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Scaling To a Million Cores and Beyond
mattaw writes "In my blog post I describe a system designed to test a route to the potential future of computing. What do we do when we have computers with 1 million cores? What about a billion? How about 100 billion? None of our current programming models or computer architecture models apply to machines of this complexity (and with their corresponding component failure rate and other scaling issues). The current model of coherent memory/identical time/everything can route to everywhere; it just can't scale to machines of this size. So the scientists at the University of Manchester (including Steve Furber, one of the ARM founders) and the University of Southampton turned to the brain for a new model. Our brains just don't work like any computers we currently make. Our brains have a lot more than 1 million processing elements (more like the 100 billion), all of which don't have any precise idea of time (vague ordering of events maybe) nor a shared memory; and not everything routes to everything else. But anyone who argues the brain isn't a pretty spiffy processing system ends up looking pretty silly. In effect, modern computing bears as much relation to biological computing as the ordered world of sudoku does to the statistical chaos of quantum mechanics.
Correct, some problems are serial - at least in current world, another topic! But parallelism is not same as threads - you can run any number of tasks, possible since 60's or 70's depends on who you ask. Unfortunately today, the younger generation has to learn the multi-tasking again, all they know (if they know!) is multi-threading, another way to make parallel processing but not the only. There is much, much more in parallel processing - code is not the only issue but one where more "cores" help. Sometimes wonder - non-locking memory management and queue processing are old, old - see some IBM research from 70's, how many has even heard of those? Very useful when several "cores"!