Jiajia Li, Xingjian Li, Guangming Tan, Mingyu Chen, Ninghui Sun
In heterogeneous systems that include CPUs and GPUs, the data transfers between these components play a critical role in determining the performance of applications. Software pipelining is a common approach to mitigate the overheads of those transfers. In this paper we investigate advanced software-pipelining optimizations for the double-precision general matrix multiplication (DGEMM) algorithm running on […]
Ali Khajeh Saeed
Graphics processing units function well as high performance computing devices for scientific computing. The non-standard processor architecture and high memory bandwidth allow graphics processing units (GPUs) to provide some of the best performance in terms of FLOPS per dollar. Recently these capabilities became accessible for general purpose computations with the CUDA programming environment on NVIDIA […]
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Mats Johansson, Oscar Winter
General-Purpose computing using Graphics Processing Units (GPGPU) has been an area of active research for many years. During 2009 and 2010 much has happened in the GPGPU research field with the release of the Open Computing Language (OpenCL) programming framework and the new NVIDIA Fermi Graphics Processing Unit (GPU) architecture. This thesis explores the hardware […]
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Rahul Garg, Jose Nelson Amaral
A new compilation framework enables the execution of numerical-intensive applications in an execution environment that is formed by multi-core Central Processing Units (CPUs) and Graphics Processing Units (GPUs). A critical innovation is the use of a variation of Linear Memory Access Descriptors (LMADs) to analyze loop nests and determine automatically which memory locations must be […]
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Rob V. van Nieuwpoort, John W. Romein
A recent development in radio astronomy is to replace traditional dishes with many small antennas. The signals are combined to form one large, virtual telescope. The enormous data streams are cross-correlated to filter out noise. This is especially challenging, since the computational demands grow quadratically with the number of data streams. Moreover, the correlator is […]
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Thilo Schmitt, Alexander Weggerle, Christian Himpel, Peter Schulthess
General Purpose Computation on Graphics Processing Units (GPGPU) makes it possible to use the massive computing power of modern graphics cards for generic high-performance computing. However, the new virtualization technologies will typically not support high-performance graphics cards and as a consequence GPGPU resources can not be used in typical virtualization setups. In this paper we […]
Xifei Wu, Hui Xiang, Peng Lu
This paper presents a parallel algorithm designed for Super-resolution Image Reconstruction based on Compressive sensing in the ATI Stream platform. In the accelerating process, we select part of the serial program as the objects to be sped up according to the execution time of each stage, set appropriate parallel granularity to make full use of […]
Yi Shan, Tianji Wu, Yu Wang, Bo Wang, Zilong Wang, Ningyi Xu, Huazhong Yang
Sparse matrix-vector multiplication (SpMV) is a fundamental operation for many applications. Many studies have been done to implement the SpMV on different platforms, while few work focused on the very large scale datasets with millions of dimensions. This paper addresses the challenges of implementing large scale SpMV with FPGA and GPU in the application of […]
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Amr Bayoumi, Michael Chu, Yasser Hanafy, Patricia Harrell, Gamal Refai-Ahmed
This continuing exploration of GPU technology examines ATI Stream technology and its use in scientific and engineering applications.
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Canqun Yang, Feng Wang, Yunfei Du, Juan Chen, Jie Liu, Huizhan Yi, Kai Lu
In this paper, we describe our experiment developing an implementation of the Linpack benchmark for TianHe-1, a petascale CPU/GPU supercomputer system, the largest GPU-accelerated system ever attempted before. An adaptive optimization framework is presented to balance the workload distribution across the GPUs and CPUs with the negligible runtime overhead, resulting in the better performance than […]
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Ryan Taylor, Xiaoming Li
Optimizing programs for Graphic Processing Unit (GPU) requires thorough knowledge about the values of architectural features for the new computing platform. However, this knowledge is frequently unavailable, e.g., due to insufficient documentation, which is probably a result of the infancy of general purpose computing on the GPU. What makes the modeling of program performance on […]
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Di Wu, Tianji Wu, Yi Shan, Yu Wang, Yong He, Ningyi Xu, Huazhong Yang
The research on complex Brain Networks plays a vital role in understanding the connectivity patterns of the human brain and disease-related alterations. Recent studies have suggested a noninvasive way to model and analyze human brain networks by using multi-modal imaging and graph theoretical approaches. Both the construction and analysis of the Brain Networks require tremendous […]
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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
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  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
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  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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