We've discussed data flow parallelism here before.  I'd like to propose 
starting a project.

Data flow computing is an interesting model because it exposes the maximum 
amount of parallelism.   OpenMP, even with tasks and other 3.0 extensions, 
can't take advantage of all the parallelism inherent in some algorithms.   With 
multi-core chips dominating the industry, multi-threaded programming is growing 
in importance.  The scalability of programs needs to increase to keep pace with 
the increasing number of cores.  Now is the time to take a look at the data 
flow programming model again.  

To start the project I have a C and Fortran API called CORD which allows coarse 
grain data flow.  I have used it to achieve highly parallel implementations of 
some linear algebra algorithms specifically the LU, QR, and Cholesky 
factorizations.  CORD has extensions for matrix decompositions to support 
linear algebra.   This should provide a model for exploring data flow 
parallelism in other domains.   

Thanks, 
Brad
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