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	<title>GPGPU &#187; Tag: Ray Tracing :: GPGPU.org</title>
	<atom:link href="http://gpgpu.org/tag/ray-tracing/feed" rel="self" type="application/rss+xml" />
	<link>http://gpgpu.org</link>
	<description>General-Purpose Computation on Graphics Hardware</description>
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	<language>en</language>
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		<title>Using GPUs to Accelerate Installed Antenna Performance Simulations</title>
		<link>http://gpgpu.org/2012/01/09/installed-antenna-performance-simulations</link>
		<comments>http://gpgpu.org/2012/01/09/installed-antenna-performance-simulations#comments</comments>
		<pubDate>Mon, 09 Jan 2012 09:48:46 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[CEM]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Ray Tracing]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4359</guid>
		<description><![CDATA[Abstract: Savant is a asymptotic ray-tracing CEM tool used to predict the performance of antennas installed on electrically large platforms, including far-field antenna patterns, near-field distributions, and antenna-to-antenna coupling. Savant is based on the shooting and bouncing rays (SBR) formulation. While asymptotic solvers like Savant have significantly smaller computational and memory requirements for electrically large [...]]]></description>
			<content:encoded><![CDATA[<p>Abstract:</p>
<blockquote><p>Savant is a asymptotic ray-tracing CEM tool used to predict the performance of antennas installed on electrically large platforms, including far-field antenna patterns, near-field distributions, and antenna-to-antenna coupling. Savant is based on the shooting and bouncing rays (SBR) formulation. While asymptotic solvers like Savant have significantly smaller computational and memory requirements for electrically large problems than full-wave techniques, the computation costs still increase significantly with frequency and simulation fidelity, and such solvers benefit greatly from parallelization techniques. Graphics processing units (GPUs) are throughput-oriented processing devices that are well suited for the mathematically intensive workloads found in CEM solvers. Current GPUs contain hundreds of processing units, leverage thousands of threads, and can execute over one trillion floating-point operations per second. A hybrid CPU and GPU parallelization approach has been developed for Savant, providing significant speedups compared to CPU-only implementations. Results from the execution of GPU-accelerated Savant on multiple case studies will be presented.</p></blockquote>
<p>(T. Courtney, J. E. Stone and R. Kipp, <em>“Using GPUs to Accelerate installed antenna performance simulations,”</em> Proc. Allerton Antenna Symposium, Sept. 2011, Monticello, IL. [<a title="direct link to PDF" href="http://www.delcross.com/publications/SavantGPU-Allerton2011.pdf" target="_blank">PDF</a>])</p>
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		<item>
		<title>Physically based lighting for volumetric data with Exposure Render</title>
		<link>http://gpgpu.org/2011/10/27/exposure-render</link>
		<comments>http://gpgpu.org/2011/10/27/exposure-render#comments</comments>
		<pubDate>Thu, 27 Oct 2011 08:52:35 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[Monte Carlo Simulation]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Open Source]]></category>
		<category><![CDATA[Ray Tracing]]></category>
		<category><![CDATA[Volume Rendering]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=4083</guid>
		<description><![CDATA[Exposure Render is a Direct Volume Rendering Application that applies progressive Monte Carlo raytracing, coupled with physically based light transport to heterogeneous volumetric data. Exposure Render enables the configuration of any number of arbitrarily shaped area lights, models a real-world camera, including its lens and aperture, and incorporates complex materials, whilst still maintaining interactive display [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://code.google.com/p/exposure-render/" target="_blank"><iframe src="http://www.youtube.com/embed/cZaPIEo6PPs" frameborder="0" align="right" width="200" height="165"></iframe>Exposure Render</a> is a Direct Volume Rendering Application that applies progressive Monte Carlo raytracing, coupled with physically based light transport to heterogeneous volumetric data. Exposure Render enables the configuration of any number of arbitrarily shaped area lights, models a real-world camera, including its lens and aperture, and incorporates complex materials, whilst still maintaining interactive display updates. It features both surface and volumetric scattering, and applies noise reduction to remove the unwanted startup noise associated with progressive Monte Carlo rendering. The complete implementation is available in source and binary forms under a permissive free software license.</p>
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		<title>CentiLeo: interactive out-of-core GPU/CUDA ray tracer</title>
		<link>http://gpgpu.org/2011/08/04/centileo-out-of-core-ray-tracer</link>
		<comments>http://gpgpu.org/2011/08/04/centileo-out-of-core-ray-tracer#comments</comments>
		<pubDate>Fri, 05 Aug 2011 02:11:41 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Business]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Out-of-core]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Ray Tracing]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=3806</guid>
		<description><![CDATA[Implementing flexible software solutions, such as rendering and ray tracing, is still challenging for GPU programs. The amount of available memory on modern GPUs is relatively small.  Scenes for feature film rendering and visualization have large geometric complexity and can easily contain millions of polygons and a large number of texture maps and other data [...]]]></description>
			<content:encoded><![CDATA[<p>Implementing flexible software solutions, such as rendering and ray tracing, is still challenging for GPU programs. The amount of available memory on modern GPUs is relatively small.  Scenes for feature film rendering and visualization have large geometric complexity and can easily contain millions of polygons and a large number of texture maps and other data attributes. <a href="http://www.centileo.com" target="_blank">CentiLeo</a> presents an interactive out-of-core ray tracing engine running on the single desktop GPU. The system is built around a virtual memory manager. A novel ray intersection algorithm built around an acceleration structure, cached on the GPU, loads needed data on-demand using page swapping. The ray tracing engine is used to implement a variety of rendering and light transport algorithms. The system is implemented using CUDA and runs on a single NVIDIA GTX 480.</p>
<p><span id="more-3806"></span>A <a href="http://www.centileo.com/news.html" target="_blank">demo video</a> presents an interactive path tracer rendering the massive 400-million-polygon Boeing 777. There will be a talk on SIGGRAPH 2011 about this work: &#8220;<a href="http://www.siggraph.org/s2011/content/out-core-gpu-ray-tracing-complex-scenes" target="_blank">Out-of-Core GPU Ray Tracing of Complex Scenes</a>&#8220;, by Kirill Garanzha, Simon Premoze, and Alexander Bely. Kirill also has <a href="http://research.nvidia.com/publication/simpler-and-faster-hlbvh-work-queues" target="_blank">a paper at High Performance Graphics</a> this weekend.</p>
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		<title>CUDA and OpenCL supported in Indigo Renderer 3.0 and Indigo RT</title>
		<link>http://gpgpu.org/2011/06/26/indigo-renderer</link>
		<comments>http://gpgpu.org/2011/06/26/indigo-renderer#comments</comments>
		<pubDate>Sun, 26 Jun 2011 23:17:28 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Business]]></category>
		<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Ray Tracing]]></category>
		<category><![CDATA[Rendering]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=3673</guid>
		<description><![CDATA[From a recent announcement: Glare Technologies is proud to announce the release of Indigo Renderer 3.0 and Indigo RT. We use a hybrid GPU acceleration approach, which typically results in a 2-3x speedup when paired with a sufficiently powerful CPU. Realtime scene changes are possible, also in conjunction with network rendering to further accelerate rendering [...]]]></description>
			<content:encoded><![CDATA[<p>From a recent announcement:</p>
<blockquote><p>Glare Technologies is proud to announce the release of Indigo Renderer 3.0 and Indigo RT. We use a hybrid GPU acceleration approach, which typically results in a 2-3x speedup when paired with a sufficiently powerful CPU. Realtime scene changes are possible, also in conjunction with network rendering to further accelerate rendering performance. A page outlining the other features and improvements of Indigo 3.0 and Indigo RT can be found at <a href="http://www.indigorenderer.com/indigo_rt" target="_blank">http://www.indigorenderer.com/indigo3</a> and <a href="http://www.indigorenderer.com/indigo_rt" target="_blank">http://www.indigorenderer.com/indigo_rt</a>.</p></blockquote>
<p>&nbsp;</p>
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		<title>PEER 1 Hosting: Large-Scale Hosted NVIDIA GPU Cloud</title>
		<link>http://gpgpu.org/2011/02/10/peer-1-hosting-large-scale-hosted-nvidia-gpu-cloud</link>
		<comments>http://gpgpu.org/2011/02/10/peer-1-hosting-large-scale-hosted-nvidia-gpu-cloud#comments</comments>
		<pubDate>Fri, 11 Feb 2011 03:48:32 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Developer Resources]]></category>
		<category><![CDATA[Press]]></category>
