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CPU Computing Using CUDA, Eclipse, and Java with JCuda - CodeProject

CPU Computing Using CUDA, Eclipse, and Java with JCuda - CodeProject | opencl, opengl, webcl, webgl | Scoop.it
Tutorial: GPU computing with JCuda and Nsight (Eclipse); Author: Max Bishop; Updated: 12 Sep 2013; Section: GPU Programming; Chapter: Platforms, Frameworks & Libraries; Updated: 12 Sep 2013
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Evaluating the Viability of Application-Driven Cooperative CPU/GPU Fault Detection

Trends in high performance computing are bringing increased heterogeneity among the computational resources within a single machine. The heterogeneous CPU/GPU platforms, however, exacerbate resilie...
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D5.5.3 - Design and implementation of the SIMD-MIMD GPU architecture

To develop a new SIMD-MIMD architecture we first characterized GPGPU workloads using simple and well known workload metrics to identify the performance bottlenecks. We found that the benchmarks wit...
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Efficient Implementation of RLS-Based Adaptive Filters on nVIDIA GeForce Graphics Processing Unit

This paper presents efficient implementation of RLS-based adaptive filters with a large number of taps on nVIDIA GeForce graphics processing unit (GPU) and CUDA software development environment. Mo...
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Detecting multiple periodicities in observational data with the multi-frequency periodogram. II. Frequency Decomposer, a parallelized time-series analysis algorithm

This is a parallelized algorithm performing a decomposition of a noisy time series into a number of frequency components. The algorithm analyses all suspicious periodicities that can be revealed, i...
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Towards a functional run-time for dense NLA domain

We investigate the use of functional programming to develop a numerical linear algebra run-time; i.e. a framework where the solvers can be adapted easily to different contexts and task parallelism ...
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Computing High Resolution Explicit Corridor Maps using Parallel Technologies

This work investigates the approximated construction of Explicit Corridor Maps (ECMs). An ECM is a type of Navigation Mesh: a geometrical structure describing the walkable space of an environment t...
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A Scalable, Efficient Scheme for Evaluation of Stencil Computations over Unstructured Meshes

Stencil computations are a common class of operations that appear in many computational scientific and engineering applications. Stencil computations often benefit from compile-time analysis, explo...
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Evolutionary Algorithm for Optimizing Parameters of GPGPU-based Image Segmentation

The use of digital microscopy allows diagnosis through automated quantitative and qualitative analysis of the digital images. Often to evaluate the samples, the first step is determining the number...
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A Feedback Approach to Task Partitioning in Heterogeneous Architectures

Personal Computers of today are based on complex architectures often with multiple high performance computational units for various dedicated purposes. The General Purpose GPU is one such example w...
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Imagination Technologies releases second generation tools for mobile GPU compute developers

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Fast network communities visualization on massively parallel GPU architecture

Modeling phenomena with networks has a wide application in many disciplines including biology, economics, sociology, and computer science. In network analysis modularity is an important measure for...
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Hardware-Oblivious Parallelism for In-Memory Column-Stores

The multi-core architectures of today's computer systems make parallelism a necessity for performance critical applications. Writing such applications in a generic, hardware-oblivious manner is a c...
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Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics

In this paper we implement histogram computations on a Graphics Processing Unit (GPU). Our Histogram computations is implemented using compute unified device architecture (CUDA) which is a minimal ...
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Samsung Exynos 5 Octa chips to gain Heterogeneous Multi-Processing

Samsung Exynos 5 Octa chips to gain Heterogeneous Multi-Processing | opencl, opengl, webcl, webgl | Scoop.it
Samsung has just made an announcement that might rock the ARM processor world: a Heterogeneous Multi-Processing (HMP) solution that will be applied to its Exynos 5 Octa core processors. This is pra...
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Comparison and Analysis of GPU Energy Effciency For CUDA and OpenCL

The use of GPUs for processing large sets of parallelizable data has increased sharply in recent years. As the concept of GPU computing is still relatively young, parameters other than computation ...
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Optimizing the MapReduce Framework on Intel Xeon Phi Coprocessor

With the ease-of-programming, flexibility and yet efficiency, MapReduce has become one of the most popular frameworks for building big-data applications. MapReduce was originally designed for distr...
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Implementation Details of GPU-based Out-of-Core Many-Lights Rendering

In this document, we provide implementation details of the GPUbased out-of-core many-lights rendering method. First, we introduce the organization of out-of-core data and the graph data used for da...
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Venceslas BIRI's curator insight, September 8, 2013 6:11 PM

Did not check this one...

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Accurate and Efficient Filtering using Anistropic Filter Decomposition

Efficient filtering remains an important challenge in computer graphics, particularly when filters are spatially-varying, have large extent, and/or exhibit complex anisotropic profiles. We present ...
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Bitcoin and The Age of Bespoke Silicon

Recently, the Bitcoin cryptocurrency has been an international sensation. This paper tells the story of Bitcoin hardware: how a group of early-adopters self-organized and financed the creation of a...
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Accelerating Text Mining Workloads in a MapReduce-based Distributed GPU Environment

Scientific computations have been using GPU-enabled computers successfully, often relying on distributed nodes to overcome the limitations of device memory. Only a handful of text mining applicatio...
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Real-Time GPU Path Tracing

In this paper, we present a simple, yet efficient implementation of the path tracing algorithm for GPUs. A reformulation of Russian Roulette is used to achieve high SIMT utilization, which leads to...
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Native code is dead: Cross Platform Development with Unity3D - CodeProject

Native code is dead: Cross Platform Development with Unity3D - CodeProject | opencl, opengl, webcl, webgl | Scoop.it
; Author: Software Developer's Journal; Updated: 29 Aug 2013; Section: Cross Platform; Chapter: Platforms, Frameworks & Libraries; Updated: 29 Aug 2013
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Efficient Sparse Matrix-Vector Multiplication on x86-Based Many-Core Processors

Sparse matrix-vector multiplication (SpMV) is an important kernel in many scientific applications and is known to be memory bandwidth limited. On modern processors with wide SIMD and large numbers ...
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