High-Performance Computing - GPGPU - CUDA - OpenCL - OpenMP - SSE-CPP-Compilers-Optimizations - Supercomputing -- Excellent Resources | Високопроизводителни изчисления, суперкомпютри, оптимизация на код на С++, графични процесори и др.

While browsing some SIMD SSE optimized image processing code and digging from some time, I reached to a few excellent free resources for boosting your software, I recommend those:

http://agner.org/optimize/
http://supercomputingblog.com/

Препоръчвам следните отлични матерали за оптимизация на код, многонишково/паралелно/матрично програмиране с CUDA, OpenCL, OpenMP, SIMD със SSE, суперкомпютри, оптимизация на код на С++ за различни процесорни архитектури.

Обработка на изображения, image processing, computer vision, компютърно зрение, manuals, tutorials, ръководства, help.

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Jürgen Schmidhuber Talk on Ted, Creative Machines and the Omega Point | Computer Vision, 3D-reconstruction from 2D

Juergen Schmidhuber - TEDxLausanne - When creative machines overtake man



Funny as usual. :)

One critics I've got on the computers who will reach human brain computing power - brain power calculations are unreliable and not really comparable, and ironically brain computing power is specialized and probably some of the operations are redundant or unnecessary., A computer having power to simulate a brain is much more flexible and powerful. I've discussed on these issues on the blog and the AGI list. (Should do the digest...)

Computer vision problems of 3D-reconstruction from images and image and video processing, done with GPUs give some suggestions on supposed required computing power in digital terms, but human brain puts a lot of "empty cycles" before reaching to such capabilities, even while having actuators which are usually lacking yet in machines - if the agent is capable to manipulate the position of the object, the "cameras" and the focus predictably and slowly, as babies can do with their eyes, heads and body, it's far easier to detect and scale perspective laws etc.

And it takes many months to get to 3D-vision and to increase resolution and develop 3D-reconstruction in the human brain. That adds ~86400 fold per day and 31,536,000 "cycles" per year.

What computing power is needed?

I don't think you need millions of the most powerful GPUs and CPUs at the moment to beat human vision, we'll beat it pretty soon, a lot of the higher level intelligence in my estimation is very low at its complexity (behavior, decision making, language at the grammar/vocabulary levels) and would need a tiny amount of MIPS, FLOPS and memory. It's the lowest levels which require vast computing power - 3D-reconstruction from 2D one or many static or motion camera sources, transformations, rotations, trajectories computations etc., and those problems are practically being solved and implemented.

See for example:

Marc Pollefeys - ZURICH.MINDS



My estimations supercomputers were fast enough since many years, it's just the algorithms which are lacking yet.


*Thanks to Sasho for the link to the Juergen's presentation!


Words, Tags: Computer vision, 3D-reconstruction, 3D-graphics, computational creativity, Juergen Schmidhuber, Jürgen, Talks, Artificial General Intelligence, AGI, Futurology, Brain, Analysis, GPU, GPGPU, CPUs, computing power, supercomputers, 3D-models

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