7034
Robert F. Lucas, Gene Wagenbreth, John J. Tran, Dan M. Davis
For many finite element problems, when represented as sparse matrices, iterative solvers are found to be unreliable because they can impose computational bottlenecks. Early pioneering work by Duff et al, explored an alternative strategy called multifrontal sparse matrix factorization. This approach, by representing the sparse problem as a tree of dense systems, maps well to […]
View View   Download Download (PDF)   
S. Ihnatsenka
The performance potential for simulating quantum electron transport on graphical processing units (GPUs) is studied. Using graphene ribbons of realistic sizes as an example it is shown that GPUs provide significant speed-ups in comparison to central processing units as the transverse dimension of the ribbon grows. The recursive Green’s function algorithm is employed and implementation […]
View View   Download Download (PDF)   
Prekshu Ajmera, Rhushabh Goradia, Sharat Chandran, Srinivas Aluru
Space Filling Curves (SFC) are particularly useful in linearization of data living in two and three dimensional spaces and have been used in a number of applications in scientific computing, and visualization. Interestingly, octrees, another versatile data structure in computer graphics, can be viewed as multiple SFCs at varying resolutions, albeit with parent-child relationship. In […]
View View   Download Download (PDF)   
Carl-Inge Colombo Nilsen, Ines Hafizovic
In this paper we investigate the use of GPUs as digital beamformers. We specify a parallel implementation of a beamformer in time and frequency domain and measure its performance. We also give examples of the processing limits of NVIDIA Geforce 8800 GPU with respect to application parameters: number of sensors, sampling frequency, bandwidth, and number […]
View View   Download Download (PDF)   
Guido Klingbeil, Radek Erban, Mike Giles, Philip K. Maini
Motivation: The importance of stochasticity in biological systems is becoming increasingly recognised and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU which exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency […]
Virat Agarwal, Lurng-Kuo Liu, David A. Bader
High performance computing is critical for financial markets where analysts seek to accelerate complex optimizations such as pricing engines to maintain a competitive edge. In this paper we investigate the performance of financial workloads on the Sony-Toshiba- IBM Cell Broadband Engine, a heterogeneous multicore chip architected for intensive gaming applications and high performance computing. We […]
View View   Download Download (PDF)   
Henrik Malm, Magnus Oskarsson, Eric Warrant, Petrik Clarberg, Jon Hasselgren, Calle Lejdfors
A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especially targeted. Smoothing kernels that automatically adapt to the local spatio-temporal intensity structure in the image sequences are constructed in order to preserve and enhance fine spatial […]
View View   Download Download (PDF)   
Bingsheng He, Naga K. Govindaraju, Qiong Luo, Burton Smith
Gather and scatter are two fundamental data-parallel operations, where a large number of data items are read (gathered) from or are written (scattered) to given locations. In this paper, we study these two operations on graphics processing units (GPUs).
View View   Download Download (PDF)   
Mathieu Giraud, Jean-Stephane Varre
Position Weight Matrices (PWMs) are broadly used in computational biology. The basic problems, Scan and Multiscan, aim to find all the occurrences of a given PWM or a set of PWMs in long sequences. Some other PWM tasks share a common NP-hard subproblem, ScoreDistribution The existing algorithms rely on the enumeration on a large set […]

* * *

* * *

Like us on Facebook

HGPU group

128 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1191 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: