🚀 go-pugleaf

In article <BURLEY.91May22040315@albert.gnu.ai.mit.edu>, burley@albert.gnu.ai.mit.edu (Craig Burley) writes:

|> But on some problems, parallelization (or even coprocessors, I suppose)
|> can have a superscalable (is this the right word?) effect on performance.
|> 
|> E.g. a program which runs in X units of time on a single processor can run
|> in X/10 units of time on eight parallel processors.  (Or even less time.)
|> 
|> But I think this works only for programs including solution-space searches
|> as critical elements of their algorithms.

There can be even more trivial reasons for super-linear speedup.

For example, the N processors together might have not only more real
memory than the single processor used as the base for the speedup
computation actually has, but they might together have more real
memory than is architecturally possible on the single processor.
-- 
                                   Dan Prener (prener @ watson.ibm.com)