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Upscaling ExaHyPE – on each and every core

Li, Baojiu; Schulz, Holger; Tuft, Adam; Weinzierl, Tobias; Zhang, Han

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Holger Schulz

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Mr Han Zhang
Post Doctoral Research Associate


We study a MPI+multithreaded PDE solver for hyperbolic partial differential equations. Each thread per rank handles a subdomain of the computational domain identified by a segment of a space-filling curve. The threads spawn additional tasks which should be used to compensate for ill-balancing between the threads running in fork-join mode. Our studies show that this tasks-over-BSP paradigm is not properly supported in some OpenMP runtimes, leads to NUMA pollution and is vulnerable to tiny tasks. It also suffers from many memory movements. Once we replace user data with smart pointers and hence avoid unnecessary copying, we propose to add a NUMA-aware queuing system on top of OpenMP, to batch multiple tasks into meta tasks which can spread out over idle cores. Many of these techniques are fixes to current OpenMP runtime implementations and we expect them to become unnecessary as the OpenMP runtimes evolve. The insights thus have pathfinding character.


Li, B., Schulz, H., Tuft, A., Weinzierl, T., & Zhang, H. (2023). Upscaling ExaHyPE – on each and every core. ARCHER2

Report Type Technical Report
Online Publication Date May 2, 2023
Publication Date 2023
Deposit Date May 5, 2023
Publicly Available Date May 5, 2023
Additional Information Publisher: ARCHER2
Type: monograph
Subtype: technical_report


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