Name
Abstract | ||
|---|---|---|
The advection of integral lines is an important computational kernel in vector field visualization. We investigate how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a baseline, we formulate a streamline tracing algorithm that facilitates auto-vectorization by an optimizing compiler. We analyze this algorithm and propose two different optimizations. Our results show that particle tracing does not per se benefit from SIMD computation. Based on a careful analysis of the auto-vectorized code, we propose an optimized data access routine and a re-packing scheme which increases average SIMD efficiency. We evaluate our approach on three different, turbulent flow fields. Our optimized approaches increase integration performance up to 5.6x over our baseline measurement. We conclude with a discussion of current limitations and aspects for future work. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.2312/pgv.20151154 | EGPGV |
Field | DocType | Citations |
Kernel (linear algebra),Computer science,Parallel computing,Network packet,SIMD,Theoretical computer science,Optimizing compiler,Data access,Tracing,Hardware architecture,Computation | Conference | 0 |
PageRank | References | Authors |
0.34 | 23 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bernd Hentschel | 1 | 16 | 3.21 |
| Jens Henrik Göbbert | 2 | 3 | 1.88 |
| Michael Klemm | 3 | 160 | 15.52 |
| Paul Springer | 4 | 1 | 0.73 |
| Andrea Schnorr | 5 | 0 | 0.68 |
| Torsten W. Kuhlen | 6 | 27 | 5.98 |