Adaptive algebraic multigrid on SIMD architectures

TL;DR

This paper discusses the implementation and optimization of an adaptive algebraic multigrid solver on SIMD architectures, especially Intel Xeon Phi, highlighting performance improvements and potential bottleneck reductions.

Contribution

It provides detailed implementation strategies for SIMD optimization of the DD-αAMG multigrid code and discusses vectorization techniques to enhance performance.

Findings

Optimized multigrid code for SIMD architectures.

Identified bottlenecks and proposed vectorization solutions.

Demonstrated suitability of the code for SIMD hardware.

Abstract

We present details of our implementation of the Wuppertal adaptive algebraic multigrid code DD-$\alpha$AMG on SIMD architectures, with particular emphasis on the Intel Xeon Phi processor (KNC) used in QPACE 2. As a smoother, the algorithm uses a domain-decomposition-based solver code previously developed for the KNC in Regensburg. We optimized the remaining parts of the multigrid code and conclude that it is a very good target for SIMD architectures. Some of the remaining bottlenecks can be eliminated by vectorizing over multiple test vectors in the setup, which is discussed in the contribution of Daniel Richtmann.