Aug, 10

Visual, Spatial and Temporal Quality in Video-Based Reconstruction of People: Achieving, Prototyping and Evaluating

Capturing, recreating and representing a high fidelity virtual representation of the dynamic human form has long been a target for a diverse range of applications including tele-presence, games, film and TV special effects. The complexity of the challenge, to achieve a lifelike, faithful and believable representation, is such that a wide range of techniques and […]
Aug, 7

DenseCut: Densely Connected CRFs for Realtime GrabCut

Figure-ground segmentation from bounding box input, provided either automatically or manually, has been extremely popular in the last decade and influenced various applications. A lot of research has focused on highquality segmentation, using complex formulations which often lead to slow techniques, and often hamper practical usage. In this paper we demonstrate a very fast segmentation […]
Aug, 7

Towards Distortion-Predictable Embedding of Neural Networks

Current research in Computer Vision has shown that Convolutional Neural Networks (CNN) give state-of-the-art performance in many classification tasks and Computer Vision problems. The embedding of CNN, which is the internal representation produced by the last layer, can indirectly learn topological and relational properties. Moreover, by using a suitable loss function, CNN models can learn […]
Aug, 7

Modern Platform for Parallel Algorithms Testing: Java on Intel Xeon Phi

Parallel algorithms are popular method of increasing system performance. Apart from showing their properties using asymptotic analysis, proof-of-concept implementation and practical experiments are often required. In order to speed up the development and provide simple and easily accessible testing environment that enables execution of reliable experiments, the paper proposes a platform with multi-core computational accelerator: […]
Aug, 7

Optimising Reconfigurable Systems for Real-time Applications

This thesis addresses the problem of designing real-time reconfigurable systems. Our first contribution of this thesis is to propose novel data structures and memory architectures for accelerating real-time proximity queries, with potential application to robotic surgery. We optimise performance while maintaining accuracy by several techniques including mixed precision, function transformation and streaming data flow. Significant […]
Aug, 7

Behavioral Spherical Harmonics for Long-Range Agents’ Interaction

We introduce behavioral spherical harmonic (BSH), a novel approach to efficiently and compactly represent the directional-dependent behavior of agent. BSH is based on spherical harmonics to project the directional information of a group of multiple agents to a vector of few coefficients; thus, BSH drastically reduces the complexity of the directional evaluation, as it requires […]
Aug, 7

A Survey Of Techniques for Architecting DRAM Caches

Recent trends of increasing core-count and memory/bandwidth-wall have led to major overhauls in chip architecture. In face of increasing cache capacity demands, researchers have now explored DRAM, which was conventionally considered synonymous to main memory, for designing large last level caches. Efficient integration of DRAM caches in mainstream computing systems, however, also presents several challenges […]
Aug, 6

Real-Time Pedestrian Detection With Deep Networks Cascades

We present a new real-time approach to object detection that exploits the efficiency of cascade classifiers with the accuracy of deep neural networks. Deep networks have been shown to excel at classification tasks, and their ability to operate on raw pixel input without the need to design special features is very appealing. However, deep nets […]
Aug, 6

Removing the Barrier for FPGA-Based OpenCL Data Center Servers

Data centers today are the backbone of the modern economy, from the server rooms that power small to midsize organizations to the enterprise data centers that support U.S. corporations and provide access to cloud computing services. According to the Natural Resources Defense Council, data centers are one of the largest and fastest-growing consumers of electricity […]
Aug, 6

Optimizing an OpenCL Application for Video Watermarking in FPGAs

Video streaming and downloading account for the majority of consumer Internet traffic and are a driving force behind cloud computing. The continually growing demand for this type of content is pushing video-processing applications out of specialized systems and into the data center. This shift in the deployment paradigm allows for the rapid scaling of computation […]
Aug, 5

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Computing platforms are now extremely complex providing an increasing number of CPUs and accelerators. This trend makes balancing computations between these heterogeneous resources performance critical. In this paper we tackle the task granularity problem and we propose aggregating several CPUs in order to execute larger parallel tasks and thus find a better equilibrium between the […]
Aug, 5

Semantic Pose using Deep Networks Trained on Synthetic RGB-D

In this work we address the problem of indoor scene understanding from RGB-D images. Specifically, we propose to find instances of common furniture classes, their spatial extent, and their pose with respect to generalized class models. To accomplish this, we use a deep, wide, multi-output convolutional neural network (CNN) that predicts class, pose, and location […]
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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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