Name
Abstract | ||
|---|---|---|
Scientific visualization software increasingly needs to support many-core architectures. However, development time is a significant challenge due to the breadth and diversity of both visualization algorithms and architectures. With this work, we introduce a development environment for visualization algorithms on many-core devices that extends the traditional data-parallel primitive (DPP) approach with several existing constructs and an important new construct: meta-DPPs. We refer to our approach as MCD3 - Meta-DPPs, Convenience routines, Data management, DPPs, and Devices. The twin goals of MCD3 are to reduce developer time and to deliver efficient performance on many-core architectures, and our evaluation considers both of these goals. For development time, we study 57 algorithms implemented in the VTK-m software library and determine that MCD3 leads to significant savings. For efficient performance, we survey ten studies looking at individual algorithms and determine that the MCD3 hardware-agnostic approach leads to performance comparable to hardware-specific approaches: sometimes better, sometimes worse, and better in the aggregate. In total, we find that MCD3 is an effective approach for scientific visualization libraries to support many-core architectures. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.parco.2021.102834 | PARALLEL COMPUTING |
Keywords | DocType | Volume |
Scientific visualization, Many-core architectures, Data-parallel primitives | Journal | 108 |
ISSN | Citations | PageRank |
0167-8191 | 1 | 0.36 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenneth Moreland | 1 | 1 | 1.03 |
| Robert Maynard | 2 | 1 | 0.36 |
| Dave Pugmire | 3 | 152 | 18.62 |
| Abhishek Yenpure | 4 | 1 | 0.70 |
| Allison Vacanti | 5 | 1 | 0.36 |
| Matthew Larsen | 6 | 1 | 3.40 |
| Hank Childs | 7 | 264 | 33.50 |