

Simpler Programming for Multicore Computers - prakash
http://www.technologyreview.com/Infotech/18597/

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Locke1689
Very interesting. Here's the paper
[http://groups.csail.mit.edu/commit/papers/06/gordon-
asplos06...](http://groups.csail.mit.edu/commit/papers/06/gordon-
asplos06.pdf), which is what you really want to read. From my brief perusal,
it looks inventive, but maybe not practical.

By that I mean that its (as it states in the name) a stream-oriented
programming language. If you're calculating FFTs (and many people are,
especially in high-performance computing), then this could be very useful.
Essentially, your language would fit your coding model, which is much easier
than adapting say, C, to the same task.

The possible problems I see here are 1) I haven't actually seen a
parallelization graph for even something simple like linear algebra vs. number
of cores and 2) there are many cases in which I can see this as being just as
complicated as threading/semaphores/whatever. If the application you're using
does not lend itself to concise representation in the stream metaphor then
this could lead to more problems than solutions.

For two other "next-gen" languages that seek to yield an implicitly parallel
solution, see Manticore (<http://manticore.cs.uchicago.edu/> University of
Chicago) and Data Parallel Haskell
(<http://www.haskell.org/haskellwiki/GHC/Data_Parallel_Haskell> mostly
University of New South Wales but Peyton-Jones is putting in some time as
well).

~~~
Locke1689
OK, so careful reading turns up this gem

 _Our compiler achieves consistent and excellent parallelization of our
benchmark suite to a 16-corearchitecture, with a mean speed up of 11.2x over
sequential, single-core performance._

Unfortunately, I still can't seem to find the standard Time vs. Cores graph.

