What are the technological reasons whereby GPUs are cheaper than CPUs?


GPUs are inherently massively parallel - you take one logic block, repeat it thousands of times and it can now process more pixels. CPUs need to deal with less parallelizable instructions and that's harder. So on a FLOPs basis a GPU can be cheaper to produce than a CPU.

  • Why are we interested in FLOATING POINT operations, and not just regular ones (hence, why are FLOPS the standard we go by)? – Dark Templar Nov 22 '11 at 8:09
  • @Dark Templar We are interested because some applications are very specific to Floaing Point operations like 3d games and scientific apps. – Andrey Nov 22 '11 at 14:50

I guess that one of the reasons is that GPU can allow to be modern. In x86 we deal with a CISC architecture which then have been modified into RISC/CISC hybrid. Modern PC supports 3 modes of operation at the same time (16, 32 and 64 bits) and support such instructions like decimal addition (who needs it anyway). On the other hand GPU deals with relatively HL domain-specific 'language' (OpenGL/DirectX) - supported on CPU side (drivers). It means each generation can (and often do like the transition from r100/r200 to r300/r400 or r300/r400 to r600/r700 [I don't know where r500 is]) have much of its internals removed.

Now imagine that we can simply replace X86-64 (which is in fact upgraded 25-years old architecture) by something like Itanium without rewriting everything. Or something like ARM. Something which could be updated to modern requirements (no need for complex slow instructions as today no one needs them as no one is writing in assembly - possibly more conditional instructions to avoid jumping like on ARM etc.).

Also - the GPU deals with much less complex problems - or rather much more parallelised. It does not need to do such things as supporting 25-years old instructions that someone might have used them. It can just have them emulated on CPU/by few GPU instructions. It does not have to predict branches inputted in a weird way just because someone thought it would save space or something.

As a side note - last time I build a computer there were about 2:2:1:1 share between the processor, graphic card, motherboard, and rest.

  • Why is RISC better than CISC?? – Dark Templar Nov 22 '11 at 8:11
  • Dark Templar: CISC were directed more on the developing in assembly - single instruction could do a lot, you could operate directly on memory etc. It resulted in clearer and shorter code at the cost of more complex processor and longer cycles (which do more). On the other hand compilers produced code that made several simple instruction. Therefore it was deemed worth to have few instruction which executed faster rather then the larger amount which do more. It is more how we use processors that inherited in architecture (trade off between cycle length and how much instruction do). – Maciej Piechotka Nov 22 '11 at 17:58
  • Please note however it is not that simple - when you have 2 processors with the same ISA you may have 2 programs - A and B - and A performs faster on P1 and B faster on P2. When you have 2 different ISA then you have multiple ways of transforming program to assembly and hence the comparation is harder. – Maciej Piechotka Nov 22 '11 at 18:04

what do you mean cheaper? There are expensive GPUs, more expensive than certain CPU. how do you compare them?

  • Are there examples to support this claim? – Dark Templar Nov 22 '11 at 8:48
  • @Dark Templar examples of what? that there are GPUs that are more expensive than certain CPU? Is it really that doubtful? – Andrey Nov 22 '11 at 14:48

They are usually created with 90 nm process, while CPUs are produced with 45 nm transistors nowadays. In fact the gpu unit then requires more energy, but the one time end-user price might be lower - older the technology the cheaper it is (in relatively close time scope 3-4 years).


Specialism vs generalism

Which way around is up to you... each works in different ways for different processing types, different data, different access patterns etc


Compare CPU and GPU architectures (picture from Nvidia).

CPU and GPU comparison

A lot of ALUs (arithmetic-logic units) give you a lot of computational power (1000s of threads). Minimal control results in severe costs of branching and other operations that are not "mathematical" (and lowers the price tag in store). Cache is very small and managed mostly by the programmer (hardware does not have to predict what to store), so it's cheap. What is more, GPU has its own "RAM", therefore it can work more efficiently on for example 2GB of data (but still pays for it) than a processor which is limited by communication with external units.

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy