Predicting Performance of Communications and Computations under Memory Contention in Distributed HPC Systems - Archive ouverte HAL Access content directly
Journal Articles International Journal of Networking and Computing Year : 2023

Predicting Performance of Communications and Computations under Memory Contention in Distributed HPC Systems

(1) , (1) , (1)
1

Abstract

To amortize the cost of MPI communications, distributed parallel HPC applications can overlap network communications with computations in the hope that it improves global application performance. When using this technique, both computations and communications are running at the same time. But computation usually also performs some data movements. Since data for computations and for communications use the same memory system, memory contention may occur when computations are memory-bound and large messages are transmitted through the network at the same time. In this paper we propose a model to predict memory bandwidth for computations and for communications when they are executed side by side, according to data locality and taking contention into account. Elaboration of the model allowed to better understand locations of bottleneck in the memory system and what are the strategies of the memory system in case of contention. The model was evaluated on many platforms with different characteristics, and showed a prediction error in average lower than 4 %.
Fichier principal
Vignette du fichier
ijnc.pdf (1.59 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03871630 , version 1 (09-01-2023)

Identifiers

  • HAL Id : hal-03871630 , version 1

Cite

Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher. Predicting Performance of Communications and Computations under Memory Contention in Distributed HPC Systems. International Journal of Networking and Computing, 2023, Special Issue on Workshop on Advances in Parallel and Distributed Computational Models 2022, 13 (1), pp.30. ⟨hal-03871630⟩
0 View
0 Download

Share

Gmail Facebook Twitter LinkedIn More