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	<title>GPGPU &#187; Tag: OpenCL :: GPGPU.org</title>
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	<link>http://gpgpu.org</link>
	<description>General-Purpose Computation on Graphics Hardware</description>
	<lastBuildDate>Mon, 06 Feb 2012 04:59:24 +0000</lastBuildDate>
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		<title>New CLOGS library with sort and scan primitives for OpenCL</title>
		<link>http://gpgpu.org/2012/02/05/clogs-library</link>
		<comments>http://gpgpu.org/2012/02/05/clogs-library#comments</comments>
		<pubDate>Mon, 06 Feb 2012 04:59:24 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Libraries]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Performance Primitives]]></category>
		<category><![CDATA[Sorting]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4451</guid>
		<description><![CDATA[CLOGS is a library for higher-level operations on top of the OpenCL C++ API. It is designed to integrate with other OpenCL code, including synchronization using OpenCL events. Currently only two operations are supported: radix sorting and exclusive scan. Radix sort supports all the unsigned integral types as keys, and all the built-in scalar and [...]]]></description>
			<content:encoded><![CDATA[<p>CLOGS is a library for higher-level operations on top of the OpenCL C++ API. It is designed to integrate with other OpenCL code, including synchronization using OpenCL events. Currently only two operations are supported: radix sorting and exclusive scan. Radix sort supports all the unsigned integral types as keys, and all the built-in scalar and vector types suitable for storage in buffers as values. Scan supports all the integral types. It also supports vector types, which allows for limited multi-scan capabilities.</p>
<p>Version 1.0 of the library has just been released. The home page is <a title="CLOGS page on sourceforge" href="http://clogs.sourceforge.net/" target="_blank">http://clogs.sourceforge.net/</a></p>
]]></content:encoded>
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		<item>
		<title>GPU and APU computations of Finite Time Lyapunov Exponent fields</title>
		<link>http://gpgpu.org/2012/02/01/lyapunov-exponent-fields</link>
		<comments>http://gpgpu.org/2012/02/01/lyapunov-exponent-fields#comments</comments>
		<pubDate>Wed, 01 Feb 2012 07:00:09 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[APU]]></category>
		<category><![CDATA[Fluid Simulation]]></category>
		<category><![CDATA[OpenCL]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4433</guid>
		<description><![CDATA[We present GPU and APU accelerated computations of Finite-Time Lyapunov Exponent (FTLE) fields. The calculation of FTLEs is a computationally intensive process, as in order to obtain the sharp ridges associated with the Lagrangian Coherent Structures an extensive resampling of the flow field is required. The computational performance of this resampling is limited by the [...]]]></description>
			<content:encoded><![CDATA[<p>We present GPU and APU accelerated computations of Finite-Time Lyapunov Exponent (FTLE) fields. The calculation of FTLEs is a computationally intensive process, as in order to obtain the sharp ridges associated with the Lagrangian Coherent Structures an extensive resampling of the flow field is required. The computational performance of this resampling is limited by the memory bandwidth of the underlying computer architecture. The present technique harnesses data-parallel execution of many-core architectures and relies on fast and accurate evaluations of moment conserving functions for the mesh to particle interpolations. We demonstrate how the computation of FTLEs can be efficiently performed on a GPU and on an APU through OpenCL and we report over one order of magnitude improvements over multi-threaded executions in FTLE computations of bluff body flows. (Conti C., Rossinelli D., Koumoutsakos P., <em><a href="http://www.sciencedirect.com/science/article/pii/S0021999111006322">GPU and APU computations of Finite Time Lyapunov Exponent fields</a></em>, Journal of Computational Physics, 231(5):2229–2244, 2012.</p>
]]></content:encoded>
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		</item>
		<item>
		<title>CLCC v0.3.0 now available</title>
		<link>http://gpgpu.org/2012/01/16/clcc-v0-3-0</link>
		<comments>http://gpgpu.org/2012/01/16/clcc-v0-3-0#comments</comments>
