The parallel computation of the smallest eigenpair of an acoustic problem with damping

Acoustic problems with damping may give rise to large quadratic eigenproblems, which require e cient and parallelizable solution algorithms. This paper describes such an algorithm: the Jacobi{Davidson solution method for quadratic eigenproblems. In particular, it describes its parallelization according to the Bulk Syn- chronous Programming model, and its implementation on the massively parallel CRAY T3D. Experimental results for a large-scale acoustic problem show that the method is e cient and parallelizes well, i.e. scales al- most linearly up to the maximum number of available processors.