Sergiy Gogolenko, Zhaojun Bai, Richard Scalettar
We present a block structured orthogonal factorization (BSOF) algorithm and its parallelization for computing the inversion of block p-cyclic matrices.We aim at the high performance on multicores with GPU accelerators. We provide a quantitative performance model for optimal host-device load balance, and validate the model through numerical tests. Benchmarking results show that the parallel BSOF […]
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell
Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models. The framework is a BSD-licensed C++ library with Python and MATLAB bindings for training and deploying general-purpose convolutional neural networks and other deep models efficiently on commodity architectures. Caffe fits industry and […]
Gordon Inggs, David Thomas, Wayne Luk
We advocate a domain specific software development methodology for heterogeneous computing platforms such as Multicore CPUs, GPUs and FPGAs. We argue that three specific benefits are realised from adopting such an approach: portable, efficient implementations across heterogeneous platforms; domain specific metrics of quality that characterise platforms in a form software developers will understand; automatic, optimal […]
David H. Eberly
An In-Depth, Practical Guide to GPGPU Programming Using Direct3D 11. GPGPU Programming for Games and Science demonstrates how to achieve the following requirements to tackle practical problems in computer science and software engineering: Robustness, Accuracy, Speed, Quality source code that is easily maintained, reusable, and readable. The book primarily addresses programming on a graphics processing […]
Bo Fang
While graphics processing units (GPUs) have gained wide adoption as accelerators for general-purpose applications (GPGPU), the end-to-end reliability implications of their use have not been quantified. Fault injection is a widely used method for evaluating the reliability of applications. However, building a fault injector for GPGPU applications is challenging due to their massive parallelism, which […]
Peng Li, Guodong Li, Ganesh Gopalakrishnan
Even the careful GPU programmer can inadvertently introduce data races while writing and optimizing code. Currently available GPU race checking methods fall short either in terms of their formal guarantees, ease of use, or practicality. Existing symbolic methods: (1) do not fully support existing CUDA kernels; (2) may require user-specified assertions or invariants; (3) often […]
Wookhyun Han, Hwidong Bae, Hyosu Kim, Jiyoen Lee, Insik Shin
GPU (General-Purpose computation on Graphics Processing Units) offers an effective computing platform to accelerate a wide class of data-parallel computing. Multi-GPU’s appear as an attractive platform to speed up the computation of data-parallel GPU. This paper aims to explore the feasibility of relaxing the task-level restriction of single GPU use in multi-GPU real-time systems.We develop […]
Hyunsu Cho, Peter A. Yoon
Divide-and-conquer algorithm is a numerically stable and efficient algorithm that computes the eigenvalues and eigenvectors of a symmetric tridiagonal matrix. We often face the situation where the input matrix fits into the main memory but not into the on-chip memory of a GPU device. We present an out-of-core implementation where only part of the input […]
Zhisong Fu, Harish Kumar Dasari, Martin Berzins, Bryan Thompson
Fast, scalable, low-cost, and low-power execution of parallel graph algorithms is important for a wide variety of commercial and public sector applications. Breadth First Search (BFS) imposes an extreme burden on memory bandwidth and network communications and has been proposed as a benchmark that may be used to evaluate current and future parallel computers. Hardware […]
Trevor L. McDonell
It is well acknowledged that the dominant mechanism for scaling processor performance has become to increase the number of cores on a chip, rather than improve the performance of a single core. However, harnessing these extra cores to improve single application performance remains an extremely challenging task. A recent trend has been to use commodity […]
Mehran Maghoumi
Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP’s problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages […]
Vassilis Vassiliadis
The target of this thesis is to optimize memory management on heterogeneous systems. Our approach involves performing memory access pattern analysis on kernels in order to produce an accurate estimation of the memory usage. This information is produced in the form of array ranges describing which elements are accessed as well as whether they are […]
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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

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