Posts Tagged ‘gpgpu’

[GPU Computing] Intel Prepares Its Arrival in OpenCL World

Radeon HD 5970: the Ultimate Password Cracking Hardware?

CUDA Programming: CuPP C++ Framework and ISC 2009 Tutorials (CUDA / OpenCL)

Geeks3D Higgledy-Piggledy News (2009.04.17)

DirectX11 Allows DirectX10 Hardware to Execute Compute Shader

Fastest GPGPU Hacking Tool: ElcomSoft Wireless Security Auditor

SIGGRAPH 2008 Asia: A Stack of PDF Available on GPGPU Programming

ATI Stream KernelAnalyzer to Optimize Stream Kernels on Radeon and FireStream

S3 Graphics S3FotoPro Quick Review

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NVIDIA GeForce Graphics Cards Used to Break WIFI Passwords

With graphics cards such the GeForce GTX 280 and parallel brute force based algorithms coded in CUDA (GPGPU techniques), WiFi’s WPA (RC4 based) and WPA2 (AES based) encryption systems are now crackable and the time to crack them compared to CPU based algorithms is reduced by a factor of 100 (or 10,000 %).

Update (2008-10-16)

• On a teste : l’acceleration GPU pour trouver une cle WPA WiFi @ PCINpact

CUDA: GPU Usage and Data Structure Design

Here is a thesis that discusses the usage of NVIDIA’s CUDA in two applications:
- Einstein@Home: a distributed computing software
- OpenSteer: a game-like application.

CUDA exposes the GPU processing power in the C programming language and can be integrated in existing applications with ease. But in order to exploit the power a GPU can deliver, one has to design the data structures in order to become optimized for CUDA.

Download the thesis here: GPU usage and data structure design (1371)

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AMD Stream SDK will support DirectX 11 and OpenCL

AMD/ATI plans to update the Stream Software Development Kit in order to offer a fast solution to produce GPU accelerated applications. Stream Software Development Kit will have an enhanced support for C/C++ and new APIs, including Microsoft’s DirectX 11 and OpenCL.

The Future – According to NVIDIA

NVIDIA is seeing as “the future of computing” – basically more GPGPU usage (i.e. the use of the graphics chip to process regular programs) and the co-existence of “competing” technologies like ray tracing and rasterization.

During the whole Editor’s Day nVidia repeated ad nauseum how marvelous GPGPU is, showing several examples of applications where performance increased monstrously by the use of this technique.

As for the rasterization vs. ray tracing battle, nVidia is seeing the co-existence of both technologies in the future, as ray tracing is in fact a better technology for some applications, but worse for others.

Read full article HERE.

NVIDIA has more than 70 million GPGPUs in the market

Nvidia unveiled some interesting data about its progress on CUDA and GPGPU-enabled processors. During the Nvidia Editor’s Day Spring 2008, the company’s CTO disclosed that more than 70 million CUDA-enabled graphics chips (beginning with the GeForce 8-series) have shipped to date. According to David Kirk, Nvidia sees 350.000 CUDA-enabled driver downloads every week, while more than 60.000 CUDA SDK downloads were reported.

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