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Scooped by Mikael Bourges-Sevenier
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Fast Subgraph Matching on Large Graphs using Graphics Processors

Fast Subgraph Matching on Large Graphs using Graphics Processors | opencl, opengl, webcl, webgl | Scoop.it
Subgraph matching is the task of finding all matches of a query graph in a large data graph, which is known as an NP-complete problem. Many algorithms are proposed to solve this problem using CPUs....
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Comparison of OpenCL performance on different platforms using VexCL and Blaze

Comparison of OpenCL performance on different platforms using VexCL and Blaze | opencl, opengl, webcl, webgl | Scoop.it
This technical report provides performance numbers for several benchmark problems running on several different hardware platforms. The goal of this report is twofold. First, it helps us better unde...
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Unlocking Bandwidth for GPUs in CC-NUMA Systems

Unlocking Bandwidth for GPUs in CC-NUMA Systems | opencl, opengl, webcl, webgl | Scoop.it
Historically, GPU-based HPC applications have had a substantial memory bandwidth advantage over CPU-based workloads due to using GDDR rather than DDR memory. However, past GPUs required a restricte...
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Persistent Mapped Buffers in OpenGL - CodeProject

Persistent Mapped Buffers in OpenGL - CodeProject | opencl, opengl, webcl, webgl | Scoop.it
Summary of techniques to stream data from CPU to GPU in OpenGL with focusing on new method called persistent mapped buffers.; Author: Bartlomiej Filipek; Updated: 3 Feb 2015; Section: OpenGL; Chapter: Multimedia; Updated: 3 Feb 2015...
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Exploiting Concurrency Patterns with Heterogeneous Task and Data Parallelism

Exploiting Concurrency Patterns with Heterogeneous Task and Data Parallelism | opencl, opengl, webcl, webgl | Scoop.it
Parallel programming of an application requires not only domain knowledge of the application, but also programming environment support and in-depth awareness of the target architecture. Often, all ...
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Locality-aware parallel block-sparse matrix-matrix multiplication using the Chunks and Tasks programming model

Locality-aware parallel block-sparse matrix-matrix multiplication using the Chunks and Tasks programming model | opencl, opengl, webcl, webgl | Scoop.it
We present a library for parallel block-sparse matrix-matrix multiplication on distributed memory clusters. The library is based on the Chunks and Tasks programming model [Parallel Comput. 40, 328 ...
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Characterizing and Enhancing Global Memory Data Coalescing on GPUs

Characterizing and Enhancing Global Memory Data Coalescing on GPUs | opencl, opengl, webcl, webgl | Scoop.it
Effective parallel programming for GPUs requires careful attention to several factors, including ensuring coalesced access of data from global memory. There is a need for tools that can provide fee...
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glNext: The Future of High Performance Graphics (Presented by Valve)

glNext: The Future of High Performance Graphics (Presented by Valve) | opencl, opengl, webcl, webgl | Scoop.it
Join us for the unveiling of Khronos' glNext initiative the upcoming cross-platform graphics API designed for modern programming techniques and processors....
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Performance Analysis and Optimization of a Distributed Processing Framework for Data Mining Accelerated with Graphics Processing Units

Performance Analysis and Optimization of a Distributed Processing Framework for Data Mining Accelerated with Graphics Processing Units | opencl, opengl, webcl, webgl | Scoop.it
In this age, a huge amount of data is generated every day by human interactions with services. Discovering the patterns of these data are very important to take business decisions. Due to the size ...
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In-Memory Data Analytics on Coupled CPU-GPU Architectures

In-Memory Data Analytics on Coupled CPU-GPU Architectures | opencl, opengl, webcl, webgl | Scoop.it
In the big data era, in-memory data analytics is an effective means of achieving high performance data processing and realizing the value of data in a timely manner. Efforts in this direction have ...
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Different Optimization Strategies and Performance Evaluation of Reduction on Multicore CUDA Architecture