		<category><![CDATA[Cloud Computing]]></category>
		<category><![CDATA[NVIDIA]]></category>
		<category><![CDATA[Ray Tracing]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=3249</guid>
		<description><![CDATA[Press release (submitted to gpgpu.org very late&#8230;): LOS ANGELES,CA – July 26, 2010 – PEER 1 Hosting (TSX:PIX), a global online IT hosting provider, today announced the availability of the industry’s first large-scale, hosted graphics processing unit (GPU) Cloud at the 37th Annual Siggraph International Conference. The system runs the RealityServer® 3D web application service [...]]]></description>
			<content:encoded><![CDATA[<p>Press release (submitted to gpgpu.org very late&#8230;):</p>
<blockquote><p>LOS ANGELES,CA – July 26, 2010 – PEER 1 Hosting (TSX:PIX), a global online IT hosting provider, today announced the availability of the industry’s first large-scale, hosted graphics processing unit (GPU) Cloud at the 37th Annual Siggraph International Conference.</p>
<p>The system runs the RealityServer® 3D web application service platform, developed by mental images, a wholly owned subsidiary of NVIDIA. The RealityServer platform is a powerful combination of NVIDIA Tesla GPUs and 3D web services software. It delivers interactive and photorealistic applications over the web using the iray® renderer, which enables animators, product designers, architects and consumers to easily visualize 3D scenes with remarkable realism.<span id="more-3249"></span></p>
<p>With the use of massively parallel NVIDIA Tesla GPUs, PEER 1 Hosting can now offer customers flexible and reliable access to a system capable of delivering high computational performance across demanding applications. These include graphics rendering, complex quantitative processing, video compression, and large-model 3D web services for access by mobile clients.</p>
<p>Hosting he GPUs and software within the cloud simplifies customer implementation and provides an inexpensive entry point for new users. It also minimizes internal IT pressures so businesses can focus their talent on core business operations.</p>
<p>“With their commitment to best-in-breed technology and state-of-the-art data centers, PEER 1 Hosting has all the skills to deliver a service of this kind and make the power of the GPU more accessible than ever before,” says Sumit Gupta, product line manager of Tesla products at NVIDIA. “RealityServer running on PEER 1 Hosting’s GPU Cloud will enable software developers of other Web 2.0 websites to offer 3D web applications, making the consumer experience on the Internet even more interactive.”</p>
<p>NVIDIA’s Tesla S1070 and Tesla M2050 (Fermi architecture-based) hosted GPUs, as well as RealityServer are now available for purchase worldwide and will be hosted as a managed hosting offering at PEER 1 Hosting data centers in Toronto, Canada and London, UK. As part of the launch at the Siggraph International Conference, PEER 1 Hosting, mental images and NVIDIA are offering free trials and proof of concepts for new customers to see first-hand how well the GPU Cloud performs.</p>
<p>“We’re excited to support and deliver high performance hosted GPUs from NVIDIA to our customers,” says Robert Miggins, PEER 1 Hosting‘s Senior Vice President Business Development. “The combination of the high performing GPUs running on our robust SuperNetwork™, with the on demand flexibility of the cloud, is truly an industry first.&#8221;</p>
<p>About PEER 1 Hosting<br />
PEER 1 Hosting is one of the world’s leading IT hosting providers. The company is built on two obsessions: Ping &amp; People. Ping, represents its commitment to best-in-breed technology, founded on a high performance 10Gb SuperNetwork™ connected by 17 state-of-the-art data centres, 21 points-of-presence and 10 colocation facilities throughout North America and Europe. People, represents its commitment to delivering outstanding customer service to its more than 10,000 customers worldwide, backed by a 100 percent uptime guarantee and 24x7x365 FirstCall Support™. PEER 1 Hosting’s portfolio includes Managed Hosting, Dedicated Servers under the ServerBeach brand, Colocation and Cloud Services. Founded in 1999, the company is headquartered in Vancouver, Canada, with European operations headquartered in Southampton, UK. PEER 1 Hosting shares are traded on the TSX under the symbol PIX. For more information visit: www.peer1.com or www.peer1hosting.co.uk.</p>
<p>Forward Looking Statements:<br />
Statements in this release relating to matters that are not historical fact are forward-looking statements based on current expectations, forecasts and assumptions that involve risks and uncertainties that could cause actual outcomes and results to differ materially. Factors that could cause or contribute to such differences include, but are not limited to, general economic conditions, changes in technology, reliance on third party manufacturing, managing rapid growth, global sales risks, limited intellectual property protection and other risks and uncertainties described in PEER 1 Hosting’s public filings with securities regulatory authorities.</p>
