Posts

Apr, 9

Task-based FMM for heterogeneous architectures

High performance FMM is crucial for the numerical simulation of many physical problems. In a previous study, we have shown that task-based FMM provides the flexibility required to process a wide spectrum of particle distributions efficiently on multicore architectures. In this paper, we now show how such an approach can be extended to fully exploit […]
Apr, 9

A two-level task scheduler on Multiple DSP system for OpenCL

This paper addresses the problem that multiple DSP system doesn’t support OpenCL programming. With the compiler, runtime and the kernel scheduler proposed, an OpenCL application becomes portable not only between multiple CPU and GPU, but also between embedded multiple DSP systems. Firstly, the LLVM compiler was imported for source-to-source translation in which the translated source […]
Apr, 9

Bayesian Sparse Unsupervised Learning for Probit Models of Binary Data

We present a unified approach to unsupervised Bayesian learning of factor models for binary data with binary and spike-and-slab latent factors. We introduce a non-negative constraint in the spike-and-slab prior that eliminates the usual sign ambiguity present in factor models and lowers the generalization error on the datasets tested here. For the generative models we […]
Apr, 9

Reducing the Disk IO Bandwidth Bottleneck through Fast Floating Point Compression using Accelerators

Compute-intensive tasks in high-end high performance computing (HPC) systems often generate large amounts of data, especially floating-point data, that need to be transmitted over the network. Although computation speeds are very high, the overall performance of these applications is affected by the data transfer overhead. Moreover, as data sets are growing in size rapidly, bandwidth […]
Apr, 9

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Scientific computation is the field of study that uses computers to implement mathematical models of physical phenomena such as FEM in deformation measurement in virtual reality. Scientific and engineering problems that would be almost impossible to solve by hand whereas on a computer, it can be handled properly. A numerical algorithm calculating for different fields […]
Apr, 9

Exploring the power of GPU’s for training Deep Belief Networks

One of the major research trends currently is the evolution of heterogeneous parallel computing. GP-GPU computing is being widely used and several applications have been designed to exploit the massive parallelism that GP-GPU’s have to offer. While GPU’s have always been widely used in areas of computer vision for image processing, little has been done […]
Apr, 7

A New Non-Blocking Approach on GPU Dynamical Memory Management

Dynamic memory allocation is a very important and basic technique implemented on modern computer architecture. In the massively parallel processor (MPP) architecture such as Graphics Processing Units (GPUs), many threads try to send allocation or deallocation requests to system in the same time, which could cause the issue of synchronization or race condition. In this […]
Apr, 7

A New Digital Repository for Hyperspectral Imagery with Unmixing-Based Retrieval Functionality Implemented on GPUs

Over the last few years, hyperspectral image data have been collected for a large number of locations over the world, using a variety of instruments for Earth observation. In addition, several new hyperspectral missions will become operational in the near future. Despite the increasing availability and large volume of hyperspectral data in many applications, there […]
Apr, 7

State of the Art Report on Real-time Rendering with Hardware Tessellation

For a long time, GPUs have primarily been optimized to render more and more triangles with increasingly flexible shading. However, scene data itself has typically been generated on the CPU and then uploaded to GPU memory. Therefore, widely used techniques that generate geometry at render time on demand for the rendering of smooth and displaced […]
Apr, 7

Detection of a faint fast-moving near-Earth asteroid using synthetic tracking technique

We report a detection of a faint near-Earth asteroid (NEA), which was done using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200-inch telescope. This asteroid, with apparent magnitude of 23, was moving at 5.97 degrees per day and was detected at a signal-to-noise ratio (SNR) of 15 using 30 sec of […]
Apr, 7

Quantifying the Energy Efficiency of Object Recognition and Optical Flow

In this report, we analyze the computational and performance aspects of current state-of-the-art object recognition and optical flow algorithms. First, we identify important algorithms for object recognition and optical flow, then we perform a pattern decomposition to identify key computations. We include profiles of the runtime and energy efficiency (GFLOPS/W) for our implementation of these […]
Apr, 7

GPU-Accelerated Face Detection Algorithm

This work is an overview of a preliminary experience in developing high-performance face detection accelerated by GPU co-processors. The objective is to illustrate the advantages and difficulties encountered while utilizing the GPU technology to perform face detection. Moreover the introduced implementation is a much faster than currently existing techniques. Previous techniques for speeding up face […]
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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 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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