Petr Svenda, Vaclav Matyas
Cryptanalysis of a cryptographic function like stream, block or hash function usually requires human cryptanalytical skills and labour. However, some automation is possible – e.g., by randomness testing suites like NIST/Diehard that can be applied to test statistical properties of cryptographic function outputs. Yet such testing suites are limited only to predefined statistical functions.We propose […]
Mads B. Eriksen, Soren Rasmussen
This master thesis treats the topic of non-linear parameter estimation using global optimization methods based on interval analysis (IA), accelerated by parallel implementation on a Graphics Processing Unit (GPU). Global optimization using IA is a mathematically rigorous Branch & Bound-type method, capable of reliably solving global optimization problems with continuously differentiable objective functions, even in […]
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Heru Suhartanto, Arry Yanuar, Ari Wibisono
One of application that needs high performance computing resources is molecular d ynamic. There is some software available that perform molecular dynamic, one of these is a well known GROMACS. Our previous experiment simulating molecular dynamics of Indonesian grown herbal compounds show sufficient speed up on 32 n odes Cluster computing environment. In order to […]
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Steven Hartung, Hemant Shukla, J. Patrick Miller, Carlton Pennypacker
Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution technique is used. Particularly suitable for large-scale images is a computationally intensive spatially-varying kernel. The underlying algorithm is inherently […]
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Joppe W. Bos
This paper presents a low-latency algorithm designed for parallel computer architectures to compute the scalar multiplication of elliptic curve points based on approaches from cryptographic side-channel analysis. A graphics processing unit implementation using a standardized elliptic curve over a 224-bit prime field, complying with the new 112-bit security level, computes the scalar multiplication in 1.9 […]
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Juan M. Cebrian, Gines D. Guerrero, Jose M. Garcia
In the last few years, Graphics Processing Units (GPUs) have become a great tool for massively parallel computing. GPUs are specifically designed for throughput and face several design challenges, specially what is known as the Power and Memory Walls. In these devices, available resources should be used to enhance performance and throughput, as the performance […]
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Hidehiko Masuhara, Yusuke Nishiguchi
We propose Ikra, a data-parallel extension to Ruby for general-purpose computing on graphical processing unit (GPGPU). Our approach is to provide a special array class with higher-order methods for describing computation on a GPU. With a static type inference system that identifies code fragments that shall be executed on a GPU and with a skeleton-based […]
Can Bekar, Tayfun Elmas, Semih Okur, Serdar Tasiran
We propose a novel approach for runtime verification on computers with a large number of computation cores, without any hardware extension to mainstream PC environment. The goal of the approach is making use of all hardware resources to decouple the computational overhead of traditional race checkers via parallelizing the runtime verification. We distinguish between two […]
Yang Chen, Yinsheng Li, Weimin Yu, Limin Luo, Wufan Chen, Christine Toumoulin
Tomographic reconstruction from noisy projections do not yield adequate results. Mathematically, this tomographic reconstruction represents an ill-posed problem due to information missing caused by the presence of noise. Maximum a posteriori (MAP) or Bayesian reconstruction methods offer possibilities to improve the image quality as compared with analytical methods in particular by introducing a prior to […]
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Hao Wu, Wenhua Zhang, Dazhi Gao, Xindao Yin, Yang Chen, Weidong Wang
Reducing the radiation dose delivered to patients has been an important concern since the introduction of X-ray computed tomography (CT). However, low-dose CT images tend to be severely degraded by noise. This paper proposes using parallelized non-local means (PNM) under a computation framework for improving low-dose X-ray CT images. For the proposed PNM method, the […]
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Adam J. Shook
A method of generating Deep Shadow Maps from a 3D data set is presented. This method uses ray tracing on the GPU to accumulate opacity and store them in a deep shadow map. The deep shadow map is then sampled based on view direction to determine how much light got to a particular fragment. The […]
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Tayfun Elmas, Semih Okur, Serdar Tasiran
We propose a novel approach for runtime monitoring and verification on computers with a large number of computation cores. The goal of the approach is to minimize the impact of runtime verification on the performance of the application being monitored. We distinguish between two kinds of computational overhead: (i) overhead caused by instrumentation and/or logging, […]
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Free GPU computing nodes at

Registered users can now run their OpenCL application at 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 11.4
  • SDK: AMD APP SDK 2.8
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 5.0.35, AMD APP SDK 2.8

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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