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Posts

Apr, 12

GPU Accelerated Path-Planning for Multi-agents in Virtual Environments

Many games are populated by synthetic humanoid actors that act as autonomous agents. The animation of humanoids in real-time applications is yet a challenge if the problem involves attaining a precise location in a virtual world (path-planning), and moving realistically according to its own personality, intentions and mood (motion planning). In this paper we present […]
Apr, 12

The fast evaluation of hidden Markov models on GPU

It is compute-intensive to evaluate the probability of an observation sequence on a hidden Markov model. Some fast algorithms exit, the forward-backward procedure is the most popular one among them. The forward-backward procedure can save much computation, but its time complexity is N^2T, in other words, there is a high computational complexity in the algorithm. […]
Apr, 12

Accelerating System-Level Design Tasks Using Commodity Graphics Hardware: A Case Study

Many system-level design tasks (e.g. timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-hard). As a result, they involve high running times even for mid-sized problems. In this paper we explore the possibility of using commodity graphics processing units (GPUs) to accelerate such tasks that commonly arise in […]
Apr, 12

Simulating Spiking Neural P systems without delays using GPUs

We present in this paper our work regarding simulating a type of P system known as a spiking neural P system (SNP system) using graphics processing units (GPUs). GPUs, because of their architectural optimization for parallel computations, are well-suited for highly parallelizable problems. Due to the advent of general purpose GPU computing in recent years, […]
Apr, 11

Interactive Simulation and Visualization of Fluids with Surface Raycasting

We present a method to couple particle-based fluid simulation methods such as Smoothed Particle Hydrodynamics (SPH) and volume rendering in order to visualize the fluid. A volume is generated from the fluid’s implicit density field so volume raycasting can be performed to render the surface on the GPU. The volume generation algorithm is also implemented […]
Apr, 11

Real-time 3-D object recognition using scale invariant feature transform and stereo vision

Scale invariant feature transform (SIFT) and stereo vision are applied together to recognize objects in real time. This work reports the performance of a GPU (graphic processing unit) based real-time feature detector in capturing the features of 3D objects when the objects undergo rotational and translational motions in cluttered backgrounds. We have compared the performance […]
Apr, 11

EXOCHI: architecture and programming environment for a heterogeneous multi-core multithreaded system

Future mainstream microprocessors will likely integrate specialized accelerators, such as GPUs, onto a single die to achieve better performance and power efficiency. However, it remains a keen challenge to program such a heterogeneous multicore platform, since these specialized accelerators feature ISAs and functionality that are significantly different from the general purpose CPU cores. In this […]
Apr, 11

CULA: hybrid GPU accelerated linear algebra routines

The modern graphics processing unit (GPU) found in many standard personal computers is a highly parallel math processor capable of nearly 1 TFLOPS peak throughput at a cost similar to a high-end CPU and an excellent FLOPS/watt ratio. High-level linear algebra operations are computationally intense, often requiring O(N3) operations and would seem a natural fit […]
Apr, 11

Clustering coefficient queries on massive dynamic social networks

The Clustering Coefficient (CC) is a fundamental measure in social network analysis assessing the degree to which nodes tend to cluster together. While CC computation on static graphs is well studied, emerging applications have new requirements for online query of the “global” CC of a given subset of a graph. As social networks are widely […]
Apr, 11

A GPU-based implementation of the MRF algorithm in ITK package

The analysis of medical image, in particular Magnetic Resonance Imaging (MRI), is a very useful tool to help the neurologists on the diagnosis. One of the stages on the analysis of MRI is given by a classification based on the Markov Random Fields (MRF) method. It is possible to find in the literature several packages […]
Apr, 11

GPU-computing in econophysics and statistical physics

A recent trend in computer science and related fields is general purpose computing on graphics processing units (GPUs), which can yield impressive performance. With multiple cores connected by high memory bandwidth, today’s GPUs offer resources for non-graphics parallel processing. This article provides a brief introduction into the field of GPU computing and includes examples. In […]
Apr, 11

Exact and complete short read alignment to microbial genomes using GPU programming

MOTIVATION: The introduction of next generation sequencing techniques and especially the high-throughput systems Solexa (Illumina Inc.) and SOLiD (ABI) made the mapping of short reads to reference sequences a standard application in modern bioinformatics. Short read alignment is needed for reference based re-sequencing of complete genomes as well as for gene expression analysis based on […]
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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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