Name
Abstract | ||
|---|---|---|
Particle advection, a fundamental building block for many flow visualization algorithms, is very difficult to parallelize efficiently. That said, work requesting is a promising technique to improve parallel performance for particle advection. With this work, we introduce a new work requesting-based method which uses the Lifeline scheduling method. To evaluate the impact of this new algorithm, we ran 92 experiments, running at concurrencies as high as 8192 cores, data sets as large as 17 billion cells, and as many as 16 million particles, comparing against other work requesting scheduling methods. Overall, our results show that Lifeline has significantly less idle time than other approaches, since it reduces the number of failed attempts to request work. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LDAV48142.2019.8944355 | 2019 IEEE 9th Symposium on Large Data Analysis and Visualization (LDAV) |
Keywords | Field | DocType |
Work requesting,Visualization,Parallel particle advection,Lifeline-Based scheduling | Data set,Visualization,Scheduling (computing),Computer science,Parallel computing,Advection,Flow visualization,Particle,Idle time | Conference |
ISSN | ISBN | Citations |
2373-7514 | 978-1-7281-2606-7 | 0 |
PageRank | References | Authors |
0.34 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roba Binyahib | 1 | 1 | 1.71 |
| Dave Pugmire | 2 | 152 | 18.62 |
| Boyana Norris | 3 | 417 | 39.46 |
| Hank Childs | 4 | 264 | 33.50 |