Name
Title | ||
|---|---|---|
Accelerating In-Transit Co-Processing For Scientific Simulations Using Region-Based Data-Driven Analysis |
Abstract | ||
|---|---|---|
Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a data-driven approach that uses the proposed method to accelerate in-transit co-processing of large-scale simulations. We use the importance metrics to simultaneously employ multiple compression methods on different data regions to accelerate the in-transit co-processing. Our approach strives to adaptively compress data on the fly and uses load balancing to counteract memory imbalances. We demonstrate the method's efficiency through a fluid mechanics application, a Richtmyer-Meshkov instability simulation, showing how to accelerate the in-transit co-processing of simulations. The results show that the proposed method expeditiously can identify regions of interest, even when using multiple metrics. Our approach achieved a speedup of 1.29x in a lossless scenario. The data decompression time was sped up by 2x compared to using a single compression method uniformly. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.3390/a14050154 | ALGORITHMS |
Keywords | DocType | Volume |
visualization, parallel computing, in-transit, co-processing | Journal | 14 |
Issue | Citations | PageRank |
5 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marcus Wallden | 1 | 0 | 1.35 |
| Masao Okita | 2 | 8 | 5.79 |
| Fumihiko Ino | 3 | 317 | 38.63 |
| D. Drikakis | 4 | 79 | 9.22 |
| Ioannis Kokkinakis | 5 | 0 | 0.34 |