FEAST is a hardware-oriented MPI based Finite Element solver toolkit. With the extension FEASTGPU the authors have previously demonstrated that significant speed-ups in the solution of the scalar Poisson problem can be achieved by the addition of GPUs as scientific co-processors to a commodity based cluster. In this paper we put the more general claim to the test: Applications based on FEAST, that ran only on CPUs so far, can be successfully accelerated on a co-processor enhanced cluster without any code modifications. The chosen solid mechanics code has higher accuracy requirements and a more diverse CPU/co-processor interaction than the Poisson example, and is thus better suited to assess the practicability of our acceleration approach. We present accuracy experiments, a scalability test and acceleration results for different elastic objects under load. In particular, we demonstrate in detail that the single precision execution of the co-processor does not affect the final accuracy. We establish how the local acceleration gains of factors 5.5 to 9.0 translate into 1.6- to 2.6-fold total speed-up. Subsequent analysis reveals which measures will increase these factors further.
@ARTICLE{GoWoSt_09FEASTSolid,
author = {Dominik G{\"o}ddeke and Hilmar Wobker and Robert Strzodka and Jamaludin Mohd-Yusof and Patrick McCormick and Stefan Turek},
title = {Co-Processor Acceleration of an Unmodified Parallel Solid Mechanics Code with {FEASTGPU}},
journal = {International Journal of Computational Science and Engineering (IJCSE)},
year = {2009},
month = nov,
volume = {4},
pages = {254--269},
number = {4},
publisher = {Inderscience},
}