<?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>Geeks3D.com &#187; NVIDIA CUDA</title>
	<atom:link href="http://www.geeks3d.com/category/technologies/nvidia-cuda/feed/" rel="self" type="application/rss+xml" />
	<link>http://www.geeks3d.com</link>
	<description>3D Tech News and Pixel Hacking</description>
	<lastBuildDate>Tue, 18 Jun 2013 08:04:50 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=</generator>
		<item>
		<title>AudioSmoke: Sound-Responsive CUDA Based Particles</title>
		<link>http://www.geeks3d.com/20130510/audiosmoke-sound-responsive-cuda-based-particles/</link>
		<comments>http://www.geeks3d.com/20130510/audiosmoke-sound-responsive-cuda-based-particles/#comments</comments>
		<pubDate>Fri, 10 May 2013 13:54:36 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[Digital Art]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[audiosmoke]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[particule]]></category>
		<category><![CDATA[pixel hacking]]></category>
		<category><![CDATA[visual computing]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=8555</guid>
		<description><![CDATA[I already wrote about Visual Compute HERE and their CUDA experiments. Their latest experiment is done with AudioSmoke, a realtime 3D visual computing application written in C#. AudioSmoke aims to visualize particles under different force field conditions. NVIDIA CUDA is used for the parallel computation of the particle system. The particles react on sound input [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20130510/audiosmoke-sound-responsive-cuda-based-particles/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>CUDA-Z 0.7.181 for Windows, Linux and Mac OSX</title>
		<link>http://www.geeks3d.com/20130502/cuda-z-0-7-181-for-windows-linux-and-mac-osx/</link>
		<comments>http://www.geeks3d.com/20130502/cuda-z-0-7-181-for-windows-linux-and-mac-osx/#comments</comments>
		<pubDate>Thu, 02 May 2013 18:31:10 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[GPU Tools]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[cua-z]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[cudaz]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[Linux]]></category>
		<category><![CDATA[mac osx]]></category>
		<category><![CDATA[NVIDIA]]></category>
		<category><![CDATA[windows]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=8551</guid>
		<description><![CDATA[CUDA-Z is GPU tool like GPU-Z or GPU Caps Viewer that gives you information about your GPU(s). And as its name says it, CUDA-Z is focused on NVIDIA CUDA GPU computing API. NVIDIA CUDA being available under Windows, Linux and Mac OS X, CUDA-Z is also available under the three operating systems thanks to Qt. [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20130502/cuda-z-0-7-181-for-windows-linux-and-mac-osx/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>GPUVerify: Formal Analysis Tool for OpenCL and CUDA Kernels</title>
		<link>http://www.geeks3d.com/20130107/gpuverify-formal-analysis-tool-for-opencl-and-cuda-kernels/</link>
		<comments>http://www.geeks3d.com/20130107/gpuverify-formal-analysis-tool-for-opencl-and-cuda-kernels/#comments</comments>
		<pubDate>Mon, 07 Jan 2013 11:40:45 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[analysis]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[gpuverify]]></category>
		<category><![CDATA[kernel]]></category>
		<category><![CDATA[opencl]]></category>
		<category><![CDATA[Programming]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=8453</guid>
		<description><![CDATA[GPUVerify is a command line tool that allows formal analysis of GPU kernels written in OpenCL and CUDA. GPUVerify can detect intra-group data races (in OpenCL, it&#8217;s a race between work items in the same work group), inter-group data races (in OpenCL, it&#8217;s a race between work items in different work groups), barrier divergence (barrier [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20130107/gpuverify-formal-analysis-tool-for-opencl-and-cuda-kernels/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>GPU Computing with Python: PyOpenCL and PyCUDA Updated</title>
		<link>http://www.geeks3d.com/20110704/gpu-computing-with-python-pyopencl-and-pycuda-updated/</link>
