<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>GPGPU &#187; Tag: OpenCL :: GPGPU.org</title>
	<atom:link href="http://gpgpu.org/tag/opencl/feed" rel="self" type="application/rss+xml" />
	<link>http://gpgpu.org</link>
	<description>General-Purpose Computation on Graphics Hardware</description>
	<lastBuildDate>Tue, 22 May 2012 08:44:05 +0000</lastBuildDate>
	<language>en</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=3.3.2</generator>
		<item>
		<title>OpenCL SDK for new Intel Core Processors</title>
		<link>http://gpgpu.org/2012/04/27/opencl-sdk-for-new-intel-core-processors</link>
		<comments>http://gpgpu.org/2012/04/27/opencl-sdk-for-new-intel-core-processors#comments</comments>
		<pubDate>Fri, 27 Apr 2012 08:00:26 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Heterogeneneous Computing]]></category>
		<category><![CDATA[Intel]]></category>
		<category><![CDATA[OpenCL]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4664</guid>
		<description><![CDATA[The Intel® SDK for OpenCL Applications now supports the OpenCL 1.1 full-profile on 3rd generation Intel® Core™ processors with Intel® HD Graphics 4000/2500. For the first time, OpenCL developers using Intel® architecture can utilize compute resources across both Intel® Processor and Intel HD Graphics. More information: http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk]]></description>
			<content:encoded><![CDATA[<p>The Intel® SDK for OpenCL Applications now supports the OpenCL 1.1 full-profile on 3rd generation Intel® Core™ processors with Intel® HD Graphics 4000/2500. For the first time, OpenCL developers using Intel® architecture can utilize compute resources across both Intel® Processor and Intel HD Graphics. More information: <a title="OpenCL SDK @ Intel.com" href="http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk" target="_blank">http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk</a></p>
]]></content:encoded>
			<wfw:commentRss>http://gpgpu.org/2012/04/27/opencl-sdk-for-new-intel-core-processors/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>OpenCL Programming Webinar Series</title>
		<link>http://gpgpu.org/2012/03/30/opencl-programming-webinar-series-2</link>
		<comments>http://gpgpu.org/2012/03/30/opencl-programming-webinar-series-2#comments</comments>
		<pubDate>Fri, 30 Mar 2012 05:57:07 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[AMD]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Webinars]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4602</guid>
		<description><![CDATA[AMD offers an OpenCL Programming Webinar Series to help software developers become experts in the latest technologies, standards and best practices. The series of three OpenCL webinars will be presented by Rob Farber. 1. April 10th, 10AM PDT: Introducing Portable Parallelism C and C++ APIs OpenCL Memory Spaces The OpenCL Execution Model 2. April 24th, 10AM PDT: [...]]]></description>
			<content:encoded><![CDATA[<p>AMD offers an OpenCL Programming Webinar Series to help software developers become experts in the latest technologies, standards and best practices. The series of three OpenCL webinars will be presented by Rob Farber.</p>
<p>1. April 10th, 10AM PDT: Introducing Portable Parallelism</p>
<ul>
<li>C and C++ APIs</li>
<li>OpenCL Memory Spaces</li>
<li>The OpenCL Execution Model</li>
</ul>
<p>2. April 24th, 10AM PDT: Coordinating OpenCL Computations on one more Heterogeneous Devices</p>
<ul>
<li>How to Concisley Utilize Multiple Command Queues and Coordinate Tasks Across Multiple Heterogeneous Devices such as two GPU + CPU</li>
<li>Code Sample Discussion: Massively Parallel Random Number Test Framework</li>
</ul>
<p>3. May 1st, 10AM PDT: Accelerate Rendering by an Order of Magnitude with OpenCL, Plus a View to the Multi-core and Web-enabled Future</p>
<ul>
<li>How to use OpenCL to Provide High-Quality, Fast Rendering in Combination with Primitive Restart</li>
<li>Device Fission, Partitioning Hardware Capabilities for Optimal Resource Usage</li>
<li>Looking to the Future &#8211; WebCL</li>
</ul>
<p>Registration is limited. More Information: <a title="Link to AMD.com OpenCL" href="http://developer.amd.com/zones/OpenCLZone/Events/pages/OpenCLWebinars.aspx">http://developer.amd.com/zones/OpenCLZone/Events/pages/OpenCLWebinars.aspx</a></p>
]]></content:encoded>
			<wfw:commentRss>http://gpgpu.org/2012/03/30/opencl-programming-webinar-series-2/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Acceleware OpenCL™ Training in NYC</title>
		<link>http://gpgpu.org/2012/02/28/acceleware-opencl-training-nyc</link>
		<comments>http://gpgpu.org/2012/02/28/acceleware-opencl-training-nyc#comments</comments>
		<pubDate>Wed, 29 Feb 2012 01:56:31 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Business]]></category>
		<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[Acceleware]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Tutorials & Courses]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4529</guid>
		<description><![CDATA[Developed in partnership with AMD, this four day course is designed for GPU Programmers who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage the multi-core processing capabilities of the GPU. Delivered by Acceleware’s Developers, who provide real world experience and examples, the training comprises classroom lectures and hands-on tutorials. [...]]]></description>
