> On Aug 14, 2015, at 6:53 PM, Logan Streondj <[email protected]> wrote: > I agree that Hadoop is not useful for supercomputing applications. I'm not > sure if you are implying that this is the basis of your statement, otherwise > feel free to elaborate. > > Map/reduce/expand works well on GPU's in practice, since there are many > relatively slow processors which are independent of each other.
Scatter/Gather, Map/Reduce, etc style computing models, whether implemented on a GPU or Hadoop, are very poor for many types of parallel computing. It only works if your problem is in the tiny subset that is embarrassingly parallel in a topological sense. Most interesting algorithms are not in this class. Put more simply, for most interesting applications of parallel computation, the processors cannot be “independent of each other”. The ability to design efficient parallel data flows between compute elements is rather important for many classes of algorithm. Join algorithms, for example, which are central to graph traversal. This, by the way, is why barrel processing architectures are far more interesting than GPU architectures (or FPGAs for that matter) when it comes to parallel computations. Barrel processors can efficiently express very sophisticated topological parallelism; GPUs are optimized for pure data parallelism. > This is of course similar to the brain, where each neuron is relatively > independent, making it's decision to fire based on dendrites and possibly > micro-tubules. No, it is not similar to the brain. The brain has an incredibly complicated computational topology between neurons. It is not convertible into a simple data parallel problem — that tacitly assumes neurons do not talk to each other. Cheers, Andrew ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