		<comments>http://www.geeks3d.com/20110704/gpu-computing-with-python-pyopencl-and-pycuda-updated/#comments</comments>
		<pubDate>Mon, 04 Jul 2011 11:21:54 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenGL]]></category>
		<category><![CDATA[Python]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[opencl]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[pycuda]]></category>
		<category><![CDATA[pyopencl]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7945</guid>
		<description><![CDATA[PyOpenCL and PyCUDA, two wrappers for OpenCL and CUDA APIs, have been updated. These wrappers allow to call OpenCL and CUDA functions from a Python code. PyOpenCL: OpenCL + Python PyOpenCL download PyOpenCL hompage PyOpenCL documentation PyCUDA: CUDA + Python PyCUDA download PyCUDA hompage PyCUDA documentation PyOpenCL sample: import pyopencl as cl import numpy import [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20110704/gpu-computing-with-python-pyopencl-and-pycuda-updated/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Floating Point and IEEE 754 Compliance for NVIDIA GPUs</title>
		<link>http://www.geeks3d.com/20110609/floating-point-and-ieee-754-compliance-for-nvidia-gpus/</link>
		<comments>http://www.geeks3d.com/20110609/floating-point-and-ieee-754-compliance-for-nvidia-gpus/#comments</comments>
		<pubDate>Thu, 09 Jun 2011 09:33:17 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[compute capability]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[floating point]]></category>
		<category><![CDATA[FMA]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[ieee 754]]></category>
		<category><![CDATA[NVIDIA]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7905</guid>
		<description><![CDATA[Here a short but detailed whitepaper about floating point on NVIDIA GPUs. Understanding floating point accuracy and compliance (IEEE 754) is important for GPU computing developers. The paper is focused on CUDA but should help OpenCL developers as well. In this whitepaper, you will learn: How the IEEE 754 standard fits in with NVIDIA GPUs [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20110609/floating-point-and-ieee-754-compliance-for-nvidia-gpus/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>KGPU: When the GPU is used to Accelerate the Linux Kernel</title>
		<link>http://www.geeks3d.com/20110509/kgpu-when-the-gpu-is-used-to-accelerate-the-linux-kernel/</link>
		<comments>http://www.geeks3d.com/20110509/kgpu-when-the-gpu-is-used-to-accelerate-the-linux-kernel/#comments</comments>
		<pubDate>Mon, 09 May 2011 20:08:50 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[GPU]]></category>
		<category><![CDATA[Linux]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[gpu-os]]></category>
		<category><![CDATA[kernel]]></category>
		<category><![CDATA[kgpu]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7859</guid>
		<description><![CDATA[KGPU is a new project that aims at using the GPU as a co-processor for the Linux kernel. This is a new step in the use of the GPU. Many applications are already accelerated by the GPU thanks to real time shader languages or GPGPU APIs like CUDA / OpenCL. Even malwares take advantage of [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20110509/kgpu-when-the-gpu-is-used-to-accelerate-the-linux-kernel/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
		</item>
		<item>
		<title>The Secret of Lucasfilm’s Magic: NVIDIA’s GPUs</title>
		<link>http://www.geeks3d.com/20110408/the-secret-of-lucasfilm%e2%80%99s-magic-nvidia%e2%80%99s-gpus/</link>
		<comments>http://www.geeks3d.com/20110408/the-secret-of-lucasfilm%e2%80%99s-magic-nvidia%e2%80%99s-gpus/#comments</comments>
		<pubDate>Fri, 08 Apr 2011 13:07:18 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[SFX and Animation]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[ILM]]></category>
		<category><![CDATA[lucasfilm]]></category>
		<category><![CDATA[NVIDIA]]></category>
		<category><![CDATA[plume]]></category>
		<category><![CDATA[quadro]]></category>
		<category><![CDATA[quadroplex 2200]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7836</guid>
