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Posts

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 […]
Jul, 22

Compressed sensing using hidden Markov models with application to vision based aircraft tracking

This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering […]
Jul, 22

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

Parallel computing has been the enabling technology of high-end machines for many years. Now, it has finally become the ubiquitous key to the efficient use of any kind of multi-processor computer architecture, from smart phones, tablets, embedded systems and cloud computing up to exascale computers. _x000D_ This book presents the proceedings of ParCo2013 – the […]
Jul, 22

High Performance Low Power Embedded Vision Systems

Human vision is a complex combination of physical, psychological and neurological processes that allow us to interact with our environment. We use vision effortlessly to detect, identify and track objects, to navigate and to create a conceptual map of our surroundings. The goal of computer vision is to design computer systems that are capable of […]
Jul, 20

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

Fast growing computing power on commodity parallel hardware makes it both an opportunity and a challenge to use modern hardware for large-scale data management. While GPU (Graphics Processing Unit) computing is conceptually an excellent match for spatial data management which is both data and computing intensive, the complexity of multi-dimensional spatial indexing and query processing […]
Jul, 20

An execution model for adaptive load-balancing on multicore and multi-GPU systems

As computing systems increase in size and parallelism, it becomes more and more difficult to balance workload during program execution. Heterogeneous systems further complicate the situation, as their different constituent compute resources may consume work at different rates, and may have affinity for different kinds of work. Traditional approaches to load-balancing fail to fully address […]
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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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