		<pubDate>Mon, 16 Jan 2012 08:20:36 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Compilers]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenCL]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4393</guid>
		<description><![CDATA[CLCC, the light-weight and flexible utility for integrating OpenCL source builds into your project has just been updated to version 0.3.0. This version allows developers to save compiled binaries as object files for distribution with their programs and adds a series of options to select specific target platform/device combinations. Documentation and further information is available [...]]]></description>
			<content:encoded><![CDATA[<p>CLCC, the light-weight and flexible utility for integrating OpenCL source builds into your project has just been updated to version 0.3.0. This version allows developers to save compiled binaries as object files for distribution with their programs and adds a series of options to select specific target platform/device combinations. Documentation and further information is available at <a title="CLCC homepage" href="http://clcc.sourceforge.net/" target="_blank">http://clcc.sourceforge.net</a>.</p>
]]></content:encoded>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>ViennaCL 1.2.0 released</title>
		<link>http://gpgpu.org/2012/01/02/viennacl-1-2-0-released</link>
		<comments>http://gpgpu.org/2012/01/02/viennacl-1-2-0-released#comments</comments>
		<pubDate>Mon, 02 Jan 2012 09:51:24 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Libraries]]></category>
		<category><![CDATA[Linear Algebra]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Scientific Computing]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4325</guid>
		<description><![CDATA[Version 1.2.0 of the OpenCL-based C++ linear algebra library ViennaCL is now available for download! It features a high-level interface compatible with Boost.ublas, which allows for compact code and high productivity. Highlights of the new release are the following features (all experimental): Several algebraic multigrid preconditioners Sparse approximate inverse preconditioners Fast Fourier transform Structured dense [...]]]></description>
			<content:encoded><![CDATA[<p>Version 1.2.0 of the OpenCL-based C++ linear algebra library ViennaCL is now available for download! It features a high-level interface compatible with Boost.ublas, which allows for compact code and high productivity. Highlights of the new release are the following features (all experimental):</p>
<ul>
<li>Several algebraic multigrid preconditioners</li>
<li>Sparse approximate inverse preconditioners</li>
<li>Fast Fourier transform</li>
<li>Structured dense matrices (circulant, Hankel, Toeplitz, Vandermonde)</li>
<li>Reordering algorithms (Cuthill-McKee, Gibbs-Poole-Stockmeyer)</li>
<li>Proxies for manipulating subvectors and submatrices</li>
</ul>
<p>The features are expected to reach maturity in the 1.2.x branch. More information about the library including download links is available at <a title="ViennaCL on SourceForge" href="http://viennacl.sourceforge.net/" target="_blank">http://viennacl.sourceforge.net</a>.</p>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>FortranCL: An OpenCL interface for Fortran 90</title>
		<link>http://gpgpu.org/2011/12/30/fortrancl</link>
		<comments>http://gpgpu.org/2011/12/30/fortrancl#comments</comments>
		<pubDate>Fri, 30 Dec 2011 08:55:20 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Fortran]]></category>
		<category><![CDATA[Libraries]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Programming Languages]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4320</guid>
		<description><![CDATA[FortranCL is an interface to OpenCL from Fortran90 programs, and it is distributed under the LGPL free software license. It allows Fortran programmer to directly execute code on GPUs or other massively parallel processors. The interface is designed to be as close to the C OpenCL interface as possible, and it is written in native [...]]]></description>
			<content:encoded><![CDATA[<p>FortranCL is an interface to OpenCL from Fortran90 programs, and it is distributed under the LGPL free software license. It allows Fortran programmer to directly execute code on GPUs or other massively parallel processors. The interface is designed to be as close to the C OpenCL interface as possible, and it is written in native Fortran 90 with type checking. FortranCL is not complete yet, but it includes enough subroutines to write GPU accelerated code in Fortran. More information: <a title="link to googlecode" href="http://code.google.com/p/fortrancl/" target="_blank">http://code.google.com/p/fortrancl/</a></p>