		<description><![CDATA[The secret weapon of ILM&#8217;s wizards effects: NVIDIA GPUs, especially the Quadro line. ILM developed several tools that take adavantage of Quadro GPUs and the last one is Plume, a tool used to simulate the movements of fluids. Computing routines of Plume are coded in CUDA. Plume allows ILM&#8217;s artists to work almost in real [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20110408/the-secret-of-lucasfilm%e2%80%99s-magic-nvidia%e2%80%99s-gpus/feed/</wfw:commentRss>
		<slash:comments>5</slash:comments>
		</item>
		<item>
		<title>[Tested] oclHashcat 0.2.4 GPU-based Cracker: OpenCL / CUDA Test</title>
		<link>http://www.geeks3d.com/20110121/tested-oclhashcat-0-2-4-gpu-based-cracker-opencl-cuda-test/</link>
		<comments>http://www.geeks3d.com/20110121/tested-oclhashcat-0-2-4-gpu-based-cracker-opencl-cuda-test/#comments</comments>
		<pubDate>Fri, 21 Jan 2011 12:21:21 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Test]]></category>
		<category><![CDATA[cracking]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[geforce]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[gtx 580]]></category>
		<category><![CDATA[hd 6970]]></category>
		<category><![CDATA[oclHashcat]]></category>
		<category><![CDATA[opencl]]></category>
		<category><![CDATA[password]]></category>
		<category><![CDATA[radeon]]></category>
		<category><![CDATA[test]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7655</guid>
		<description><![CDATA[1 &#8211; oclHashcat Overview A new version of oclHashcat is available. oclHashcat is the GPU accelerated version of Hashcat, a MD5 password cracker. oclHashcat is able to use up to 16 GPUs to achieve its job. oclHashcat is available in two versions: OpenCL (oclHashcat) and CUDA (cudaHashcat). It seems the OpenCL version is only limited [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20110121/tested-oclhashcat-0-2-4-gpu-based-cracker-opencl-cuda-test/feed/</wfw:commentRss>
		<slash:comments>21</slash:comments>
		</item>
		<item>
		<title>[GPU Computing] CUDA Experiment III: Video Mapping (2 Million Pixel)</title>
		<link>http://www.geeks3d.com/20101112/gpu-computing-cuda-experiment-iii-video-mapping-2-million-pixel/</link>
		<comments>http://www.geeks3d.com/20101112/gpu-computing-cuda-experiment-iii-video-mapping-2-million-pixel/#comments</comments>
		<pubDate>Fri, 12 Nov 2010 18:17:54 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[Digital Art]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[digital art]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[processing]]></category>
		<category><![CDATA[video]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7526</guid>
		<description><![CDATA[When GPU computing meets digital art. Really cool! This CUDA experiment maps a FULL-HD (1920&#215;1080 @ 30 frames per second, MPEG2 compression) video source into 3D space. Each frame is processed in real-time on the GPU using CUDA. Each pixel in a frame (2.073.600 pixels per frame) is scaled by its luminance value and given [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20101112/gpu-computing-cuda-experiment-iii-video-mapping-2-million-pixel/feed/</wfw:commentRss>
		<slash:comments>14</slash:comments>
		</item>
		<item>
		<title>Terrain Rendering Demo With Perlin Noise, SSAO and SSDM</title>
		<link>http://www.geeks3d.com/20100914/terrain-rendering-demo-with-perlin-noise-ssao-and-ssdm/</link>
		<comments>http://www.geeks3d.com/20100914/terrain-rendering-demo-with-perlin-noise-ssao-and-ssdm/#comments</comments>
		<pubDate>Tue, 14 Sep 2010 07:54:17 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenGL]]></category>
		<category><![CDATA[tech demo]]></category>
		<category><![CDATA[cg]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[demo]]></category>
		<category><![CDATA[opengl]]></category>
		<category><![CDATA[perlin noise]]></category>
		<category><![CDATA[ray casting]]></category>
		<category><![CDATA[rendering]]></category>
		<category><![CDATA[shader]]></category>
		<category><![CDATA[ssao]]></category>
		<category><![CDATA[ssdm]]></category>
		<category><![CDATA[terrain]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7343</guid>
		<description><![CDATA[Here is a CUDA / Cg / OpenGL demo for NVIDIA cards. It runs at 60 FPS on my GTX 480 (I guess the VSYNC is enabled on this demo). The demo is an experiment to combine terrain raycasting of perlin noise generated terrain with screen space ambient occlusions (SSAO) and screen space displacement mapping [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100914/terrain-rendering-demo-with-perlin-noise-ssao-and-ssdm/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>[GPU Computing] Particle Systems with OpenCL and CUDA</title>