			<content:encoded><![CDATA[<p>Developed in partnership with AMD, <a href="http://acceleware.com/mar27New-york" target="_blank">this four day course</a> is designed for GPU Programmers who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage the multi-core processing capabilities of the GPU.</p>
<p>Delivered by Acceleware’s Developers, who provide real world experience and examples, the training comprises classroom lectures and hands-on tutorials. Each student will be supplied with a laptop equipped with an AMD Fusion APU for the duration of the course. Small class sizes maximize learning and ensure a personal educational experience.<span id="more-4529"></span></p>
<p>Register before March 6 and receive $200 off your course fee! Enter promotional code AXTEB2012.</p>
]]></content:encoded>
			<wfw:commentRss>http://gpgpu.org/2012/02/28/acceleware-opencl-training-nyc/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Chai, a new managed platform for GPGPU</title>
		<link>http://gpgpu.org/2012/02/13/chai-a-new-managed-platform-for-gpgpu</link>
		<comments>http://gpgpu.org/2012/02/13/chai-a-new-managed-platform-for-gpgpu#comments</comments>
		<pubDate>Mon, 13 Feb 2012 05:12:54 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[Auto-Tuning]]></category>
		<category><![CDATA[Compilers]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[PeakStream]]></category>
		<category><![CDATA[Tools]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4486</guid>
		<description><![CDATA[Chai is a new managed platform for GPGPU. It is a free and open source clean room workalike of the PeakStream platform. While not production-ready, the just-released alpha version is able to compile and run non-trivial PeakStream demo code on AMD and NVIDIA GPUs (e.g. conjugate gradient). Chai combines an application virtual machine, garbage collection, [...]]]></description>
			<content:encoded><![CDATA[<p>Chai is a new managed platform for GPGPU. It is a free and open source clean room workalike of the PeakStream platform. While not production-ready, the <a href="https://github.com/cjang/chai" target="_blank">just-released alpha version</a> is able to compile and run non-trivial PeakStream demo code on AMD and NVIDIA GPUs (e.g. conjugate gradient).</p>
<p>Chai combines an application virtual machine, garbage collection, auto-tuning JIT compiler, and high level array programming language implemented as an embedded domain-specific language in C++. The JIT back-end uses expectation-maximization to auto-tune and generate vectorized OpenCL. The JIT includes auto-tuned model families for GEMM and GEMV. Although originally developed for AMD GPUs, these parameterized kernel families also generalize to NVIDIA GPUs.</p>
]]></content:encoded>
			<wfw:commentRss>http://gpgpu.org/2012/02/13/chai-a-new-managed-platform-for-gpgpu/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>OpenCL Studio 2.0 released</title>
		<link>http://gpgpu.org/2012/02/10/opencl-studio-2-0</link>
		<comments>http://gpgpu.org/2012/02/10/opencl-studio-2-0#comments</comments>
		<pubDate>Fri, 10 Feb 2012 07:33:23 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[IDEs]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[OpenGL]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4477</guid>
		<description><![CDATA[OpenCL Studio integrates OpenCL and OpenGL into a single development environment for high performance computing. The feature rich editor, interactive scripting language and extensible plug-in architecture support the rapid development of complex parallel algorithms and accompanying visualizations. Version 2.0 now conforms to the Lua plug-in architecture and closely integrates the open-source libCL parallel algorithm library. [...]]]></description>
			<content:encoded><![CDATA[<p>OpenCL Studio integrates OpenCL and OpenGL into a single development environment for high performance computing. The feature rich editor, interactive scripting language and extensible plug-in architecture support the rapid development of complex parallel algorithms and accompanying visualizations. Version 2.0 now conforms to the Lua plug-in architecture and closely integrates the open-source libCL parallel algorithm library. A complete version of OpenCL Studio is freely available for download at <a href="http://www.opencldev.com" target="_blank">www.opencldev.com</a>, including instructional videos and technology showcases.</p>
]]></content:encoded>
			<wfw:commentRss>http://gpgpu.org/2012/02/10/opencl-studio-2-0/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<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>
			<wfw:commentRss>http://gpgpu.org/2012/02/05/clogs-library/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<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>
			<wfw:commentRss>http://gpgpu.org/2012/02/01/lyapunov-exponent-fields/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</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>
			<wfw:commentRss>http://gpgpu.org/2012/01/16/clcc-v0-3-0/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<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>
]]></content:encoded>
			<wfw:commentRss>http://gpgpu.org/2012/01/02/viennacl-1-2-0-released/feed</wfw:commentRss>
		<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>
			<wfw:commentRss>http://gpgpu.org/2011/12/30/fortrancl/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
	</channel>
</rss>

