"In fact what you call a "core" when you're talking about CPUs is composed of multiple such general purpose programmable, as well as less general purpose memory load/store units"
So are GPU cores.
"But saying that the NVidia GPU has 1526 "cores" is just dishonest."
No, it isn't. You can run 1536 things in parallel at speeds that would have qualified as full cpu speeds several years prior.
Something isn't any less a core merely because it does less juggling magic, and that juggling magic is actually undesirable for a heavily parallelized task.
"So there are some tasks where the Intel core will be much faster than the NVidia SM, and some tasks where the NVidia SM will be much faster."
This conversation already has a context. Arguments which ignore that context completely miss the point.
If you don't understand how I achieved the amount of processing I did, that's fine. Playing games with the semantics of a "core" somehow magically requiring all the features of current Intel-strategy chips, though, are not going to convince me.
There is more to Heaven and Earth, Horatio, than is dreamt of in Intel's philosophy. This sort of attitude towards what constitutes the no true scotsman "a real core" is why Arm is in the process of eating Intel alive, and why Tilera stands a decent chance of doing the same thing to ARM.
This is merely extreme RISC. I realize it's sort of a tradition for the modern VLIW movement to suggest that if you can't double-backflip through a flaming hoop made out of predictive NAND gates it somehow doesn't count.
But, if you actually look, the rate of modern supercomputing going to video cards is rising dramatically.
So obviously they count as cores to somebody.
You also seem to have missed the point. It's not the core scale that we're discussing here. It's the dataset scale. The number of cores you throw at a problem is not terribly important; 20 years ago it would have been breathtaking to throw 32 cores at a problem, and now that's two CPUs.
What makes an experiment cutting edge is the nature of the experiment, not the volume of hardware that you throw at it. I was talking about the /data/ and the /problem/ . Predicting movie ratings is a hell of a lot harder than feature detection.
So are GPU cores.
"But saying that the NVidia GPU has 1526 "cores" is just dishonest."
No, it isn't. You can run 1536 things in parallel at speeds that would have qualified as full cpu speeds several years prior.
Something isn't any less a core merely because it does less juggling magic, and that juggling magic is actually undesirable for a heavily parallelized task.
"So there are some tasks where the Intel core will be much faster than the NVidia SM, and some tasks where the NVidia SM will be much faster."
This conversation already has a context. Arguments which ignore that context completely miss the point.
If you don't understand how I achieved the amount of processing I did, that's fine. Playing games with the semantics of a "core" somehow magically requiring all the features of current Intel-strategy chips, though, are not going to convince me.
There is more to Heaven and Earth, Horatio, than is dreamt of in Intel's philosophy. This sort of attitude towards what constitutes the no true scotsman "a real core" is why Arm is in the process of eating Intel alive, and why Tilera stands a decent chance of doing the same thing to ARM.
This is merely extreme RISC. I realize it's sort of a tradition for the modern VLIW movement to suggest that if you can't double-backflip through a flaming hoop made out of predictive NAND gates it somehow doesn't count.
But, if you actually look, the rate of modern supercomputing going to video cards is rising dramatically.
So obviously they count as cores to somebody.
You also seem to have missed the point. It's not the core scale that we're discussing here. It's the dataset scale. The number of cores you throw at a problem is not terribly important; 20 years ago it would have been breathtaking to throw 32 cores at a problem, and now that's two CPUs.
What makes an experiment cutting edge is the nature of the experiment, not the volume of hardware that you throw at it. I was talking about the /data/ and the /problem/ . Predicting movie ratings is a hell of a lot harder than feature detection.