]]></content:encoded>
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		</item>
		<item>
		<title>Introduction to Generic Accelerated Computing with Libra SDK</title>
		<link>http://gpgpu.org/2011/11/30/generic-accelerated-computing-libra-sdk</link>
		<comments>http://gpgpu.org/2011/11/30/generic-accelerated-computing-libra-sdk#comments</comments>
		<pubDate>Wed, 30 Nov 2011 07:35:49 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Business]]></category>
		<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[OpenGL]]></category>
		<category><![CDATA[Programming Environments]]></category>
		<category><![CDATA[Scientific Computing]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4230</guid>
		<description><![CDATA[Libra SDK is a sophisticated runtime including API, sample programs and documentation for massively accelerating software computations. This introduction tutorial provides an overview and usage examples of the powerful Libra API &#38; math libraries executing on x86/x64, OpenCL, OpenGL and CUDA technology. Libra API enables generic and portable CPU/GPU computing within software development without the [...]]]></description>
			<content:encoded><![CDATA[<p>Libra SDK is a sophisticated runtime including API, sample programs and documentation for massively accelerating software computations. This introduction tutorial provides an overview and usage examples of the powerful Libra API &amp; math libraries executing on x86/x64, OpenCL, OpenGL and CUDA technology. Libra API enables generic and portable CPU/GPU computing within software development without the need to create multiple, specific and optimized code paths to support x86, OpenCL, OpenGL or CUDA devices. Link to PDF: <a href="http://www.gpusystems.com/doc/LibraGenericComputing.pdf" target="_blank">www.gpusystems.com/doc/LibraGenericComputing.pdf</a></p>
]]></content:encoded>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>KOAP: Kentucky OpenCL Application Preprocessor</title>
		<link>http://gpgpu.org/2011/11/29/koap-kentucky-opencl-application-preprocessor</link>
		<comments>http://gpgpu.org/2011/11/29/koap-kentucky-opencl-application-preprocessor#comments</comments>
		<pubDate>Tue, 29 Nov 2011 09:07:15 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Programming Environments]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4222</guid>
		<description><![CDATA[KOAP, pronounced &#8220;cope,&#8221; is a tool for developing OpenCL applications. It&#8217;s purpose is to allow the programmer to aggregate and simplify calls to the OpenCL API. KOAP accepts as input a file containing (or including) both the OpenCL program and the host C program. KOAP understands several directives, each of which is prefixed with a [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://aggregate.org/KOAP/" target="_blank">KOAP</a>, pronounced &#8220;cope,&#8221; is a tool for developing OpenCL applications. It&#8217;s purpose is to allow the programmer to aggregate and simplify calls to the OpenCL API. KOAP accepts as input a file containing (or including) both the OpenCL program and the host C program. KOAP understands several directives, each of which is prefixed with a $ character. When KOAP is run, these directives are replaced with the requisite OpenCL API calls. Programs preprocessed by KOAP can run on any target supported by OpenCL, including both NVIDIA and AMD GPUs.</p>
<p>KOAP is now freely available as a source code tar file from <a href="http://aggregate.org/KOAP/" target="_blank">http://aggregate.org/KOAP/</a>.</p>
]]></content:encoded>
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		</item>
		<item>
		<title>OpenCL Compiler Tools</title>
		<link>http://gpgpu.org/2011/10/19/opencl-compiler-tools</link>
		<comments>http://gpgpu.org/2011/10/19/opencl-compiler-tools#comments</comments>
		<pubDate>Wed, 19 Oct 2011 07:46:29 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Tools]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4036</guid>
		<description><![CDATA[OCLTools is a powerful, yet compact, suite of Open Source tools that provide OpenCL developers with more alternatives to kernel compilation. OCLTools enables developers to eliminate costly kernel compilation time from the runtime of your application. With OCLTools developers can embed the source code of their kernels (clear text or encrypted) directly into their program [...]]]></description>
