2/ But, don't forget that GPGPU programming is an tool, and not *really* a general one. The instrument selects for theories whose testability comports to a specific set of hardware-associated constraints. And, that subset need not intersect the one with all the good theory.
-
-
Show this threadThanks. Twitter will use this to make your timeline better. UndoUndo
-
-
-
I think that GPUs (and multi-core CPUs) made Bayes Methods speedier, but WinBUGS made Bayesian Methods more accessible to the general scientist/professional, leaving programmers like me to monitor convergence and model structure for basic efficiency https://en.wikipedia.org/wiki/WinBUGS
-
That's certainly true, in the same way that
@fchollet's Keras framework makes deep learning generally accessible to non-experts. But, my point is more about how GPUs expand the set of tractable, and researcher rush in (sometimes blindly) to use that, kinda like Parkinson's law. - 1 more reply
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.