		<link>http://www.geeks3d.com/20100830/gpu-computing-particle-systems-with-opencl-and-cuda/</link>
		<comments>http://www.geeks3d.com/20100830/gpu-computing-particle-systems-with-opencl-and-cuda/#comments</comments>
		<pubDate>Mon, 30 Aug 2010 09:33:50 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gl interop]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[opencl]]></category>
		<category><![CDATA[particle system]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7312</guid>
		<description><![CDATA[“OpenCL was very straightforward to get started with. I coded as I read the spec, and it worked almost immediately.” - John Carmack - So true. It&#8217;s a pity AMD doesn&#8217;t want to officialize the OpenCL support in Catalyst&#8230; 1 &#8211; Adventures in OpenCL Part 2: Particles with OpenGL Here is a article that takls [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100830/gpu-computing-particle-systems-with-opencl-and-cuda/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>GPU-Based Smoothed Particle Hydrodynamics With CUDA</title>
		<link>http://www.geeks3d.com/20100807/gpu-based-smoothed-particle-hydrodynamics-with-cuda/</link>
		<comments>http://www.geeks3d.com/20100807/gpu-based-smoothed-particle-hydrodynamics-with-cuda/#comments</comments>
		<pubDate>Sat, 07 Aug 2010 07:41:01 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[tech demo]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[fluid]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[HPC-lab]]></category>
		<category><![CDATA[physics]]></category>
		<category><![CDATA[simulation]]></category>
		<category><![CDATA[Smoothed Particle Hydrodynamics]]></category>
		<category><![CDATA[sph]]></category>
		<category><![CDATA[water]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7257</guid>
		<description><![CDATA[A video demonstrating my GPU-based Smoothed Particle Hydrodynamics (SPH) implementation using CUDA to achieve extremely high performance. The video shows the real-time performance of the implementation, more than 100 FPS (dt=0.002) is achieved on a NVIDIA Geforce GTX 470 (Fermi). In this scene a water-like fluid is simulated using a SPH model described by Mueller [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100807/gpu-based-smoothed-particle-hydrodynamics-with-cuda/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>[GPU Tool] GPU Caps Viewer 1.8.9 with OpenGL 4.1 and Better OpenCL Support</title>
		<link>http://www.geeks3d.com/20100729/gpu-tool-gpu-caps-viewer-1-8-9-with-opengl-4-1-and-better-opencl-support/</link>
		<comments>http://www.geeks3d.com/20100729/gpu-tool-gpu-caps-viewer-1-8-9-with-opengl-4-1-and-better-opencl-support/#comments</comments>
		<pubDate>Thu, 29 Jul 2010 09:51:02 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[GPU Caps Viewer]]></category>
		<category><![CDATA[GPU Tools]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[OpenGL]]></category>
		<category><![CDATA[api]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[gpu caps viewer]]></category>
		<category><![CDATA[graphics card]]></category>
		<category><![CDATA[information]]></category>
		<category><![CDATA[opencl]]></category>
		<category><![CDATA[opengl]]></category>
		<category><![CDATA[utility]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7237</guid>
		<description><![CDATA[Update GPU Caps Viewer 1.9.0 with OpenGL 4 tessellation demo is available HERE. A new update of GPU Caps Viewer is available. This new version adds the support of OpenGL 4.1 and improves the OpenCL support. You can download GPU Caps Viewer 1.8.9 here (Win32 installer): Webmasters: hotlinking is not allowed, please use the post [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100729/gpu-tool-gpu-caps-viewer-1-8-9-with-opengl-4-1-and-better-opencl-support/feed/</wfw:commentRss>
		<slash:comments>12</slash:comments>
		</item>
		<item>
		<title>[GPU Tool] GPU Caps Viewer 1.8.8 Available</title>
		<link>http://www.geeks3d.com/20100723/gpu-tool-gpu-caps-viewer-1-8-8-available/</link>
		<comments>http://www.geeks3d.com/20100723/gpu-tool-gpu-caps-viewer-1-8-8-available/#comments</comments>
