[ivany]

Spot-on. I came to post this. A CPU core != a Xeon Phi core != a GPU "core". Memory architecture matters a LOT, and much of CPU area is devoted to cache and memory infrastructure. In a GPU, my understanding is every ~32 cores share a small cache and MMU, which makes some SIMD operations / algorithms more challenging to implement. Good for some algorithms, not so great for others.

I think the whole focus on "cores" misses lots of issues. Memory infrastructure is only one. Instruction-level parallelism (superscalar & out-of-order) execution is another - even single-core processors like ye olde Pentium can execute multiple instructions per cycle. It's very easy and tempting to look at the number of cores and use that as a rough estimate of system performance. But this approach will land you WAY off of real-world figures. It's akin to using the number of cylinders in a car's engine to determine how fast it is - sure, to the first order, cylinder count is correlated with engine output and hence car speed, but it's only a very rough correlation.

[lgeek]

I'm wondering why you say that a 'CPU core' is different from a Xeon Phi core. I've looked a bit into the Xeon Phi microarchitecture and I don't see any fundamental differences (well, I guess it depends on how you define 'fundamental') compared to other processors.

[Someone]

For a recent example, google discussions about the CPU in the iPhone 5. It has two cores but a hugely improved memory bus. That makes it comparable in speed to some four-core phones at the same clock speed.