For a long time, single core performance has been the most important feature for gaming. Though we are getting better multi-threaded games, we are still pushing for the maximum single core performance instead of cores. Why can’t 16* 2ghz cores do roughly as good job as 8* 4ghz (of the same CPU architecture), especially in gaming?
They say that software programmers have to manually split the jobs for multiple cores. Why? Why does the OS even need to operate multiple cores in the first place? To me this sounds like bad workplace management, where the results depend on pushing the limits of the same few people (cores) instead of splitting the work. I feel like making just a big bunch of cheap cores would give better performance for the money than doing tons of research for the best possible elite cores. This works for encoding jobs but not for snappy game performance.
Now, one limitation that comes to mind is sequential jobs. Things where the steps need to be done in a certain order, depending on the results of the previous step. In this case, higher clock speed has an advantage and you wouldn’t even be able to utilize multiple cores. However, I still feel like the clock speeds like 4 000 000 000 cycles per second can’t be the limiting factor for running a game over 150 frames per second. Or is it? Are the CPU jobs in game programming just so sequential? Is there any way to increase the speed of simple sequential jobs with the help of more cores?
Bonus question: How do multiple instructions per cycle work if a job is sequential?
Bonus question 2: GPUs have tons of low power cores. Why is this okay? Is it just because the job of rendering is not sequential at all?
In: Engineering
Bonus Question 2: GPUs have the job of calculating an array of data to figure out what the screen needs to show. The math is relatively straightforward, and it can be done in parallel because the combination of each of those pixel calculations builds the image, so its best to split that pixel processing over as many cores as possible.
Cinebench runs are a good way of seeing this in practice, even though its a CPU benchmarking software. The benchmark splits the image processing task over as many threads as there is available. So with more cores, you can run more parts of the image simultaneously, and because the parts are independent of each other, you aren’t waiting for adjacent parts to process the next one. Consistently, higher core count CPUS have the best runs despite being slower, because they can process more at once.
GPUs work similarly, the CPU has told the GPU what to do based on all it’s calcs, so the GPUs job is to process the image. More cores makes this job faster.
Before anyone jumps in, yes the GPU is more complex, i dumbed it down significantly.
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