Dynamic workload optimisation on NUMA and heterogeneous architectures

  1. Rubén Laso Rodríguez
Supervised by:
  1. José Carlos Cabaleiro Domínguez Director
  2. Tomás F. Pena Director

Defence university: Universidade de Santiago de Compostela

Fecha de defensa: 22 May 2023

Committee:
  1. Javier Díaz Bruguera Chair
  2. Dora Blanco Heras Secretary
  3. Vicente José Blanco Pérez Committee member
Department:
  1. Department of Electronics and Computing

Type: Thesis

Teseo: 810337 DIALNET lock_openMINERVA editor

Abstract

This thesis faces the challenges of dynamic workload optimisation and workload balancing in two different problems: in conventional systems using heterogeneous (CPU and GPU) parallelism, and in NUMA systems. On one hand, a library named IHP is proposed. Dynamically, CPU and GPU performance are evaluated so computational workload is divided accordingly. Results show that execution times can be improved between 3% and 55% depending on the code and the performance of the computing units. On the other hand, a tool for migrating threads and memory pages in NUMA systems has been developed. This tool incorporates several algorithms that, considering performance measurements, decide whether migrations are required. Experiments show that performance can be improved by up to 47%, particularly in multi-tasking scenarios.