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{\large H. Carter Edwards \\
{\bf Performance Concerns when Iterating Hybrid-Parallel Kernels}}

Sandia National Laboratories \\ P O Box 5800 / MS 0382 \\ Albuquerque \\ NM 87185
\\
{\tt hcedwar@sandia.gov}\end{center}

Iterative algorithms are typically implemented by a sequence of calls to
simple computational kernels, such as the BLAS or their sparse
equivalent. Hybrid-parallelization of these kernels on clusters of nodes
with multicore CPUs or GPGPUs has demonstrated performance gains for
individual kernels. An iterative algorithm can realize a similar
performance gain only if the programming model for calling a sequence of
these kernels does not introduce significant overhead. Such a programming
model for hybrid-parallel kernels has been implemented in Trilinos'
ThreadPool library. A simple CG iterative solver is implemented using the
ThreadPool library and its hybrid-parallel performance is assessed.


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