Jul, 28

Bayesian model comparison via sequential Monte Carlo

The sequential Monte Carlo (smc) methods have been widely used for modern scientific computation. Bayesian model comparison has been successfully applied in many fields. Yet there have been few researches on the use of smc for the purpose of Bayesian model comparison. This thesis studies different smc strategies for Bayesian model computation. In addition, various […]
Jul, 28

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

High-performance computing are based more and more in heterogeneous architectures and GPGPUs have become one of the main integrated blocks in these, as the recently emerged Mali GPU in embedded systems or the NVIDIA GPUs in HPC servers. In both GPGPUs, programming could become a hurdle that can limit their adoption, since the programmer has […]
Jul, 28

Understanding the ISA impact on GPU Architecture

The wide spread acceptance of GPU for parallel computation has created the demand for general purpose capabilities in GPU. In response, Industry is coming up rapidly with better architecture to support general purpose processing on GPUs. NVIDIA has come up with Tesla, Fermi and Kepler architecture. General Purpose Graphics Processing Units (GPGPU) are widely being […]
Jul, 28

Agent-based crowd simulation using GPU computing

The purpose of the research is to investigate agent-based approaches to virtual crowd simulation. Crowds are ubiquitous and are becoming an increasingly common phenomena in modern society, particularly in urban settings. As such, crowd simulation systems are becoming increasingly popular in training simulations, pedestrian modelling, emergency simulations, and multimedia. One of the primary challenges in […]
Jul, 28

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

A major challenge in computational neuroscience is to achieve high performance for real-time simulations of full size brain networks. Recent advances in GPU technology provide massively parallel, low-cost and efficient hardware that is widely available on the computer market. However, the comparatively low-level programming that is necessary to create an efficient GPU-compatible implementation of neuronal […]
Jul, 28

Improved Finite Difference Schemes for a 3-D Viscothermal Wave Equation on a GPU

Viscothermal effects in air lead to a damping of high frequencies over time. Such effects cannot be neglected in large-scale room acoustics simulations for the full audible bandwidth. In this study, full-bandwidth room acoustics is modelled using a variant of the three-dimensional wave equation including viscothermal losses in air following from a simplification of the […]
Jul, 28

CUDT: A CUDA Based Decision Tree Algorithm

Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in […]
Jul, 26

Towards fast and certified multiple-precision libraries

Many numerical problems require higher precision than the conventional floating-point (single, double) formats. One solution is to use multiple precision libraries such as GNU MPFR, which allow the manipulation of very high precision numbers. But their generality (they are able to handle numbers with millions of digits), is a quite heavy alternative when medium precision […]
Jul, 26

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

Graphics Processing Units (GPU) in today’s desktops can well be thought of as a high performance parallel processor. Traditionally, parallel computing is the usage of multiple computing resources to execute computational problems simultaneously. Such computations are possible using multi-core CPUs or computers with multiple CPUs or by using a network of computers in parallel. Today’s […]
Jul, 26

Performance Efficient DNA Sequence Detection on GPU Using Parallel Pattern Matching Approach

Bioinformatics is the field of science which applies computer science and information technology to the problems of biological science. One of the most useful applications of bioinformatics is sequence analysis. Sequence analysis, which is the process of subjecting a DNA, RNA to any wide range of analytical approaches, involves methodologies like sequence alignment and searches […]
Jul, 26

ReGen: Optimizing Genetic Selection Algorithms for Heterogeneous Computing

GenSel is a genetic selection analysis tool used to determine which genetic markers are informational for a given trait. Performing genetic selection related analyses is a time consuming and computationally expensive task. Due to an expected increase in the number of genotyped individuals, analysis times will increase dramatically. Therefore, optimization efforts must be made to […]
Jul, 26

Parallel solutions of static Hamilton-Jacobi equations for simulations of geological folds

Two new algorithms for numerical solution of static Hamilton-Jacobi equations are presented. These algorithms are designed to work efficiently on different parallel computing architectures, and numerical results for multicore CPU and GPU implementations are reported and discussed. The numerical experiments show that the proposed solution strategies scale well with the computational power of the hardware. […]
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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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