Bounding the delays of the MPPA network-on-chip with network calculus: Models and benchmarks - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Performance Evaluation Année : 2020

Bounding the delays of the MPPA network-on-chip with network calculus: Models and benchmarks

Résumé

The Kalray MPPA2-256 processor integrates 256 processing cores and 32 management cores on a chip. These cores are grouped into clusters and clusters are connected by a high-performance network on chip (NoC). This NoC provides hardware mechanisms (ingress traffic limiters) that can be configured to offer service guarantees. This paper introduces a network calculus formulation, designed to configure the NoC traffic limiters, that also computes guarantee upper bounds on the NoC traversal latencies. This network calculus formulation accounts for the traffic shaping performed by the NoC links, and can be solved using linear programming. This paper then shows how existing network calculus approaches (the Separated Flow Analysis — SFA ; the Total Flow Analysis — TFA ; the Linear Programming approach — LP) can be adapted to analyze this NoC. The delay bounds obtained by the four approaches are then compared on two case studies: a small configuration coming from a previous study, and a realistic configuration with 128 or 256 flows. From these cases studies, it appears that modeling the shaping introduced by NoC links is of major importance to get accurate bounds. And when all packets have the same size, modeling it reduces the bound by 20%–25% on average.
Fichier principal
Vignette du fichier
dtis21044PostPrint-Article-2.pdf (982.22 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03170466 , version 1 (16-03-2021)

Identifiants

Citer

Marc Boyer, Amaury Graillat, Benoît Dupont de Dinechin, Jörn Migge. Bounding the delays of the MPPA network-on-chip with network calculus: Models and benchmarks. Performance Evaluation, 2020, 143, pp.102124. ⟨10.1016/j.peva.2020.102124⟩. ⟨hal-03170466⟩

Collections

ONERA CNRS
45 Consultations
195 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More