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 […]
Apr, 11

DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

BACKGROUND: Next-generation sequencing technologies have led to the high-throughput production of sequence data (reads) at low cost. However, these reads are significantly shorter and more error-prone than conventional Sanger shotgun reads. This poses a challenge for the de novo assembly in terms of assembly quality and scalability for large-scale short read datasets. RESULTS: We present […]
Apr, 11

Simulation of bevel gear cutting with GPGPUs-performance and productivity

The desire for general purpose computation on graphics processing units caused the advance of new programming paradigms, e.g. OpenCL C/C++, CUDA C or the PGI Accelerator Model. In this paper, we apply these programming approaches to the software KegelSpan for simulating bevel gear cutting. This engineering application simulates an important manufacturing process in the automotive […]
Apr, 11

4th Workshop at ISCA’11 Emerging Applications and Many-core Architectures, EAMA

The goal of the workshop is to bring together application domain experts and computer architects to discuss emerging applications as well as their implications on current- and next-generation many-core architectures. The workshop focuses on the following two areas: Emerging application domains such as recognition/mining/synthesis (RMS), medical imaging, bioinformatics, visual computing, Web3D, datacenter workloads, business analytics, […]
Apr, 11

First ADBIS workshop on GPUs In Databases, GID 2011

The GPUs in Databases workshop is devoted to sharing the knowledge related to applying GPUs in Database environments and to discuss possible future development of this application domain.List of topics of the GID workshop includes (but is not limited to): 1. Data compression on GPUs * lossless/lossy compression and decompression * real time compression and […]
Apr, 10

GPU Accelerated Adams-Bashforth Multirate Discontinuous Galerkin FEM Simulation of High-Frequency Electromagnetic Fields

A multirate Adams-Bashforth (AB) scheme for simulation of electromagnetic wave propagation using the discontinuous Galerkin finite element method (DG-FEM) is presented. The algorithm is adapted such that single-instruction multiple-thread (SIMT) characteristic for the implementation on a graphics processing unit (GPU) is preserved. A domain decomposition strategy respecting the multirate classification for computation on multiple GPUs […]
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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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