PDF)   
Vicente Galiano, Otoniel Lopez, Manuel P. Malumbres, Hector Migallon
Wide amount of applications like volumetric medical data compression, video watermarking and video coding use the three-dimensional wavelet transform (3D-DWT) in their algorithms. In this work, we present GPU algorithms, based on both global and shared memory, to compute the 3D-DWT transform on both the GTX280 and the GMT540 platforms. The results obtained show that […]
View View   Download Download (PDF)   
Brice Videau, Vania Marangozova-Martin, Luigi Genovese, Thierry Deutsch
Nanosimulations present a big HPC challenge as they present increasing performance demands in heterogeneous execution environments. In this paper, we present our optimization methodology for BigDFT, a nanosimulation software using Density Functional Theory. We explore autotuning possibilities for BigDFT’s 3D convolutions by studying optimization techniques for several architectures. Namely, we focus on processors with vector […]
View View   Download Download (PDF)   
Mark Murphy
Magnetic Resonance Imaging (MRI) is a non-invasive and highly exible medical imaging modality that does not expose patients ionizing radiation. MR Image acquisitions can be designed by varying a large number of contrast-generation parameters, and many clinical diagnostic applications exist. However, imaging speed is a fundamental limitation to many potential applications. Traditionally, MRI data have […]
Sylvain Paris, Samuel W. Hasinoff, Jan Kautz
The Laplacian pyramid is ubiquitous for decomposing images into multiple scales and is widely used for image analysis. However, because it is constructed with spatially invariant Gaussian kernels, the Laplacian pyramid is widely believed as being unable to represent edges well and as being ill-suited for edge-aware operations such as edge-preserving smoothing and tone mapping. […]
Page 1 of 3123

* * *

* * *

* * *

Free GPU computing nodes at

Registered users can now run their OpenCL application at We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 11.4
  • SDK: AMD APP SDK 2.8
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 5.0.35, AMD APP SDK 2.8

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to will be treated according to our Privacy Policy

HGPU group © 2010-2014

All rights belong to the respective authors

Contact us: