Studies on the energy and deep memory behaviour of a cache-oblivious, task-based hyperbolic PDE solver

Charrier, D.E.; Hazelwood, B.; Tutlyaeva, E.; Bader, M.; Dumbser, M.; Kudryavtsev, A.; Moskovsky, A.; Weinzierl, T.

Авторы: Charrier Dominic E., Hazelwood Benjamin, Tutlyaeva Ekaterina, Bader Michael, Dumbser Michael, Kudryavtsev Andrey, Moskovsky Alexander, Weinzierl Tobias
Журнал: International Journal of High Performance Computing Applications
Том: 33
Номер: 5
Год издания: 2019
Издательство: SAGE Publications
Местоположение издательства: United States
Первая страница: 973
Последняя страница: 986
DOI: 10.1177/1094342019842645
Аннотация: We study the performance behaviour of a seismic simulation using the ExaHyPE engine with a specific focus on memory characteristics and energy needs. ExaHyPE combines dynamically adaptive mesh refinement (AMR) with ADER-DG. It is parallelized using tasks, and it is cache efficient. AMR plus ADER-DG yields a task graph which is highly dynamic in nature and comprises both arithmetically expensive tasks and tasks which challenge the memory’s latency. The expensive tasks and thus the whole code benefit from AVX vectorization, although we suffer from memory access bursts. A frequency reduction of the chip improves the code’s energy-to-solution. Yet, it does not mitigate burst effects. The bursts’ latency penalty becomes worse once we add Intel Optane technology, increase the core count significantly or make individual, computationally heavy tasks fall out of close caches. Thread overbooking to hide away these latency penalties becomes contra-productive with noninclusive caches as it destroys the cache and vectorization character. In cases where memory-intense and computationally expensive tasks overlap, ExaHyPE’s cache-oblivious implementation nevertheless can exploit deep, noninclusive, heterogeneous memory effectively, as main memory misses arise infrequently and slow down only few cores. We thus propose that upcoming supercomputing simulation codes with dynamic, inhomogeneous task graphs are actively supported by thread runtimes in intermixing tasks of different compute character, and we propose that future hardware actively allows codes to downclock the cores running particular task types.
Добавил в систему: Московский Александр Александрович

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Studies on the energy and deep memory behaviour of a cache-oblivious, task-based hyperbolic PDE solverстатья Исследовательская статья