Restructuring expression dags for efficient parallelization
For practitioners in robust geometric computation, this work provides methods to speed up exact decision-making using parallelization.
The paper shows that exact-decision number types based on expression dags can be evaluated faster through parallelization on multiple cores, and compares restructuring methods for the expression dag to improve running time.
In the field of robust geometric computation it is often necessary to make exact decisions based on inexact floating-point arithmetic. One common approach is to store the computation history in an arithmetic expression dag and to re-evaluate the expression with increasing precision until an exact decision can be made. We show that exact-decisions number types based on expression dags can be evaluated faster in practice through parallelization on multiple cores. We compare the impact of several restructuring methods for the expression dag on its running time in a parallel environment.