12545

Posts

Jul, 24

ADHA: Automatic Data layout framework for Heterogeneous Architectures

Data layouts play a crucial role in determining the performance of a given application running on a given architecture. Existing parallel programming frameworks for both multicore and heterogeneous systems leave the onus of selecting a data layout to the programmer. Therefore, shifting the burden of data layout selection to optimizing compilers can greatly enhance programmer […]
Jul, 24

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

We have implemented, tested, validated and benchmarked a scalable parallel implementations of the integral histogram algorithm critical for computer vision tasks for fast multiscale subwindow-based object searching, motion analysis and content-based image retrieval applications. Several integral histogram kernels using CUDA optimizations for many core GPUs were investigated. The integral histogram algorithm was also parallelized using […]
Jul, 24

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

The last decade saw the long tradition of frequency scaling of processing units grind to a halt, and efforts were re-focused on maintaining computational growth by other means; such as increased parallelism, deep memory hierarchies and complex execution logic. After a long period of "boring productivity", a host of new architectures, accelerators, programming languages and […]
Jul, 24

Electromagnetic Computation and Visualization of Transmission Particle Model and its Simulation Based on GPU

Electromagnetic calculation plays an important role in both military and civic fields. Some methods and models proposed for calculation of electromagnetic wave propagation in a large range, bring heavy burden in CPU computation, and also require huge amount of memory. Using the GPU to accelerate computation and visualization can reduce the computational burden on the […]
Jul, 24

Parallel kinetic Monte Carlo simulation of Coulomb glasses

We develop a parallel rejection algorithm to tackle the problem of low acceptance in Monte Carlo methods, and apply it to the simulation of the hopping conduction in Coulomb glasses using Graphics Processing Units, for which we also parallelize the update of local energies. In two dimensions, our parallel code achieves speedups of up to […]
Jul, 23

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

Local search metaheuristic algorithms are proven & powerful combinatorial optimization strategies to tackle hard problems like traveling salesman problem. These algorithms explore & evaluate neighbors of a single solution. Time Consuming LSM algorithms can be improved by parallelizing exploration & evaluation of neighbors of a solution. GPU architecture is suitable for algorithms of single program […]
Jul, 23

A Study on GPU Computing and Accelerating Simulation of Sedimentary Rock Structure

General Purpose Computation on Graphics Processing Units (GP-GPU) has been recognized as viable and inexpensive technique in recent trends of parallel computing. Earlier this technology has only been used as commodity processing units in video cards which have been used for generating graphics in High resolution. This technology provides greater computational power with its high […]
Jul, 23

A Multi-GPU Compute Solution for Optimized Genomic Selection Analysis

Many modern-day Bioinformatics algorithms rely heavily on statistical models to analyze their biological data. Some of these statistical models lend themselves nicely to standard high performance computing optimizations such as parallelism, while others do not. One such algorithm is Markov Chain Monte Carlo (MCMC). In this thesis, we present a heterogeneous compute solution for optimizing […]
Jul, 23

Accelerating Volume Image Registration through Correlation Ratio based Methods on GPUs

Volume image registration is a basic component of medical image processing which traditionally requires long computation time. In this paper, we propose five Correlation Ratio based schemes that explore the design space for Graphics Processing Unit (GPU) acceleration. Through comparisons among these five schemes, we present the trade-off between benefits and overheads of introducing shadow […]
Jul, 23

Faster Multipattern Matching System on GPU Based on Aho-Corasick Algorithm

GPU Computing Have attracted lots of attention due to their large amount of data processing. The algorithm proposed in this paper is use for exact pattern matching on GPU. Among some famous algorithms, the Aho-Corasick Algorithm match multiple pattern simultaneously. a Traditional Aho-Corasick Algorithm matches the pattern by traversing state machine, known as Deterministic finite […]
Jul, 22

Dark Sky Simulations: Early Data Release

The Dark Sky Simulations are an ongoing series of cosmological N-body simulations designed to provide a quantitative and accessible model of the evolution of the large-scale Universe. Such models are essential for many aspects of the study of dark matter and dark energy, since we lack a sufficiently accurate analytic model of non-linear gravitational clustering. […]
Jul, 22

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

As microfluidics has been applied extensively in many cell and biochemical applications, monitoring the related processes is an important requirement. In this work, we design and fabricate a high-throughput microfluidic device which contains 32 microchambers to perform automated parallel microfluidic operations and monitoring on an automated stage of a microscope. Images are captured at multiple […]
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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.

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