I've waited 20 years for something like that, thanks for posting! FPGAs are great but I think the biggest problem with them is that they're an array of gates i

I've waited 20 years for something like that, thanks for posting! FPGAs are great but I think the biggest problem with them is that they're an array of gates instead of logic units (like ALUs). So the learning curve to get to the point where you can place an array of cores and memories and have them all communicate is so high that most people never get that far. So that's been a huge barrier to exploring the problem spaces that GPUs are currently used for like AI and physics simulations. Hopefully using languages like Go/Elixer/Erlang/MATLAB/Octave etc will alleviate that to some degree. My gut feeling is that in 3-5 years we'll reach the limits of what SIMD can accomplish and we'll find it difficult to do the kinds of general-purpose MIMD computing needed to move beyond the basic building blocks of AI like neural nets and genetic algorithms. I stumbled onto these links a month and a half ago and I think something like this will make writing generalized/abstract highly parallelized code tractable again: http://aggregate.org/MOG/ http://aggregate.org/MOG/ https://en.wikipedia.org/wiki/Flynn%27s_taxonomy https://en.wikipedia.org/wiki/Flynn%27s_taxonomy Original at: https://news.ycombinator.com/item?id=17419917 https://news.ycombinator.com/item?id=17419917