In situ particle advection via parallelizing over particles

We extend the method for particle advection that parallelizes over particles to work in an in situ setting. We then compare our method with the typical method for in situ, parallelizing over data. Our experiments consist of parallelism at 512 cores, a data set with 67 million cells, and ten billion total advection steps. Our findings show that parallelizing over particles can be more than ten times faster for some workloads, for reasonable memory cost. Overall, the significance of these findings is to demonstrate that moving data can be worthwhile in some in situ settings.