14047

Applications

I.A. Surmin, S.I. Bastrakov, E.S. Efimenko, A.A. Gonoskov, A.V. Korzhimanov, I.B. Meyerov
This paper concerns development of a high-performance implementation of the Particle-in-Cell method for plasma simulation on Intel Xeon Phi coprocessors. We discuss suitability of the method for Xeon Phi architecture and present our experience of porting and optimization of the existing parallel Particle-in-Cell code PICADOR. Direct porting with no code modification gives performance on Xeon […]
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Dominik Charousset, Raphael Hiesgen, Thomas C. Schmidt
The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model. […]
Gary Lawson, Masha Sosonkina, Yuzhong Shen
In the push for exascale computing, energy efficiency is of utmost concern. System architectures often adopt accelerators to hasten application execution at the cost of power. The Intel Xeon Phi co-processor is unique accelerator that offers application designers high degrees of parallelism, energy-efficient cores, and various execution modes. To explore the vast number of available […]
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Toshiya Hachisuka
Ray tracing on GPUs is becoming quite common these days. There are many publicly available documents on how to implement basic ray tracing on GPUs for spheres and implicit surfaces. We even have some general frameworks for ray tracing on GPUs. We however hardly find details on how to implement more complex ray tracing algorithms […]
Mingzhe Wang, Bo Wang, Qiu He, Xiuxiu Liu, Kunshuai Zhu
Matlab is very widely used in scientific computing, but Matlab computational efficiency is lower than C language program. In order to improve the computing speed, some toolbox can use GPU to accelerate the computation. This paper describes GPU working principle, our experiments and results analysis of parallel computing by using GPU based on Matlab. Experimental […]
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Johann Hauswald, Yiping Kang, Michael A. Laurenzano, Quan Chen, Cheng Li, Trevor Mudge, Ronald G. Dreslinski, Jason Mars, Lingjia Tang
As applications such as Apple Siri, Google Now, Microsoft Cortana, and Amazon Echo continue to gain traction, webservice companies are adopting large deep neural networks (DNN) for machine learning challenges such as image processing, speech recognition, natural language processing, among others. A number of open questions arise as to the design of a server platform […]
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Sebastian Oude Voshaar
In this thesis, the nucleation rate of almost hard spheres in a course-grained fluid is measured to study the effects of an explicit solvent on the nucleation rate. Previous measurements show a discrepancy between physical measurements and simulations, where the latter all used implicit solvents. In this thesis, the fluid is approximated using Stochastic Rotation […]
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Freddie Astrom, Michael Felsberg
Many image processing methods such as corner detection,optical flow and iterative enhancement make use of image tensors. Generally, these tensors are estimated using the structure tensor. In this work we show that the gradient energy tensor can be used as an alternativeto the structure tensor in several cases. We apply the gradient energy tensor to […]
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Fatemah Ramzy AlZayer
We optimize parameters in OpenACC clauses for a stencil evaluation kernel executed on Graphical Processing Units (GPUs) using a variety of machine learning and optimization search algorithms, individually and in hybrid combinations, and compare execution time performance to the best possible obtained from brute force search. Several auto-tuning techniques – historic learning, random walk, simulated […]
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Yushan Wang
In this PhD thesis, we present our research in the domain of high performance software for computational fluid dynamics (CFD). With the increasing demand of high-resolution simulations, there is a need of numerical solvers that can fully take advantage of current manycore accelerated parallel architectures. In this thesis we focus more specifically on developing an […]
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AJ Guillon
Today servers, desktops, mobile devices, and embedded systems contain many processors in addition to the CPU that runs programs. These extra processors are generally called accelerators and could be a GPU, FPGA, Xeon Phi, or other programmable device. There are many types of accelerators available, from many vendors, for many different environments. Khronos developed the […]
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Ondrej Mosnacek
Key derivation functions are a key element of many cryptographic applications. Password-based key derivation functions are designed specifically to derive cryptographic keys from low-entropy sources (such as passwords or passphrases) and to counter brute-force and dictionary attacks. However, the most widely adopted standard for password-based key derivation, PBKDF2, as implemented in most applications, is highly […]
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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: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • 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: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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