1653

Posts

Nov, 19

Rodinia: A benchmark suite for heterogeneous computing

This paper presents and characterizes Rodinia, a benchmark suite for heterogeneous computing. To help architects study emerging platforms such as GPUs (Graphics Processing Units), Rodinia includes applications and kernels which target multi-core CPU and GPU platforms. The choice of applications is inspired by Berkeley’s dwarf taxonomy. Our characterization shows that the Rodinia benchmarks cover a […]
Nov, 19

Ultra-fast FFT protein docking on graphics processors

MOTIVATION: Modelling proteinaprotein interactions (PPIs) is an increasingly important aspect of structural bioinformatics. However, predicting PPIs using in silico docking techniques is computationally very expensive. Developing very fast protein docking tools will be useful for studying large-scale PPI networks, and could contribute to the rational design of new drugs. RESULTS: The Hex spherical polar Fourier […]
Nov, 19

Optimizing and tuning the fast multipole method for state-of-the-art multicore architectures

This work presents the first extensive study of single-node performance optimization, tuning, and analysis of the fast multipole method (FMM) on modern multi-core systems. We consider single- and double-precision with numerous performance enhancements, including low-level tuning, numerical approximation, data structure transformations, OpenMP parallelization, and algorithmic tuning. Among our numerous findings, we show that optimization and […]
Nov, 19

Design and Performance Evaluation of Image Processing Algorithms on GPUs

In this paper, we construe key factors in design and evaluation of image processing algorithms on the massive parallel GPU (graphics processing units) using the CUDA (compute unified device architecture) programming model. A set of metrics, customized for image processing, are proposed to quantitatively evaluate algorithm characteristics. In addition, we show that a range of […]
Nov, 19

Multi-dimensional characterization of temporal data mining on graphics processors

Through the algorithmic design patterns of data parallelism and task parallelism, the graphics processing unit (GPU) offers the potential to vastly accelerate discovery and innovation across a multitude of disciplines. For example, the exponential growth in data volume now presents an obstacle for high-throughput data mining in fields such as neuroscience and bioinformatics. As such, […]
Nov, 19

A two-level real-time vision machine combining coarse- and fine-grained parallelism

In this paper, we describe a real-time vision machine having a stereo camera as input generating visual information on two different levels of abstraction. The system provides visual low-level and mid-level information in terms of dense stereo and optical flow, egomotion, indicating areas with independently moving objects as well as a condensed geometric description of […]
Nov, 18

From Rendering to Tracking Point-based 3D Models

This paper adds to the abundant visual tracking literature with two main contributions. First we illustrate the interest of using Graphic Processing Units (GPU) to support efficient implementations of computer vision algorithms and, secondly, we introduce the use of point-based 3D models as a shape prior for real-time 3D tracking with a monocular camera. The […]
Nov, 18

Acceleration of the Smith-Waterman Algorithm using Single and Multiple Graphics Processors

Finding regions of similarity between two very long data streams is a computationally intensive problem referred to as sequence alignment. Alignment algorithms must allow for imperfect sequence matching with different starting locations and some gaps and errors between the two data sequences. Perhaps the most well known application of sequence matching is the testing of […]
Nov, 18

Parallel implementation of Artificial Neural Network training for speech recognition

In this paper we describe the implementation of a complete ANN training procedure using the block mode back-propagation learning algorithm for sequential patterns – such as the observation feature vectors of a speech recognition system – exploiting the high performance SIMD architecture of GPU using CUDA and its C-like language interface. We also compare the […]
Nov, 18

Modeling the propagation of elastic waves using spectral elements on a cluster of 192 GPUs

We implement a high-order finite-element application, which performs the numerical simulation of seismic wave propagation resulting for instance from earthquakes at the scale of a continent or from active seismic acquisition experiments in the oil industry, on a large GPU-enhanced cluster. Mesh coloring enables an efficient accumulation of degrees of freedom in the assembly process […]
Nov, 18

Accelerating POCS interpolation of 3D irregular seismic data with Graphics Processing Units

Seismic trace interpolation is necessary for high-resolution imaging when the acquired data are not adequate or when some traces are missing. Projection-onto-convex-sets (POCS) interpolation can gradually recover missing traces with an iterative algorithm, but its computational cost in a 3D CPU-based implementation is too high for practical applications. We present a computing scheme to speed […]
Nov, 18

Fast evaluation of Helmholtz potential on graphics processing units (GPUs)

This paper presents a parallel algorithm implemented on graphics processing units (GPUs) for rapidly evaluating spatial convolutions between the Helmholtz potential and a large-scale source distribution. The algorithm implements a non-uniform grid interpolation method (NGIM), which uses amplitude and phase compensation and spatial interpolation from a sparse grid to compute the field outside a source […]

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