<p>Media Contact:<br />
For North American inquiries please contact Katie Boland at MAVERICK PR, 416-640-5525 ext. 228, katieb@maverickpr.com<br />
For European media inquiries please contact Champion Communications +44 (0)207 268 3439 PEER1hosting@championcomms.com</p></blockquote>
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		<title>Conference Proceedings: HPG and SIGGRAPH 2009</title>
		<link>http://gpgpu.org/2009/08/23/hpg-siggraph-2009</link>
		<comments>http://gpgpu.org/2009/08/23/hpg-siggraph-2009#comments</comments>
		<pubDate>Mon, 24 Aug 2009 01:15:30 +0000</pubDate>
		<dc:creator>dom</dc:creator>
				<category><![CDATA[Events]]></category>
		<category><![CDATA[Research]]></category>
		<category><![CDATA[Conferences]]></category>
		<category><![CDATA[Graph Algorithms]]></category>
		<category><![CDATA[High-Performance Graphics]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Ray Tracing]]></category>
		<category><![CDATA[SIGGRAPH]]></category>
		<category><![CDATA[stream compaction]]></category>

		<guid isPermaLink="false">http://gpgpu.org/?p=1810</guid>
		<description><![CDATA[Ke-Sen Huang has assembled a web page with links to all papers presented at these two important conferences, High Performance Graphics (a synthesis of the Graphics Hardware and Interactive Ray Tracing conferences) and SIGGRAPH. Both conferences had quite a number of GPGPU-related publications.  Highlights from HPG include a paper on computing minimum spanning trees on [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://kesen.huang.googlepages.com/" target="_blank">Ke-Sen Huang</a> has assembled a web page with links to all papers presented at these two important conferences, <a href="http://highperformancegraphics.org/" target="_blank">High Performance Graphics</a> (a synthesis of the Graphics Hardware and Interactive Ray Tracing conferences) and <a href="http://www.siggraph.org/s2009/" target="_blank">SIGGRAPH</a>. Both conferences had quite a number of GPGPU-related publications.  Highlights from HPG include a paper on computing minimum spanning trees on the GPU, one on optimizing stream compaction on GPUs, and a study from NVIDIA on understanding the efficiency of GPUs and of wide-SIMD architectures in general on inherently imbalanced workloads like ray tracing (among others).</p>
<p>Click <a href="http://kesen.huang.googlepages.com/sig2009.html" target="_blank">here for SIGGRAPH papers</a>, and <a href="http://kesen.huang.googlepages.com/hpg2009Papers.htm" target="_blank">here for HPG papers</a>. <a href="http://kesen.huang.googlepages.com/" target="_blank">Ke-Sen&#8217;s pages</a> are also a good resource for other conferences in the field.</p>
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		<title>Hybrid Ray Tracing: Ray Tracing Using GPU-Accelerated Image-Space Methods</title>
		<link>http://gpgpu.org/2007/04/25/hybrid-ray-tracing-ray-tracing-using-gpu-accelerated-image-space-methods</link>
		<comments>http://gpgpu.org/2007/04/25/hybrid-ray-tracing-ray-tracing-using-gpu-accelerated-image-space-methods#comments</comments>
		<pubDate>Wed, 25 Apr 2007 11:52:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Computer Graphics]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Ray Tracing]]></category>
		<category><![CDATA[Rendering]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/AdvancedRendering/robertHybridRT07.html</guid>
		<description><![CDATA[This paper by Robert et al. at the University of Bern, Switzerland describes the object intersection buffer (OIB), a GPU-based visibility preprocessing algorithm for accelerating ray tracing. Based on this approach, a hybrid ray tracer is proposed to exploit parallel ray tracing using the GPU and CPU. (Hybrid Ray Tracing &#8211; Ray Tracing Using GPU-Accelerated [...]]]></description>
			<content:encoded><![CDATA[<p>This paper by <a href="http://www.iam.unibe.ch/~robert">Robert</a> et al. at the University of Bern, Switzerland describes the object intersection buffer (OIB), a GPU-based visibility preprocessing algorithm for accelerating ray tracing. Based on this approach, a hybrid ray tracer is proposed to exploit parallel ray tracing using the GPU and CPU. (<a href="http://www.iam.unibe.ch/~robert/doc/hybrid-rt-2007.pdf">Hybrid Ray Tracing &#8211; Ray Tracing Using GPU-Accelerated Image-Space Methods</a>. Philippe C.D. Robert, Severin Schoepke, and Hanspeter Bieri.<em> Proceedings of GRAPP 2007</em>.)</p>
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		<title>Call for Participation &#8211; IEEE Symposium on Interactive Ray Tracing</title>
