Jul, 7

Latency considerations of depth-first GPU ray tracing

Despite the potential divergence of depth-first ray tracing [AL09], it is nevertheless the most efficient approach on massively parallel graphics processors. Due to the use of specialized caching strategies that were originally developed for texture access, it has been shown to be compute rather than bandwidth limited. Especially with recents developments however, not only the […]
Jul, 7

Color Me Noisy: Example-based Rendering of Hand-colored Animations with Temporal Noise Control

We present an example-based approach to rendering hand-colored animations which delivers visual richness comparable to real artwork while enabling control over the amount of perceived temporal noise. This is important both for artistic purposes and viewing comfort, but is tedious or even intractable to achieve manually. We analyse typical features of real hand-colored animations and […]
Jul, 6

Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams

Random Forests is a classical ensemble method used to improve the performance of single tree classifiers. It is able to obtain superior performance by increasing the diversity of the single classifiers. However, in the more challenging context of evolving data streams, the classifier has also to be adaptive and work under very strict constraints of […]
Jul, 6

High performance MRI simulations of motion on multi-GPU systems

BACKGROUND: MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance […]
Jul, 6

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

Many problems in Computer Science can be modelled using graphs. Evaluating node centrality in complex networks, which can be considered equivalent to undirected graphs, provides an useful metric of the relative importance of each node inside the evaluated network. The knowledge on which the most central nodes are, has various applications, such as improving information […]
Jul, 6

Two-way partitioning of a recursive Gaussian filter in CUDA

Recursive Gaussian filters are more efficient than basic Gaussian filters when its filter window size is large. Since the computation of a point should start after the computation of its neighborhood points, recursive Gaussian filters are line oriented. Thus, the degree of parallelism is restricted by the length of the data image. In order to […]
Jul, 6

SimCommSys: taking the errors out of error-correcting code simulations

In this study, we present SimCommSys, a simulator of communication systems that we are releasing under an open source license. The core of the project is a set of C + + libraries defining communication system components and a distributed Monte Carlo simulator. Of principal interest is the error-control coding component, where various kinds of […]
Jul, 6

A Parallelized Implementation for H. 264 Real-time Encoding Scheme

In this paper, a high-speed video stream encoder for the H.264 digital video codec standard specification is accelerated with nowadays parallel processing architectures. Based on the parallel processing techniques with GPU’s, we used an OpenCL-based GPU kernel programs, and finally achieved a high-level CPU-GPU interoperability. In its design, our system makes the CPU perform all […]
Jul, 6

High-level Parallel Programming Support for Heterogeneous Systems

This master thesis focuses on several high-level parallel programming models for heterogeneous systems that have been becoming increasingly popular in the field of high-performance computing. Heterogeneous systems are an inexpensive and effective way for further performance improvements. A powerful combination of graphics processing units (GPUs) and central processing units (CPUs) is one of the most […]
Jul, 4

Writing self-adaptive codes for heterogeneous systems

Heterogeneous systems are becoming increasingly common. Relatedly, the popularity of OpenCL is growing, as it provides a unified mean to program a wide variety of devices including GPUs or multicore CPUs. More recently, the Heterogeneous Programming Library (HPL) targets the same variety of systems as OpenCL, intending to improve their programmability. The main drawback of […]
Jul, 4

Molecular dynamics simulations through GPU video games technologies

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements […]
Jul, 4

High-Level Energy Model of Embedded GPU for Real-Time Graphic Rendering

Embedded graphic processing unit (GPU) accelerates a real-time rendering process of a graphics application on mobile devices, however, at the cost of consuming a considerable portion of the system energy [1] which is one of the most critical design issues for battery-operated devices. To estimate the power consumption of a graphics application, conventional approaches collect […]
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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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