Opportunities for shared memory parallelism in financial modeling

Although much has been written about the “multi-core discontinuity”, and the impact on mathematical software, see, for example, [KD, LM], the full benefits to quantitative finance have yet to be realized. The purpose of this paper is to highlight the numerical structure of some common fixed income modeling problems with the aim of demonstrating how shared-memory parallelism may be brought to bear on improving performance, ultimately allowing us to calibrate larger and more complete models sufficiently fast to be useful in market making and risk management.