logo SBA

ETD

Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-06132019-230957


Tipo di tesi
Tesi di laurea magistrale
Autore
UMANI, FEDERICO
URN
etd-06132019-230957
Titolo
Modelling Simultaneous Multithreading Contribution to Performances and Power Consumption
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Dott. De Sensi, Daniele
Parole chiave
  • linear regression model
  • parallel computing
  • power-aware computing
  • self-adaptive computing
  • simultaneous multithreading
Data inizio appello
26/07/2019
Consultabilità
Completa
Riassunto
Energy demanding trend in Information and Communication Technologies makes power consumption an important metric in parallel computations. In this thesis we focus on the contribution brought by the Simultaneous Multithreading (SMT) technology both on performances and on power consumption. We build a linear regression model that integrates SMT and we show that it can predict both metrics more accurately with respect to another model that ignores SMT. This is tested both on offline data, by calculating the model error for a test set, and online by integrating it in Nornir, a framework for self-adaptive computing.
File