Visual Object Recognition with PlayStation 3 and a NVIDIA 16-GPU Monster Supercomputer
Categories: GPU Computing, Graphics Cards, NVIDIA CUDA, Python Tags: 16 gpus monster, computer vision, cuda, face recognition, gpu, image processing, image recognition, mit, object recognition, pycuda, supercomputer
16 GPUs Supercomputer
PlayStation 3 cluster
Read more…
SIGGRAPH 2009: NVIDIA Presentations Available
Categories: Game Development, Programming Tags: 3d stereo, apex, cuda, image processing, NVIDIA, OptiX, presentation, Siggraph 2009
Read more…
NVPP: CUDA Programming With Ease
Categories: NVIDIA CUDA, Programming Tags: cuda, gpu, image processing, nvidia performance primitives, nvpp, Programming
Read more…
S3 Graphics S3FotoPro Quick Review
Categories: 3D, Test Tags: chrome 430 gt, gpgpu, image manipulation, image processing, review, S3 Graphics, S3FotoPro, software
|
|
S3FotoPro is a GPGPU (General Purpose GPU) acccelerated utility for image processing. S3FotoPro requires Windows XP SP2/3 or Vista SP1 and a Chrome-based S3 graphics card. Geeks3D has such a graphics card (a S3 Chrome 430 GT) so let’s play a little bit with this software. |
NVIDIA Quadro CX for Adobe Creative Suite 4 Hardware Acceleration
Categories: Graphics Cards Tags: adobe cs4, cuda, gpu, h.264, image processing, NVIDIA, quadro cx, video encoding
Read more…
SIGGRAPH 2008 Presentations: Programming with CUDA
Categories: NVIDIA CUDA, Programming Tags: cuda, image filtering, image processing, nvcuvid, NVIDIA, parallel computing, Programming, stream computing, video
NVIDIA has released two SIGGRAPH 2008 presentations about CUDA. The first one talks about image processing and video algorithms with CUDA and shows some CUDA applications such as image filtering (sobel filter with code sample). This presentation talks also about NVCUVID, the video extension for CUDA. NVCUVID is similar to DXVA API, but is platform OS independent.
The second presentation is more general about CUDA programming and shows how to create high performance code to run on the millions of CUDA-capable GPUs already in use.
Links:
GPU benchmark tool for image processing
Categories: Benchmarks Tags: cpu, glsl, gpu benchmark, image processing, intel opencv library, opengl, shader
Here is a small benchmark that try to compare several optimized Intel OpenCV library functions with their GPU analogs, written using OpenGL and GLSL shader language.
More information HERE.
Because I can’t resist, here is my score (Core 2 Duo 6600 default clocks, Radeon HD 3870 Catalyst8.5, WinXP 32-bit) with Resolution multiplier set to 4:
------------ CPU | GPU step1: 75.3 21.5 step2: 35.8 22.5 step3: 05.7 00.7 Total Time: 116.9 345.3
-source-