		<pubDate>Fri, 23 Jul 2010 12:53:56 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[GPU Caps Viewer]]></category>
		<category><![CDATA[GPU Tools]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[OpenCL]]></category>
		<category><![CDATA[OpenGL]]></category>
		<category><![CDATA[api]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[gpu caps viewer]]></category>
		<category><![CDATA[gpu tool]]></category>
		<category><![CDATA[graphics card]]></category>
		<category><![CDATA[opencl]]></category>
		<category><![CDATA[opengl]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7228</guid>
		<description><![CDATA[Update (2010.07.29) GPU Caps Viewer 1.8.9 is available HERE. A new update of GPU Caps Viewer is ready. This new version is essentially a maintenance release with minor changes and bugfixes. You can download GPU Caps Viewer 1.8.8 here: Webmasters: hotlinking is not allowed, please use the post url as download link. I tested all [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100723/gpu-tool-gpu-caps-viewer-1-8-8-available/feed/</wfw:commentRss>
		<slash:comments>10</slash:comments>
		</item>
		<item>
		<title>CUDA Developers: Fermi Tuning Guide and CUDA Programming Guide Updated</title>
		<link>http://www.geeks3d.com/20100723/cuda-developers-fermi-tuning-guide-and-cuda-programming-guide-updated/</link>
		<comments>http://www.geeks3d.com/20100723/cuda-developers-fermi-tuning-guide-and-cuda-programming-guide-updated/#comments</comments>
		<pubDate>Fri, 23 Jul 2010 06:35:17 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[GPU Computing]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[fermi]]></category>
		<category><![CDATA[gpu computing]]></category>
		<category><![CDATA[guide]]></category>
		<category><![CDATA[tuning]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7225</guid>
		<description><![CDATA[NVIDIA has updated the Fermi tuning guide (version 1.2) and the CUDA C programming guide (version 3.1.1). The version 1.2 of the Fermi tuning guide adds this advice: For CUDA Driver API applications, the use of 32-bit device code within a 64-bit host application is no longer recommended, as support for this mixed-bitness mode will [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100723/cuda-developers-fermi-tuning-guide-and-cuda-programming-guide-updated/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>[GPU Computing] NVIDIA GPU Artificial Intelligence Technology Preview</title>
		<link>http://www.geeks3d.com/20100606/gpu-computing-nvidia-gpu-artificial-intelligence-technology-preview/</link>
		<comments>http://www.geeks3d.com/20100606/gpu-computing-nvidia-gpu-artificial-intelligence-technology-preview/#comments</comments>
		<pubDate>Sun, 06 Jun 2010 12:32:59 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[Game Development]]></category>
		<category><![CDATA[GPU Computing]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gai]]></category>
		<category><![CDATA[gpu ai]]></category>
		<category><![CDATA[NVIDIA]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7162</guid>
		<description><![CDATA[NVIDIA has released the version version 0.5.0 of the GPU accelerated artificial intelligence library called GAI or NVIDIA GPU AI. You can find more information and downloads HERE. This technology preview is a snapshot of some internal research we have been working on and talking about at various conferences for the past couple years. The [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100606/gpu-computing-nvidia-gpu-artificial-intelligence-technology-preview/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>(GPU Computing) NVIDIA CUDA Compute Capability Comparative Table</title>
		<link>http://www.geeks3d.com/20100606/gpu-computing-nvidia-cuda-compute-capability-comparative-table/</link>
		<comments>http://www.geeks3d.com/20100606/gpu-computing-nvidia-cuda-compute-capability-comparative-table/#comments</comments>
		<pubDate>Sun, 06 Jun 2010 12:25:06 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[GPU Caps Viewer]]></category>
		<category><![CDATA[GPU Computing]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[compute capability]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[geforce]]></category>
		<category><![CDATA[gpu caps viewer]]></category>
