Jul, 12

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We have presented several contributions on the collision detection optimization centered on hardware performance. We focus on the first step (Broad-phase) and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute […]
Jul, 12

Parallelized Hierarchical Expected Matching Probability for Multiple Sequence Alignment

Sequence alignment of two or more than two biological sequences such as protein, DNA (Deoxyribonucleic acid) or RNA (Ribonucleic acid) is called MSA (Multiple Sequence Alignment). Sequence homology can be inferred from the resulting MSA. Existing System uses dynamic programming technique which suffers from exponential growth of time as the sequence grows. A Hierarchical Expected […]
Jul, 12

Using the GPU for Fast Symmetry-Based Dense Stereo Matching in High Resolution Images

SymStereo is a new algorithm used for stereo estimation. Instead of measuring photo-similarity, it proposes novel cost functions that measure symmetry for evaluating the likelihood of two pixels being a match. In this work we propose a parallel approach of the LogN matching cost variant of SymStereo capable of processing pairs of images in real-time […]
Jul, 11

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

In earlier times, computer systems had only a single core or processor. In these computers, the number of transistors on-chip (i.e. on the processor) doubled every two years and all applications enjoyed free speedup. Subsequently, with more and more transistors being packed on-chip, power consumption became an issue, frequency scaling reached its limits and industry […]
Jul, 11

Programming-Model Centric Debugging for Multicore Embedded Systems

In this thesis, we propose to study interactive debugging of applications running on embedded systems Multi-Processor System on Chip (MPSoC). A literature study showed that nowadays, the design and development of these applications rely more and more on programming models and development frameworks. These environments gather established algorithmic and programming good-practices, and hence speed up […]
Jul, 11

Development of a Restricted Additive Schwarz Preconditioner for Sparse Linear Systems on NVIDIA GPU

In this paper, we develop, study and implement a restricted additive Schwarz (RAS) preconditioner for speedup of the solution of sparse linear systems on NVIDIA Tesla GPU. A novel algorithm for constructing this preconditioner is proposed. This algorithm involves two phases. In the first phase, the construction of the RAS preconditioner is transformed to an […]
Jul, 11

Accelerating Preconditioned Iterative Linear Solvers on GPU

Linear systems are required to solve in many scientific applications and the solution of these systems often dominates the total running time. In this paper, we introduce our work on developing parallel linear solvers and preconditioners for solving large sparse linear systems using NVIDIA GPUs. We develop a new sparse matrix-vector multiplication kernel and a […]
Jul, 11

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Multiple matching algorithms are used to locate the occurrences of patterns from a finite pattern set in a large input string. Aho-Corasick and Wu-Manber, two of the most well known algorithms for multiple matching require an increased computing power, particularly in cases where large-size datasets must be processed, as is common in computational biology applications. […]
Jul, 11

Parallelization of BFS Graph Algorithm using CUDA

Graphs play a very important role in the field of Science and Technology for finding the shortest distance between any two places. This Paper demonstrate the recent technology named as CUDA (Compute Unified Device Architecture) working for BFS Graph Algorithm. There are some Graph algorithms are fundamental to many disciplines and application areas. Large graphs […]
Jul, 11

Algorithms and Data Structures for Interactive Ray Tracing on Commodity Hardware

Rendering methods based on ray tracing provide high image realism, but have been historically regarded as offline only. This has changed in the past decade, due to significant advances in the construction and traversal performance of acceleration structures and the efficient use of data-parallel processing. Today, all major graphics companies offer real-time ray tracing solutions. […]
Jul, 11

Hybrid Particle Lattice Boltzmann Shallow Water for interactive fluid simulations

We introduce a hybrid approach for the simulation of fluids based in the Lattice Boltzmann Method for Shallow Waters and particle systems. Our modified LBM Shallow Waters can handle arbitrary underlying terrain and arbitrary fluid depth. It also introduces a novel and simplified method of tracking dry-wet regions. Dynamic rigid bodies are also included in […]
Jul, 11

Visualization and Correction of Automated Segmentation, Tracking and Lineaging from 5-D Stem Cell Image Sequences

RESULTS: We present an application that enables the quantitative analysis of multichannel 5-D (x, y, z, t, channel) and large montage confocal fluorescence microscopy images. The image sequences show stem cells together with blood vessels, enabling quantification of the dynamic behaviors of stem cells in relation to their vascular niche, with applications in developmental and […]
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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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