Association for Computing Machinery
In this paper the authors introduce a novel mixed precision methodology applicable to any Monte Carlo (MC) simulation. It involves the use of data-paths with reduced precision, and the resulting errors are corrected by auxiliary sampling. An analytical model is developed for a reconfigurable accelerator system with a Field-Programmable Gate Array (FPGA) and a General Purpose Processor (GPP). Optimization based on mixed integer geometric programming is employed for determining the optimal reduced precision and optimal resource allocation among the MC data-paths and correction data-paths.