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Future of 3d Graphics
zymano writes "Extremetech
has this nice article on the future of 3d graphics. The article also mentions that graphic card gpus can be used for non-traditional powerful processing like physics. A quote from the article, "GPU can be from 10 to 100 times faster than a Pentium 4 and Scientific computations such as linear algebra, Fast Fourier Transforms, and partial differential equations can benefit". My question - If these cards are getting so powerful at computations then why do we need a Intel/AMD processor at all? Just make a graphics card with more transistors and drop the traditional processor..."
My question - If these cards are getting so powerful at computations then why do we need a Intel/AMD processor at all? Just make a graphics card with more transistors and drop the traditional processor...
If you'd really like the answer to this question, try programming anything on the GPU and you'll understand. It's hell to do half this stuff. GPUs are highly specialized and make very specific tradeoffs in favor of graphics processing. Of course, some operations, specifically those that can be modeled using cellular automata, map well to this set of constraints. Others, such as ray-tracing can be shoe-horned in, but if you were to try to write a word processor on the GPU, it'd essentially be impossible. The GPU allows you to do massively parallel computations, but penalizes you heavilly for things such as loops of variable length or reading memory back from the card outside of the once-per-cycle frame update, and the price of interrupting computation is prohibitive. Clearing the graphics pipeline can take a long, long time.
Furthermore, while there have been a few papers published claiming the orders of magnitude increase in speed in these sorts of computations, none actually demonstrate this sort of speed-up. Everyone's speculating, but when it comes to it, results are lacking.
b.c
While optimized for graphics, GPUs can indeed be used as general-purpose processors. GPUs are effectively stream processors, a class of devices whose architecture and programming model make then particularly efficient for scientific calculation.
> It might take a real long time, but it is a general purpose processor and so can process anything
The same holds true for GPUs. Like CPUs, they are turing complete.
OpenGL and Direct3D are the two interfaces that graphics card vendors provide to get at the hardware; there is no lower-level way to get at it. However, these APIs now include ways of describing programs that run on the GPUs directly; you can write programs that run at the per-vertex or per-pixel level with either of those APIs.
These programs can be given to the GPU via specialized low-level assembly language that has been developed to expose the programmability of GPUs. (They are pretty clean, RISC-like instruction sets).
Alternatively, you can use a higher level programming language, like NVIDIA's Cg, or Microsoft's HLSL, to write programs to run on the GPU. These are somewhat C-like languages that then compile down to those GPU assembly instruction sets.