GPUs have gone far beyond just SIMD these days. To effectively program a GPU, you need to program it like a GPU, not a CPU. In particular, while most people are

GPUs have gone far beyond just SIMD these days. To effectively program a GPU, you need to program it like a GPU, not a CPU. In particular, while most people are aware that GPUs don't like branching at a high level, branching can actually be fine as long as each block (small group of processors in the GPU) take the same branch. Block 1 taking the branch while block 2 not taking the branch will have little impact on performance. Additionally, the memory hierarchy is completely different for GPUs with blocks sharing cache and a huge number of registers per core while having very little memory for a typical stack. Sure, treating a GPU as a SIMD blackbox may work for many problems as a suitable abstraction, but in doing so you also overlook many of its capabilities. x86-64 can emulate many of the SIMD aspects without too much trouble, but the aspects like huge number of processors with many registers is not something that is able to be reproduced without a large number of tradeoffs. The only way that I see it as being possible to have a true CPU/GPU hybrid that is effective would be to basically have two separate chips for the GPU and the CPU, maybe multiple chips. I think the reason why such a product has not really taken off is because at that point there really isn't a point over using it versus a separate GPU and CPU. Maybe if hardware designers figured out how to greatly improve CPU to GPU communication in such a setup over having the motherboard in-between it might be worth it. CPU to GPU communication is a bottleneck for many applications.