		<link>http://gpgpu.org/2006/04/24/call-for-participation-ieee-symposium-on-interactive-ray-tracing</link>
		<comments>http://gpgpu.org/2006/04/24/call-for-participation-ieee-symposium-on-interactive-ray-tracing#comments</comments>
		<pubDate>Mon, 24 Apr 2006 14:29:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Events]]></category>
		<category><![CDATA[Conferences]]></category>
		<category><![CDATA[Ray Tracing]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/Conferences/RT06.html</guid>
		<description><![CDATA[To focus and facilitate research on real-time ray tracing, a new forum is being created for this rapidly developing field: the 2006 IEEE Symposium on Interactive Ray Tracing, sponsored by the IEEE Computer Society and the IEEE Visualization and Graphics Technical Committee (pending). The Call For Participation is now online and contributions on Ray Tracing [...]]]></description>
			<content:encoded><![CDATA[<p>To focus and facilitate research on real-time ray tracing, a new forum is being created for this rapidly developing field:  the 2006 IEEE Symposium on Interactive Ray Tracing, sponsored by the IEEE Computer Society and the IEEE Visualization and Graphics Technical Committee (pending). The <a href="http://www.sci.utah.edu/RT06" title="RT06 Call for Participation" target="_blank">Call For Participation is now online</a> and contributions on Ray Tracing on GPUs are invited.</p>
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		<title>Fast GPU Ray Tracing of Dynamic Meshes using Geometry Images</title>
		<link>http://gpgpu.org/2006/03/17/fast-gpu-ray-tracing-of-dynamic-meshes-using-geometry-images</link>
		<comments>http://gpgpu.org/2006/03/17/fast-gpu-ray-tracing-of-dynamic-meshes-using-geometry-images#comments</comments>
		<pubDate>Fri, 17 Mar 2006 19:15:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Data Structures]]></category>
		<category><![CDATA[Papers]]></category>
		<category><![CDATA[Ray Tracing]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/AdvancedRendering/GlobalIllumination/carrRTGeomImage2006.html</guid>
		<description><![CDATA[Using the GPU to accelerate ray tracing may seem like a natural choice due to the highly parallel nature of the problem. However, determining the most versatile GPU data structure for scene storage and traversal is a challenge. In this paper, we introduce a new method for quick intersection of triangular meshes on the GPU. [...]]]></description>
			<content:encoded><![CDATA[<p>Using the GPU to accelerate ray tracing may seem like a natural choice due to the highly parallel nature of the problem. However, determining the most versatile GPU data structure for scene storage and traversal is a challenge. In this paper, we introduce a new method for quick intersection of triangular meshes on the GPU. The method uses a threaded bounding volume hierarchy built from a geometry image, which can be efficiently traversed and constructed entirely on the GPU. This acceleration scheme is highly competitive with other GPU ray tracing methods, while allowing for both dynamic geometry and an efficient level of detail scheme at no extra cost. (<a href="http://graphics.cs.uiuc.edu/geomrt/" title="Fast GPU Ray Tracing of Dynamic Meshes using Geometry Images" target="_blank">Fast GPU Ray Tracing of Dynamic Meshes using Geometry Images</a> Nathan A. Carr, Jared Hoberock, Keenan Crane, and John C. Hart.  <em>To appear in Proceedings of Graphics Interface 2006</em>)</p>
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		<title>Ray Tracing News vol. 18 no. 1</title>
		<link>http://gpgpu.org/2005/12/13/ray-tracing-news-vol18-no1</link>
		<comments>http://gpgpu.org/2005/12/13/ray-tracing-news-vol18-no1#comments</comments>
		<pubDate>Tue, 13 Dec 2005 13:58:00 +0000</pubDate>
		<dc:creator>Mark Harris</dc:creator>
				<category><![CDATA[Research]]></category>
		<category><![CDATA[Ray Tracing]]></category>

		<guid isPermaLink="false">http://www.gpgpu.org/cgi-bin/blosxom.cgi/AdvancedRendering/RTNv18n1.html</guid>
		<description><![CDATA[Eric Haines has released the latest issue of his long-running &#8220;Ray Tracing News&#8221;. It&#8217;s chock full of news and interesting discussion about ray tracing implementation and optimization, kd-trees, and more. It also includes links to various ray-tracing work being done on GPUs. (Ray Tracing News volume 18, no. 1)]]></description>
			<content:encoded><![CDATA[<p>Eric Haines has released the latest issue of his long-running &#8220;Ray Tracing News&#8221;.  It&#8217;s chock full of news and interesting discussion about ray tracing implementation and optimization, kd-trees, and more.  It also includes links to various ray-tracing work being done on GPUs. (<a href="http://www.acm.org/tog/resources/RTNews/html/rtnv18n1.html" title="Ray Tracing News vol. 18 no. 1" target="_blank">Ray Tracing News volume 18, no. 1</a>)</p>
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