Different Optimization Strategies and Performance Evaluation of Reduction on Multicore CUDA Architecture | opencl, opengl, webcl, webgl | Scoop.it
The objective of this paper is to use different optimization strategies on multicore GPU architecture. Here for performance evaluation we have used parallel reduction algorithm. GPU on-chip shared ...
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Speech Recognition on Modern Graphic Processing Units

Speech Recognition on Modern Graphic Processing Units | opencl, opengl, webcl, webgl | Scoop.it
Speech Recognition run on Graphic Processing Units (GPUs) has shown some promising performance improvements ranging 2-10x speedups when compare to execution on CPUs. GPU has continued to introduce ...
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Intel Posts OpenCL 2.0 QuickSort Tutorial (Compare to TE CUDA Version) - TechEnablement

Intel Posts OpenCL 2.0 QuickSort Tutorial (Compare to TE CUDA Version) - TechEnablement | opencl, opengl, webcl, webgl | Scoop.it
Intel Engineer Robert Ioffe has posted an OpenCL QuickSort tutorial that utilizes nested parallelism and Workgroup-scan functions. In particular, the tutorial shows how to use the OpenCL™ 2.0 enqueue_kernel functions that queue kernels from the device...
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Video: How to Build a Cheap Supercomputer

Video: How to Build a Cheap Supercomputer | opencl, opengl, webcl, webgl | Scoop.it
In this video, Rasim Muratovic shows you how to to build a cheap super computer using Raspberry Pi devices. In related news, the $35 Raspberry Pi 2 is out with a faster processor and twice the mem...
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Cryptography on Graphics Processing Unit: A Survey

Cryptography on Graphics Processing Unit: A Survey | opencl, opengl, webcl, webgl | Scoop.it
The profession of shelter advertisement by transfigure it into an unreadable arrange name decipher text, only those who possess a recondite keyboard can read the express into bewail text is Cryptog...
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Scaling Recurrent Neural Network Language Models

Scaling Recurrent Neural Network Language Models | opencl, opengl, webcl, webgl | Scoop.it
This paper investigates the scaling properties of Recurrent Neural Network Language Models (RNNLMs). We discuss how to train very large RNNs on GPUs and address the questions of how RNNLMs scale wi...
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Pointer Analysis for Semi-Automatic Code Parallelizers

Pointer Analysis for Semi-Automatic Code Parallelizers | opencl, opengl, webcl, webgl | Scoop.it
Code parallelizers are employed these days to reduce the efforts needed in manually parallelizing sequential code. But they are ineffective when it comes to handling programming constructs like poi...
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Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors

Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors | opencl, opengl, webcl, webgl | Scoop.it
Parallel stochastic simulations tend to exploit more and more computing power and they are now also developed for General Purpose Graphics Process Units (GP-GPUs). Consequently, they need reliable ...
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Multi-GPU Support on Shared Memory System using Directive-based Programming Model

Multi-GPU Support on Shared Memory System using Directive-based Programming Model | opencl, opengl, webcl, webgl | Scoop.it
Existing and emerging studies show that using single Graphics Processing Units (GPUs) can lead to obtaining significant performance gains. These devices have tremendous processing capabilities. We ...
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Mascar: Speeding up GPU Warps by Reducing Memory Pitstops

Mascar: Speeding up GPU Warps by Reducing Memory Pitstops | opencl, opengl, webcl, webgl | Scoop.it
With the prevalence of GPUs as throughput engines for data parallel workloads, the landscape of GPU computing is changing significantly. Non-graphics workloads with high memory intensity and irregu...
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Optimized Data Transfers Based on the OpenCL Event Management Mechanism

Optimized Data Transfers Based on the OpenCL Event Management Mechanism | opencl, opengl, webcl, webgl | Scoop.it
In standard OpenCL programming, hosts such as CPUs are supposed to control their compute devices such as GPUs. Since compute devices are dedicated to kernel computation, only hosts can execute seve...
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