George Teodoro, Tahsin Kurc, Jun Kong, Lee Cooper, Joel Saltz
We investigate and characterize the performance of an important class of operations on GPUs and Many Integrated Core (MIC) architectures. Our work is motivated by applications that analyze low-dimensional spatial datasets captured by high resolution sensors, such as image datasets obtained from whole slide tissue specimens using microscopy image scanners. We identify the data access […]
View View   Download Download (PDF)   
Thai V. Hoang, Xavier Cavin, Patrick Schultz, David W. Ritchie
BACKGROUND: Picking images of particles in cryo-electron micrographs is an important step in solving the 3D structures of large macromolecular assemblies. However, in order to achieve sub-nanometre resolution it is often necessary to capture and process many thousands or even several millions of 2D particle images. Thus, a computational bottleneck in reaching high resolution is […]
View View   Download Download (PDF)   
Thai V. Hoang, Xavier Cavin, David W. Ritchie
Fitting high resolution protein structures into low resolution cryo-electron microscopy (cryo-EM) density maps is an important technique for modeling the atomic structures of very large macromolecular assemblies. This article presents "gEMfitter", a highly parallel fast Fourier transform (FFT) EM density fitting program which can exploit the special hardware properties of modern graphics processor units (GPUs) […]
View View   Download Download (PDF)   
Sandor Szenasi, Zoltan Vamossy
The use of digital microscopy allows diagnosis through automated quantitative and qualitative analysis of the digital images. Often to evaluate the samples, the first step is determining the number and location of cell nuclei. For this purpose, we have developed a GPGPU based data-parallel region growing algorithm that is equally as accurate as the already […]
View View   Download Download (PDF)   
Stephan Preibisch, Fernando Amat, Evangelia Stamataki, Mihail Sarov, Eugene Myers, Pavel Tomancak
Light sheet fluorescence microscopy is able to image large specimen with high resolution by imaging the samples from multiple angles. Multi-view deconvolution can significantly improve the resolution and contrast of the images, but its application has been limited due to the large size of the datasets. Here we present a derivation of multi-view Bayesian deconvolution […]
Andrej Krejcir
The aim of the thesis is to implement and optimize chosen image processing algorithms used in digital holographic microscopy on the GPU. The algorithms are 2-D phase unwrapping and polynomial surface fitting. They are described and certain used optimizations are pointed out. The results chapter shows the performance and precision of the GPU implementation compared […]
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)   
George Teodoro, Tony Pan, Tahsin M. Kurc, Jun Kong, Lee A. D. Cooper, Norbert Podhorszki, Scott Klasky, Joel H. Saltz
Analysis of large pathology image datasets offers significant opportunities for biomedical researchers to investigate the morphology of disease, but the resource requirements of image analyses limit the scale of those studies. Motivated by such a study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high […]
View View   Download Download (PDF)   
Giovanni Cerchiari, Fabrizio Croccolo, Frederic Cardinaux, Frank Scheffold
We present an implementation of the analysis of dynamic near field scattering (NFS) data using a graphics processing unit (GPU). We introduce an optimized data management scheme thereby limiting the number of operations required. Overall, we reduce the processing time from hours to minutes, for typical experimental conditions. Previously the limiting step in such experiments, […]
View View   Download Download (PDF)   
George Teodoro, Tony Pan, Tahsin M. Kurc, Lee Cooper, Jun Kong, Joel H. Saltz
In this paper we develop and experimentally evaluate a novel GPU-based implementation of the morphological reconstruction operation. This operation is commonly used in the segmentation and feature computation steps of image analysis pipelines, and often used as a component in other image processing operations. Our implementation builds on a fast hybrid CPU algorithm, which employs […]
View View   Download Download (PDF)   
Ya Shu
Optical techniques are a promising technology to realize high frequency ultrasound arrays. High sensitivity and broad bandwidth have been demonstrated with optoacoustic sensors based on thin film etalons. A thin film etalon consists of a transparent layer (e.g. photoresist or parylene) with gold coatings on a glass substrate. One-dimensional (1-D) data acquisition is realized by […]
View View   Download Download (PDF)   
Stefan Lang, Panos Drouvelis, Enkelejda Tafaj, Peter Bastian, Bert Sakmann
Neuron morphology is frequently used to classify cell-types in the mammalian cortex. Apart from the shape of the soma and the axonal projections, morphological classification is largely defined by the dendrites of a neuron and their subcellular compartments, referred to as dendritic spines. The dimensions of a neuron’s dendritic compartment, including its spines, is also […]
View View   Download Download (PDF)   
Page 1 of 212

* * *

* * *

* * *

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: