13801
Shay I. Heizler, David A. Kessler
We study the high-velocity regime mode-I fracture instability using large scale simulations. At large driving displacements, the pattern of a single, steady-state crack that propagates in the midline of the sample breaks down, and small microbranches start to appear near the main crack. Some of the features of those microbranches have been reproduced qualitatively in […]
View View   Download Download (PDF)   
Christopher Fougner, Stephen Boyd
In a recent paper, Parikh and Boyd describe a method for solving a convex optimization problem, where each iteration involves evaluating a proximal operator and projection onto a subspace. In this paper we address the critical practical issues of how to select the proximal parameter in each iteration, and how to scale the original problem […]
View View   Download Download (PDF)   
Dayong Wang, Anil K. Jain
Face retrieval is an enabling technology for many applications, including automatic face annotation, deduplication, and surveillance. In this paper, we propose a face retrieval system which combines a k-NN search procedure with a COTS matcher (PittPatt) in a cascaded manner. In particular, given a query face, we first pre-filter the gallery set and find the […]
View View   Download Download (PDF)   
H.A. Du Nguyen, Zaid Al-Ars, Georgios Smaragdos, Christos Strydis
The Inferior Olive (IO) in the brain, in conjunction with the cerebellum, is responsible for crucial sensorimotor-integration functions in humans. In this paper, we simulate a computationally challenging IO neuron model consisting of three compartments per neuron in a network arrangement on GPU platforms. Several GPU platforms of the two latest NVIDIA GPU architectures (Fermi, […]
View View   Download Download (PDF)   
Gloria Ortega Lopez
This thesis, entitled "High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study" investigates the computational issues related to the resolution of linear systems of equations which come from the discretization of physical models described by means of Partial Differential Equations (PDEs). These physical models are conceived for the […]
Benjamin Schmid, Jan Huisken
In light-sheet microscopy, overall image content and resolution are improved by acquiring and fusing multiple views of the sample from different directions. State-of-the-art multi-view (MV) deconvolution employs the point spread functions (PSF) of the different views to simultaneously fuse and deconvolve the images in 3D, but processing takes a multiple of the acquisition time and […]
Zi'ang Ding, Zhanping Liu, Yang Yu, Wei Chen
This paper presents an accurate parallel implementation of unsteady flow line integral convolution (UFLIC) for high-performance visualization of large time-varying flows. Our approach differs from previous implementations by using a novel value scattering+gathering mechanism to parallelize UFLIC and designing a pathline reuse strategy to reduce the computational cost of pathline integration. By exploiting the massive […]
View View   Download Download (PDF)   
Richard Wilton, Tamas Budavari, Ben Langmead, Sarah J. Wheelan, Steven L. Salzberg, Alexander S. Szalay
When computing alignments of DNA sequences to a large genome, a key element in achieving high processing throughput is to prioritize locations in the genome where high-scoring mappings might be expected. We formulated this task as a series of list-processing operations that can be efficiently performed on graphics processing unit (GPU) hardware.We followed this approach […]
Xiaowen Chu, Chengjian Liu, Kai Ouyang, Ling Sing Yung, Hai Liu, Yiu-Wing Leung
In recent years, erasure coding has been adopted by large-scale cloud storage systems to replace data replication. With the increase of disk I/O throughput and network bandwidth, the speed of erasure coding becomes one of the key system bottlenecks. In this paper, we propose to offload the task of erasure coding to Graphics Processing Units […]
View View   Download Download (PDF)   
Lena Oden, Benjamin Klenk, Holger Froning
GPUs are widely used in high performance computing, due to their high computational power and high performance per Watt. Still, one of the main bottlenecks of GPU-accelerated cluster computing is the data transfer between distributed GPUs. This not only affects performance, but also power consumption. The most common way to utilize a GPU cluster is […]
View View   Download Download (PDF)   
Yuki Tsujita, Toshio Endo
Recently large scale scientific computation on heterogeneous supercomputers equipped with accelerators is receiving attraction. However, traditional static job execution methods and memory management methods are insufficient in order to harness heterogeneous computing resources including memory efficiently, since they introduce larger data movement costs and lower resource usage. This paper takes the Cholesky decomposition computation, which […]
View View   Download Download (PDF)   
Vasvi Kakkad
Advances in technology have given rise to applications that are deployed on wireless sensor networks (WSNs), the cloud, and the Internet of things. There are many emerging applications, some of which include sensor-based monitoring, web traffic processing, and network monitoring. These applications collect large amount of data as an unbounded sequence of events and process […]
View View   Download Download (PDF)   
Page 1 of 49612345...102030...Last »

* * *

* * *

Like us on Facebook

HGPU group

231 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1429 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: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • 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: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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 © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: