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That's why Intel devotes large part of the CPU to the embedded GPU -- it doesn't have much else to do with it. I don't quite understand your point here, but if

That's why Intel devotes large part of the CPU to the embedded GPU -- it doesn't have much else to do with it. I don't quite understand your point here, but if you were intending to refute my point regarding GPU computing, I think you are not understanding the nature of the CPU to GPU shift. GPGPU computing is a way to increase effective computing power without advancements in semiconductor technology. GPUs have a fundamentally different architecture that allows them to get much more processing power from the same silicon. They work differently to CPUs (amortizing memory access latency across many hardware threads instead of trying to minimize it, sharing control flow across many cores to minimize that cost, and requiring manual control of memory locality) but on many domains including training neural networks, they are much more powerful. So GPUs are certainly not a diversion CPU makers get into when they can't make progress on CPUs.

coldtea 11y ago
>I think you are not understanding the nature of the CPU to GPU shift. I do. It's just not a general way to bypass the Moore law slowdown because there are domains that are inherently non parallelizable, and there GPUs don't do much. Besides, I'll already covered GPUs in a sense when I talked about the need to make software to work well in many cores. Part of the work for that translates to GPU computing too. But there's no general "shift" from CPU to GPU computing, as in "here's a new paradigm that will solve the Moore slowdown". It's, and will remain, more of a special purpose thing, for graphics, rendering, number crunching and yes, neural networks. >So GPUs are certainly not a diversion CPU makers get into when they can't make progress on CPUs. GPUs in general might not be, but for integrated CPUs and especially those from Intel, they are.

coldtea 11y ago

>I think you are not understanding the nature of the CPU to GPU shift. I do. It's just not a general way to bypass the Moore law slowdown because there are domains that are inherently non parallelizable, and there GPUs don't do much. Besides, I'll already covered GPUs in a sense when I talked about the need to make software to work well in many cores. Part of the work for that translates to GPU computing too. But there's no general "shift" from CPU to GPU computing, as in "here's a new paradigm that will solve the Moore slowdown". It's, and will remain, more of a special purpose thing, for graphics, rendering, number crunching and yes, neural networks. >So GPUs are certainly not a diversion CPU makers get into when they can't make progress on CPUs. GPUs in general might not be, but for integrated CPUs and especially those from Intel, they are.