12138
M. Ploschner, B. Straka, K. Dholakia, T. Cizmar
We present a GPU accelerated toolbox for shaping the light propagation through multimode fibre using a spatial light modulator (SLM). The light is modulated before being coupled to the proximal end of the fibre in order to achieve arbitrary light patterns at the distal end of the fibre. First, the toolbox optimises the acquisition time […]
Koki Murano, Tomoyoshi Shimobaba, Atsushi Sugiyama, Naoki Takada, Takashi Kakue, Minoru Oikawa, Tomoyoshi Ito
We report fast computation of computer-generated holograms (CGHs) using Xeon Phi coprocessors, which have massively x86-based processors on one chip, recently released by Intel. CGHs can generate arbitrary light wavefronts, and therefore, are promising technology for many applications: for example, three-dimensional displays, diffractive optical elements, and the generation of arbitrary beams. CGHs incur enormous computational […]
View View   Download Download (PDF)   
Naoki Takada, Hiroaki Niwase, Hiromitsu Araki, Hirotaka Nakayama, Atsushi Sugiyama, Takashi Kakue, Tomoyoshi Shimobaba, Tomoyoshi Ito
We report a real-time electroholography using compact system composed of a multi-GPU environmental PC with four GPUs of Kepler architecture. Finally, our system can calculate 1,920×1,024 pixel CGH from the 3D object composed of 10,240 points in 40.3ms.
View View   Download Download (PDF)   
Koki Murano, Tomoyoshi Shimobaba, Takashi Kakue, Tomoyoshi Ito
Using parallel computing is an effective way to accelerate computer-generated hologram (CGH) calculation. In this paper, we implemented various CGH algorithms on Intel Xeon Phi Coprocessors. In the best case, we succeeded the CGH calculations 12-times faster than a CPU.
View View   Download Download (PDF)   
Carlos Trujillo, Jorge Garcia-Sucerquia
The huge video games market has propelled the development of hardware and software focused on making the game environment more realistic. Among such developments are graphics processing units (GPUs). These devices are intended to alleviate the central processing unit (CPU) of the host computer from the computation that creates "life" for video games. The GPUs […]
View View   Download Download (PDF)   
Joong-Seok Song, Jungsik Park, Sungwoo Kim, Jong-Il Park
Digital hologram generation methods commonly use computer generated hologram (CGH) algorithm. However, it requires complicated computation. Thus, this paper proposes an optimization method for a fast generation of digital hologram. The proposed method uses CUDA and OpenMP for multi-GPU. Also, it applies various optimization methods (variable fixation, vectorization, and loop unrolling) to a CGH algorithm. […]
View View   Download Download (PDF)   
Fahri Yaras, Hoonjong Kang, Levent Onural
A real-time multi-GPU color holographic video display system computes holograms from 3D video of a rigid object. System has three main stages; client, server and optics. 3D coordinate and texture information are kept in client and sent online to the server through the network. In the server stage, with the help of the parallel processing […]
View View   Download Download (PDF)   
Hoonjong Kang, Fahri Yaras, Levent Onural
A holographic fringe pattern generation methods is based on Fraunhofer diffraction and subsequent segmentation and approximation of the fringe pattern. Several modifications of the original algorithm are already proposed to improve the quality of reconstructions. We compare the quality of to the reconstructed images from different versions of this algorithm by taking the reconstructions from […]
View View   Download Download (PDF)   
Ivo Hanak, Martin Janda, Vaclav Skala
Application of the GPU to the computer generated holography is a topic of research for some time. While the majority of authors aim on performance, we aim on visual aspects. We present a new approach that is capable to synthesise a hologram of a scene described by triangles using the GPU and it is capable […]
View View   Download Download (PDF)   
Laszlo Orzo, Zoltan Gorocs, Istvan Szatmari, Szabolcs Tokes
Using Digital Holographic Microscopy (DHM) we can gather information from a whole volume and thus we can avoid the small depth of field constraint of the conventional microscopes. This way a volume inspection system can be constructed, which is capable to find, segment, collect, and later classify those objects that flow through an inspection chamber. […]
View View   Download Download (PDF)   
Lukas Ahrenberg, Andrew J. Page, Bryan M. Hennelly, John B. McDonald, Thomas J. Naughton
View-reconstruction and display is an important part of many applications in digital holography such as computer vision and microscopy. Thus far, this has been an offline procedure for megapixel sized holograms. This paper introduces an implementation of real-time view-reconstruction using programmable graphics hardware. The theory of Fresnel-based view-reconstruction is introduced, after which an implementation using […]
View View   Download Download (PDF)   
Zhuqing Zhu, Min Sun, Heping Ding, Shaotong Feng, Shouping Nie
The paper presents a numerical reconstruction method of digital holography based on graphic processing unit with MATLAB, which can obtain a calculation speed about 41 times faster than a CPU alone and make real-time system possible.
Page 1 of 212

* * *

* * *

Like us on Facebook

HGPU group

166 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1272 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. 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 13.1
  • SDK: AMD APP SDK 2.9
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 6.0.1, AMD APP SDK 2.9

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 hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: