Name
Abstract | ||
|---|---|---|
There has been a large increase in the amount of work on hierarchical low-rank approximation methods, where the interest is shared by multiple communities that previously did not intersect. This objective of this article is two-fold; to provide a thorough review of the recent advancements in this field from both analytical and algebraic perspectives, and to present a comparative benchmark of two highly optimized implementations of contrasting methods for some simple yet representative test cases. The first half of this paper has the form of a survey paper, to achieve the former objective. We categorize the recent advances in this field from the perspective of compute-memory tradeoff, which has not been considered in much detail in this area. Benchmark tests reveal that there is a large difference in the memory consumption and performance between the different methods. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-62426-6_17 | Lecture Notes in Computational Science and Engineering |
Field | DocType | Volume |
Mathematical optimization,Algebraic number,Computer science,Matrix (mathematics),Theoretical computer science,Implementation,Low-rank approximation,Fast multipole method,Test case,The Intersect | Journal | 117 |
ISSN | Citations | PageRank |
1439-7358 | 2 | 0.37 |
References | Authors | |
43 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rio Yokota | 1 | 209 | 25.73 |
| Huda Ibeid | 2 | 25 | 4.06 |
| David E. Keyes | 3 | 407 | 81.69 |