Parallel techniques in irregular codes: cloth simulation as case of study

This paper discusses and compares different irregular reduction parallelization techniques on ccNUMA share memory machines. Broadly speaking, we may classify them into two groups: privatization-based and data partitioning-based methods. In this paper we describe a framework, based on data affinity, that permits to develop various algorithms inside the group of the data partitioning-based techniques. All these techniques and approaches are analyzed and adapted to the computational structure of a real, physically based, cloth simulator.