1 research outputs found
DuctTeip: An efficient programming model for distributed task based parallel computing
Current high-performance computer systems used for scientific computing
typically combine shared memory computational nodes in a distributed memory
environment. Extracting high performance from these complex systems requires
tailored approaches. Task based parallel programming has been successful both
in simplifying the programming and in exploiting the available hardware
parallelism for shared memory systems. In this paper we focus on how to extend
task parallel programming to distributed memory systems. We use a hierarchical
decomposition of tasks and data in order to accommodate the different levels of
hardware. We test the proposed programming model on two different applications,
a Cholesky factorization, and a solver for the Shallow Water Equations. We also
compare the performance of our implementation with that of other frameworks for
distributed task parallel programming, and show that it is competitive