A Study on Balancing Parallelism, Data Locality, and Recomputation in Existing PDE Solvers | IEEE Conference Publication | IEEE Xplore

A Study on Balancing Parallelism, Data Locality, and Recomputation in Existing PDE Solvers


Abstract:

Structured-grid PDE solver frameworks parallelize over boxes, which are rectangular domains of cells or faces in a structured grid. In the Chombo framework, the box sizes...Show More

Abstract:

Structured-grid PDE solver frameworks parallelize over boxes, which are rectangular domains of cells or faces in a structured grid. In the Chombo framework, the box sizes are typically 163 or 323, but larger box sizes such as 1283 would result in less surface area and therefore less storage, copying, and/or ghost cells communication overhead. Unfortunately, current on node parallelization schemes perform poorly for these larger box sizes. In this paper, we investigate 30 different inter-loop optimization strategies and demonstrate the parallel scaling advantages of some of these variants on NUMA multicore nodes. Shifted, fused, and communication-avoiding variants for 1283 boxes result in close to ideal parallel scaling and come close to matching the performance of 163 boxes on three different multicore systems for a benchmark that is a proxy for program idioms found in Computational Fluid Dynamic (CFD) codes.
Date of Conference: 16-21 November 2014
Date Added to IEEE Xplore: 19 January 2015
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Conference Location: New Orleans, LA, USA

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