		<category><![CDATA[NVIDIA]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7161</guid>
		<description><![CDATA[Updated on June 9, 2011: GTX 500 and CUDA 4.0 compute capabilities features. The Compute Capability describes the features supported by a CUDA hardware. First CUDA capable hardware like the GeForce 8800 GTX have a compute capability (CC) of 1.0 and recent GeForce like the GTX 480 have a CC of 2.0. Knowing the CC [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100606/gpu-computing-nvidia-cuda-compute-capability-comparative-table/feed/</wfw:commentRss>
		<slash:comments>7</slash:comments>
		</item>
		<item>
		<title>Octane Render: CUDA Accelerated Photorealistic Renderer</title>
		<link>http://www.geeks3d.com/20100428/octane-render-cuda-accelerated-photorealistic-renderer/</link>
		<comments>http://www.geeks3d.com/20100428/octane-render-cuda-accelerated-photorealistic-renderer/#comments</comments>
		<pubDate>Wed, 28 Apr 2010 09:18:02 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[3D]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[SFX and Animation]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[octane render]]></category>
		<category><![CDATA[photorealistic rendering]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7091</guid>
		<description><![CDATA[Octane Render is a renderer that uses the power of GPU and multi-GPU to render photorealistic images. It&#8217;s based on CUDA so any GeForce 8 series or better can be used. But in practice, it&#8217;s better to have a high-end GPU (GTX 200 or GTX 400) to achieve fast results. Octane Render is the world&#8217;s [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100428/octane-render-cuda-accelerated-photorealistic-renderer/feed/</wfw:commentRss>
		<slash:comments>7</slash:comments>
		</item>
		<item>
		<title>OGRE 1.7.1 And CUDA Integration</title>
		<link>http://www.geeks3d.com/20100427/ogre-1-7-1-and-cuda-integration/</link>
		<comments>http://www.geeks3d.com/20100427/ogre-1-7-1-and-cuda-integration/#comments</comments>
		<pubDate>Tue, 27 Apr 2010 09:46:34 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[3D Engines]]></category>
		<category><![CDATA[Game Development]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[3d engine]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[direct3d]]></category>
		<category><![CDATA[game development]]></category>
		<category><![CDATA[ogre]]></category>
		<category><![CDATA[opengl]]></category>
		<category><![CDATA[sdk]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7087</guid>
		<description><![CDATA[A maintenance release of OGRE 1.7.x is available. You can download the SDK, sources and demos HERE. OGRE is one of the most popular 3D rendering engine and is available for Windows, Mac OS X and Linux. OGRE supports all modern rendering paths: OpenGL, Direct3D 9, Direct3D 10 and Direct3D 11. And for those who [...]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100427/ogre-1-7-1-and-cuda-integration/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>JX3Benchmark: Direct3D Benchmark with PhysX and CUDA</title>
		<link>http://www.geeks3d.com/20100423/jx3benchmark-direct3d-benchmark-with-physx-and-cuda/</link>
		<comments>http://www.geeks3d.com/20100423/jx3benchmark-direct3d-benchmark-with-physx-and-cuda/#comments</comments>
		<pubDate>Fri, 23 Apr 2010 14:58:26 +0000</pubDate>
		<dc:creator>JeGX</dc:creator>
				<category><![CDATA[Benchmarks]]></category>
		<category><![CDATA[NVIDIA CUDA]]></category>
		<category><![CDATA[NVIDIA PhysX]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[direct3d]]></category>
		<category><![CDATA[jx3benchmark]]></category>
		<category><![CDATA[physx]]></category>

		<guid isPermaLink="false">http://www.geeks3d.com/?p=7082</guid>
		<description><![CDATA[JianXia 3 (JX3Benchmark) is a PhysX / CUDA benchmark that uses Direct3D for the rendering. You can download this benchmark HERE And don&#8217;t panic, this benchmark respects your private life&#8230; On my GeForce GT 240, I got an average FPS of 15. Here is the score: And here are some screenshots: [via]]]></description>
		<wfw:commentRss>http://www.geeks3d.com/20100423/jx3benchmark-direct3d-benchmark-with-physx-and-cuda/feed/</wfw:commentRss>
		<slash:comments>4</slash:comments>
		</item>
	</channel>
</rss>
