A cache-optimal alternative to the unidirectional hierarchization algorithm

3Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The sparse grid combination technique provides a framework to solve high-dimensional numerical problems with standard solvers by assembling a sparse grid from many coarse and anisotropic full grids called component grids. Hierarchization is one of the most fundamental tasks for sparse grids. It describes the transformation from the nodal basis to the hierarchical basis. In settings where the component grids have to be frequently combined and distributed in a massively parallel compute environment, hierarchization on component grids is relevant to minimize communication overhead. We present a cache-oblivious hierarchization algorithm for component grids of the combination technique. It causes (Formula presented.) cache misses under the tall cache assumption M = ω (Bd).1 Here, Gℓ denotes the component grid, d the dimension, M the size of the cache and B the cache line size. This algorithm decreases the leading term of the cache misses by a factor of d compared to the unidirectional algorithm which is the common standard up to now. The new algorithm is also optimal in the sense that the leading term of the cache misses is reduced to scanning complexity, i.e., every degree of freedom has to be touched once. We also present a variant of the algorithm that causes (Formula presented.) cache misses under the assumption M = ω (B). The new algorithms have been implemented and outperform previously existing software. In several cases the measured performance is close to the best possible.

Cite

CITATION STYLE

APA

Hupp, P., & Jacob, R. (2016). A cache-optimal alternative to the unidirectional hierarchization algorithm. In Lecture Notes in Computational Science and Engineering (Vol. 109, pp. 103–132). Springer Verlag. https://doi.org/10.1007/978-3-319-28262-6_5

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free