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Posts

Mar, 28

Parallel data mining on graphics processors

We introduce GPUMiner, a novel parallel data mining system that utilizes new-generation graphics processing units (GPUs). Our system relies on the massively multi-threaded SIMD (Single Instruction, Multiple-Data) architecture provided by GPUs. As specialpurpose co-processors, these processors are highly optimized for graphics rendering and rely on the CPU for data input/output as well as complex program […]
Mar, 27

Study on Transient Temperature Field Parallel Computing in Cooling Control Based on a GPU Fourier Method

With the evolution of graphics processing units (GPUs) in floating point operations and programmability, GPU has increasingly become powerful and cost-efficient computing architectures, its range of application has expanded tremendously, especially in the area of computational simulation. In this article, the Fourier method combined with GPU acceleration techniques is applied to simulate large-scale transient temperature […]
Mar, 27

Parallel frequent patterns mining algorithm on GPU

Extraction of frequent patterns from a transactional database is a fundamental task in data mining. Its applications include association rules, time series, etc. The Apriori approach is a commonly used generate-and-test approach to obtain frequent patterns from a database with a given threshold. Many parallel and distributed methods have been proposed for frequent pattern mining […]
Mar, 27

CaravelaMPI: Message Passing Interface for Parallel GPU-Based Applications

With the ever increasing demand for high quality 3D image processing on markets such as cinema and gaming, graphics processing units (GPUs) capabilities have shown tremendous advances. Although GPU-based cluster computing, which uses GPUs as the processing units, is one of the most promising high performance parallel computing platforms, currently there is no programming environment, […]
Mar, 27

A parallelization cost model for GPU

Using GPU for general computing has become an important research direction in high performance computing technology. However, this is not a lossless optimization method. Due to the impact of device initialization cost, data transmission delay, specific characteristics of programs, and other factors, the general computing on GPU may not always achieve the desired speedup, and […]
Mar, 27

Accelerate video decoding with generic GPU

Most modern computers or game consoles are equipped with powerful yet cost-effective graphics processing units (GPUs) to accelerate graphics operations. Though the graphics engines in these GPUs are specially designed for graphics operations, can we harness their computing power for more general nongraphics operations? The answer is positive. In this paper, we present our study […]
Mar, 27

Exploiting Parallelism in Iterative Irregular Maxflow Computations on GPU Accelerators

The Graphics Processing Unit (GPU) is an asymmetric, heterogeneous multi-core architecture that can be used for high performance parallel computing applications. However, a significant level of interest has been focused on algorithms for solving regular problems, as these applications typically map well to the GPU. Irregular applications, which rely on pointer or graph-based data structures, […]
Mar, 27

Image parallel processing based on GPU

In order to solve the compute-intensive character of image processing, based on advantages of GPU parallel operation, parallel acceleration processing technique is proposed for image. First, efficient architecture of GPU is introduced that improves computational efficiency, comparing with CPU. Then, Sobel edge detector and homomorphic filtering, two representative image processing algorithms, are embedded into GPU […]
Mar, 27

Data structure design for GPU based heterogeneous systems

This paper reports on our experience with data structure design for systems having both multiple CPU cores and a programmable graphics card. We integrate our data structures into the game-like application OpenSteerDemo and compare our data structures on two pc-systems. One System has a relative fast single core CPU and slower GPU, whereas the other […]
Mar, 27

HCW 2009 keynote talk: GPU computing: Heterogeneous computing for future systems

Over the last decade, commodity graphics processors (GPUs) have evolved from fixed-function graphics units into powerful, programmable data-parallel processors. Today’s GPU is capable of sustaining computation rates substantially greater than today’s modern CPUs, with technology trends indicating a widening gap in the future. Researchers in the rapidly evolving field of GPU computing have demonstrated mappings […]
Mar, 27

Scalable and Parallel Implementation of a Financial Application on a GPU: With Focus on Out-of-Core Case

The architecture of the latest Graphic Processing Unit (GPU) consists of a number of uniform programmable units integrated on the same chip, which facilitate the general-purpose computing beyond the graphic processing. With the multiple programmable units executing in parallel, the latest GPU shows superior performance for many non-graphic applications. Furthermore, programmers can have a direct […]
Mar, 25

Introduction to GPU Programming with GLSL

One of the challenging advents in computer science in recent years was the fast evolution of parallel processors, specially the GPU – graphics processing unit. GPUs today play a major role in many computational environments, most notably those regarding real-time graphics applications, such as games. The digital game industry is one of the main driving […]

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