Most CPU&#x27;s these days already have a GPUs worth of core&#x27;s onboard. So, about 5 years ago to answer your question?<p>The other answer to the rest of your question is probably about when the majority of software starts running entirely on the GPU.<p>So, let&#x27;s take the Gefore GTX 980, a pretty heavyweight GPU right now. Tech specs say it has 2048 &quot;CUDA cores&quot; whatever that means. Well, a cuda processor is actually a SIMD core, and in this case, I think it&#x27;s actually a 32 element wide SIMD core. Which makes the 980 actually contain 64 cores (Is that actually the number of cores, or just instruction schedulers)... Which is still a bit, but you can get a modern 18-core Xeon, which only puts us off in about a factor of 4 in core count.<p>So, the main reason for the gap at this point is functionality. The CPU does a lot of things that the GPU doesn&#x27;t, and that all takes silicon that the GPU uses for extra ALU. Things like legacy instruction decode, instruction reordering, deep branch prediction pipelines, and a giant bucket of instructions that just aren&#x27;t needed on the GPU, but many modern CPU targeted software really relies on for performance. And really, if the average piece of software properly took advantage of many-cores, we&#x27;d all have a ton of cores in our CPU. It much easier for CPU designers to bolt on another core than dealing with complicated branch prediction invalidation logic, or any other trick to make crappy code run well.<p>In all I think the gap is smaller than you think, and we will continue to see convergence, particularly as engineers start writing code better suited to the GPU, and rely less on the CPUs fancy performance tricks. But in all, there are some fundamental differences that make complete crossover tricky.