Parallel Computing for Computational Finance Applications: A Case Study Parallelizing NAG with Zircon Software

Analysts, scientist, engineers, and multimedia professionals require massive processing power to analyze financial trends, create test simulations, model climate, compile code, render video, decode genomes and other complex tasks. Although these groups could use specialized super computers, the custom development time and the hardware costs are prohibitive. This paper describes how we applied the Zircon adaptive high-performance computing software platform and tools with the NAG C library to substantially improve the performance of a representative complex computational finance application via distribution and parallelization, thereby reducing the total computation time from several hours to several minutes.