			<content:encoded><![CDATA[<p>OCLTools is a powerful, yet compact, suite of Open Source tools that provide OpenCL developers with more alternatives to kernel compilation. OCLTools enables developers to eliminate costly kernel compilation time from the runtime of your application. With OCLTools developers can embed the source code of their kernels (clear text or encrypted) directly into their program binaries, eliminating the need to distribute kernel source code in the open while still maintaining the flexibility of runtime compilation. Both source code and precompiled binaries can be embedded into OpenCL binaries, effectively eliminating the additional kernel compilation overhead from the run time of your application.</p>
<p>For more information go to <a href="http://www.clusterchimps.org" target="_blank">http://www.clusterchimps.org</a></p>
]]></content:encoded>
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		<item>
		<title>Aparapi &#8211; Parallel programming with Java and OpenCL</title>
		<link>http://gpgpu.org/2011/09/15/aparapi</link>
		<comments>http://gpgpu.org/2011/09/15/aparapi#comments</comments>
		<pubDate>Thu, 15 Sep 2011 06:07:39 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[AMD]]></category>
		<category><![CDATA[Java]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Tools]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=3966</guid>
		<description><![CDATA[AMD just released to open source a project called Aparapi that started in their JavaLabs team. Aparapi is an API for expressing data parallel workloads in Java and a runtime component capable of converting the Java bytecode of compatible workloads into OpenCL™ so that it can be executed on a variety of GPU devices.  More [...]]]></description>
			<content:encoded><![CDATA[<p>AMD just released to open source a project called Aparapi that started in their JavaLabs team. Aparapi is an API for expressing data parallel workloads in Java and a runtime component capable of converting the Java bytecode of compatible workloads into OpenCL™ so that it can be executed on a variety of GPU devices.  More information can be found in <a href=" http://blogs.amd.com/developer/2011/09/14/i-dont-always-write-gpu-code-in-java-but-when-i-do-i-like-to-use-aparapi/" target="_blank">this blog entry</a>.</p>
]]></content:encoded>
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		<item>
		<title>libCL 1.0 released</title>
		<link>http://gpgpu.org/2011/09/08/libcl-1-0</link>
		<comments>http://gpgpu.org/2011/09/08/libcl-1-0#comments</comments>
		<pubDate>Thu, 08 Sep 2011 13:06:48 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[OpenCL]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=3911</guid>
		<description><![CDATA[libCL is an open-source parallel algorithm library written in C++ and OpenCL. Rather than a specific domain, libCL intends to encompass a wide range of parallel algorithms and data structures. The goal is to provide a comprehensive repository for high performance visual-centric computing ranging from fundamental primitives such as sorting, searching and algebra to advanced [...]]]></description>
			<content:encoded><![CDATA[<p><a title="libCL homepage" href="http://libcl.org/" target="_blank">libCL</a> is an open-source parallel algorithm library written in C++ and OpenCL. Rather than a specific domain, libCL intends to encompass a wide range of parallel algorithms and data structures. The goal is to provide a comprehensive repository for high performance visual-centric computing ranging from fundamental primitives such as sorting, searching and algebra to advanced systems of algorithms for computational research and visualization. The current distribution of libCL already contains entirely parallelized implementations of the following algorithms:</p>
<ul>
<li>Bounding volume hierarchy construction</li>
<li>Smoothed particle hydrodynamics</li>
<li>Radix sort</li>
<li>Adaptive tone-mapping</li>
<li>Screen-space ambient occlusion culling</li>
<li>Bilateral and Recursive Gaussian</li>
</ul>
<p><a href="http://libcl.org/" target="_blank">libCL</a> emerged out of <a href="http://www.opencldev.com/" target="_blank">OpenCL Studio</a>, and as such integrates well with the development environment and its visualization capabilities. <a href="http://libcl.org/" target="_blank">libCL</a> is Open Source and released under the Apache license.</p>
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