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Posts

Dec, 25

Building Multiclass Nonlinear Classifiers with GPUs

The adoption of multiclass classification strategies that train independent binary classifiers becomes challenging when the goal is to retrieve nonlinear models from large datasets and the process requires several passes through the data. In such scenario, the combined use of a search and score algorithm and GPUs allows to obtain binary classifiers in a reduced […]
Dec, 25

Efficiency analysis of a physical problem: Different parallel computational approaches for a dynamical integrator evolution

A great challenge for scientists is to execute their computational applications efficiently. Nowadays, parallel programming has become a fundamental key to achieve this goal. High-performance computing provides a solution to exploit parallel architectures in order to get optimal performance. Both parallel programming model and the system architecture will maximize the benefits if both together are […]
Dec, 25

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

On the work sharing among GPUs and CPU cores on GPU equipped clusters, it is a critical issue to keep load balance among these heterogeneous computing resources. We have been developing a runtime system for this problem on PGAS language named XcalableMP-dev/StarPU [1]. Through the development, we found the necessity of adaptive load balancing for […]
Dec, 25

A Convex Relaxation Approach to Space Time Multi-view 3D Reconstruction

We propose a convex relaxation approach to space-time 3D reconstruction from multiple videos. Generalizing the works [16], [8] to the 4D setting, we cast the problem of reconstruction over time as a binary labeling problem in a 4D space. We propose a variational formulation which combines a photoconsistency based data term with a spatio-temporal total […]
Dec, 24

Graphics Processing Units in Acceleration of Bandwidth Selection for Kernel Density Estimation

The Probability Density Function (PDF) is a key concept in statistics. Constructing the most adequate PDF from the observed data is still an important and interesting scientific problem, especially for large datasets. PDFs are often estimated using nonparametric data-driven methods. One of the most popular nonparametric method is the Kernel Density Estimator (KDE). However, a […]
Dec, 24

Scene Boundary Detection Technique Based on Bottom-Up Attention System and OpenCL Parallel Implementation

This paper spotlights the maintaining of scene boundary detection system in video and process of porting it to the OpenCL. The scene boundary detection algorithm proposed by authors is based on bottom-up focus attention principle. The system builds Gaussian pyramids from input image, calculates map of saliency from the image and then detects the most […]
Dec, 24

Transparent Checkpoint-Restart for Hardware-Accelerated 3D Graphics

A mechanism for transparent GPU-independent checkpoint-restart of 3D graphics is described. The approach is based on a record-prune-replay paradigm: all OpenGL calls relevant to the graphics driver state are recorded; calls not relevant to the internal driver state as of the last graphics frame prior to checkpoint are discarded; and and the remaining calls are […]
Dec, 24

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

The ability to train large-scale neural networks has resulted in state-of-the-art performance in many areas of computer vision. These results have largely come from computational break throughs of two forms: model parallelism, e.g. GPU accelerated training, which has seen quick adoption in computer vision circles, and data parallelism, e.g. A-SGD, whose large scale has been […]
Dec, 24

Large-Scale Paralleled Sparse Principal Component Analysis

Principal component analysis (PCA) is a statistical technique commonly used in multivariate data analysis. However, PCA can be difficult to interpret and explain since the principal components (PCs) are linear combinations of the original variables. Sparse PCA (SPCA) aims to balance statistical fidelity and interpretability by approximating sparse PCs whose projections capture the maximal variance […]
Dec, 23

GPU Acceleration of Melody Accurate Matching in Query-by-Humming

With the increasing scale of the melody database,the query-by-humming system faces the tradeoffs between response speed and retrieval accuracy. Melody accurate matching is the key factor to restrict the response speed. In this paper, we present a GPU acceleration method of melody accurate matching, in order to improve the response speed without reducing retrieval accuracy. […]
Dec, 23

Enabling High Performance Computing in Cloud Infrastructure using Virtualized GPUs

With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their technical computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities clouds provide, as well as many novel computing paradigms available for data-intensive applications. However, there is […]
Dec, 23

Hardware Acceleration Technologies in Computer Algebra: Challenges and Impact

The objective of high performance computing (HPC) is to ensure that the computational power of hardware resources is well utilized to solve a problem. Various techniques are usually employed to achieve this goal. Improvement of algorithm to reduce the number of arithmetic operations, modifications in accessing data or rearrangement of data in order to reduce […]

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